Friday, May 26, 2017

CLIMATE CHANGE: THE SCIENCE University of British Columbia. Coursera. Roilo Golez notes. Coursera.

University of British Columbia

Dr Sara Harris: Hi everyone, welcome to this brief introduction to the state
of climate science.
We'll take a look at a little bit of climate data here,
and we'll see a lot more of it later in the course.
Scientific information about climate comes
from lots of sources that fall broadly into the categories of observations
of the world around us and modeling.
People have collected and continue to generate multiple lines of evidence
about how earth's climate system works and how it changes.
And, when multiple lines of evidence, generated
using all sorts of different approaches, pretty much converge
to a coherent picture, our confidence in our understanding of the system
goes up.
We don't know everything, of course, since knowing
everything is an impossible standard.
And there's still plenty to learn.
But we know a lot about how earth's climate system operates.
Here are a few observations.
First, people have measured global average surface temperature over time,
and that's gone up in the past century.

Figuring out global average surface temperature
is in itself a super challenging task, and several different groups
of scientists, using different approaches,
all end up with essentially the same story.
As a second example, people have measured
atmospheric CO2, which has also gone up since measurements
began in the late 1950s.
We have measurements of declining sea ice extent in the arctic
as time goes on.
And we have measurements of sea level rise.

These are all quite different measurements,
yet together they form a logical, coherent story
about climate, based essentially on how physics and chemistry work.

There's virtually zero argument about the trends in these measurements.
Here's another, slightly more complicated set of observations.
This animation represents changes in the distribution of summertime temperature
anomalies in the northern hemisphere over time.
So the word anomaly just means the difference
between a measurement and some average.
In this case, the average for comparison is average summer temperatures
between 1951 and 1980.
Temperature anomalies under the smooth curve in the grey area are considered
to be within what we'd call normal for that time period.
Values between minus 1 and minus 2 are considered to be colder than normal.
Between minus 2 and minus 3 are very cold.
And values to the left of minus 3 are considered extremely cold.
Similarly, on the red side, values between plus 1 plus 2
are considered hot.
Between plus 2 and plus 3 are very hot, and, to the right of plus 3,
considered extremely hot.
Over time, summertime temperatures have gradually shifted toward the warm end,
with many more instances of what used to be
considered extremely high temperatures.
And, what these data show, is that the probability
of getting extreme warm events is greater than it used to be.
And the probability of getting extreme cold events is lower than before.
We also have observations and measurements
of how earth's climate system changed in the past.
Here's the last million years, for example, which we'll look out
more closely later in the course.
Air bubbles trapped in ice preserve samples of the atmosphere
at times in the past, so we can directly measure things
like CO2 concentrations back through time, as far back as the ice cores go,
which is about 800,000 years.
We can reconstruct temperature records using a wide variety of approaches,
including things like the chemistry of sediments in the deep ocean,
the types of organisms that lived in the past, the chemistry of corals,
the chemistry of ice, and lots of other approaches.
We can use these records from the past to learn

how the earth's climate system has varied before
and how the parts are connected.
To get a little practice looking at data, here's a question for you.
You're going to find questions like this throughout the course for you
to try as you go along.
So here's the question.
What's the general relationship between temperature and CO2
overtime according to these data?
So, read the two vertical axis scales, and see what you think.


Earth’s climate system has many inter-related parts. Broadly, we can group the parts into four categories: the atmosphere, hydrosphere, biosphere, and geosphere. Within each category are a variety of materials with different roles in the climate system. For example, the atmosphere contains greenhouse gases, non-greenhouse gases, clouds, reflective aerosols, and non-reflective aerosols. The hydrosphere contains ocean water, sea ice, glaciers, ice sheets, and water vapor. Materials constantly exchange among these four basic categories, some via very fast processes, others via very slow processes.
A different way to think about Earth’s climate system is to categorize based on energy flow processes. We have energy coming in from the Sun, reflection of solar energy by various materials, and we have the greenhouse effect altering energy flows. Our four “materials” categories are intimately intertwined with the three “energy flow” categories. Considering materials together with energy flows yields places to look for mitigation options.
Learning Goals
By the end of this section, you will be able to:
1 Articulate the difference between weather and climate.
2 Describe the primary components of the Earth system: the atmosphere, hydrosphere, biosphere, and geosphere.
3 Explain how three primary factors each influence energy flow in Earth’s climate system: solar energy, reflectivity, and the greenhouse effect.

"Climate is what you expect; weather is what you get"
This saying encapsulates the difference between weather and climate.  Explore the links below (or others you find online) until you feel confident you can explain the differences between weather and climate.
Royal Meteorological Society:
National Center for Atmospheric Research:
National Geographic video (focuses mostly on weather):


Weather is the state of the atmosphere at any given time. Some places on the globe see very little change in weather from day to day; how boring is that? We are lucky in the UK that our weather is not as dangerous to life and property as it can be in other countries, but yet it can change from heavy rain to glorious sunshine in a matter of a couple of hours. A meteorologist will describe the weather in terms of accurate measurements of temperature, humidity, rainfall, pressure and many other factors – for example a temperature of 23.8°C, relative humidity of 67%, etc.  The weatherman on TV will be a bit less exact, but still give numbers for temperature (24°C) or wind speed (20mph).  But most people will simply use expressions such as “it’s nice and warm this afternoon” or “it’s raining cats and dogs”.
Here you can find out more about observing the weather, how weather forecasts are made, and see some interesting weather data and video resources.
Space Weather


Frost Fairs



Climate describes what the average of weather will be over a period of time. It will include not just the mean, but the variability and extremes, as these can have big impacts.  Climate is usually defined for different seasons or months, and averaged over a period of 30 years – currently the period 1971-2000 is used.  So we might read for a particular place that “The average maximum temperature in July is 25°C, with typically 2 days hotter than 30°C”, or “The average rainfall for June is a total of 35mm, with 10 days of no rain and 3 days where rainfall is more than 5mm”.
Here you can explore some of the UK’s most established climatological data sets and related climate statistics produced by the UK’s National Climate Information Centre.

"Pathway 2050" a look at different pathways
The 2050 Pathways work presents a framework through which to considers some of the choices and trade-offs we will have to make over the next forty years

  • video on climate change image

    "Talking Heads" Video
    on Climate Change

    Watch the RMetS Video on
    climate change. This features interviews with eminent scientists, including
    Professor Sir David King, Professor Chris Rapley and many others

Carbon Footprint: Interactive calculator
Why not use this interactive tool to calculate your own and your family's carbon footprint with this carbon calculator?
    Some important datasets:

Long time series of observations are important in detecting the changes in our climate.  Here are some interesting climate datasets used in the studies of climate change.  See data >>

    Aerosols and Climate

    This is the second in a series of articles about climate by top climate scientists and is by Professor Ellie Highwood, who is the Professor of Climate Physics at the University of Reading
    The image shows aerosol pollution over India
    The importance of atmospheric gases such as carbon dioxide for climate is well known and well publicised. However the tiny particles that are present in the atmosphere, or aerosols, also play crucial roles in weather and climate. Atmospheric aerosols can be either solid or liquid, with diameters of a few nanometers to tens of microns. There are two broad classes of aerosols. Primary aerosols are generated or emitted as solid particles, for example Saharan dust, sea salt or soot. Secondary aerosols are formed in the atmosphere by chemical reactions, for example ammonium sulphate aerosols are formed from the gases sulphur dioxide and ammonia, whilst organic aerosols are formed by chemical reactions acting on chemicals such as isoprene which is emitted by vegetation. Some aerosols have mainly natural origins (dust, sea salt, volcanic ash and volcanic sulphates), whilst others result at least partly from human activities (some soot, ammonium sulphate and ammonium nitrate). Aerosols are often mixed together, and can also be described by their size, e.g. PM10 is particles with diameter less than 10 micron.
    Once in the atmosphere, aerosols can have a variety of impacts. Aerosols reflect and absorb radiation from the sun. Thus a large concentration of most aerosol types will tend to scatter sunlight back to space, preventing the direct beam reaching the Earth's surface. This can lead to a cooling of the earth's surface, a change in the fluxes of latent heat and sensible heat, and a change in the distribution of heating in the atmosphere. Whilst the direct beam is prevented from reaching the surface, more scattered light is available and this affects photosynthesis. High aerosol concentrations can improve plant productivity, until other effects such as temperature or plant physiological issues become dominant. Aerosols are also responsible for clouds, and rainfall. Cloud droplets require an initial "seed" to start the condensation of water - this is provided by aerosols. Changes in aerosol can therefore lead to changes in cloud properties. For example, an increase in aerosol concentration in a cloudy region might mean more seeds for the water to condense on, therefore the available water is spread over a larger number of droplets and each individual droplet is smaller. Smaller droplets reflect more light, and this "indirect effect" of aerosol on cloud can lead to a cooling of the Earth's surface.
    Unlike several of the greenhouse gases, aerosols have a short lifetime in the lowest part of the atmosphere as they are washed out by rainfall. The main sources of aerosols are the highly populated regions of the world, particularly where coal is burnt in large quantities, and the deserts. Aerosols can also be a problem for air quality, and so emissions have reduced in Europe and the US in recent decades. This is interesting for climate change, because since aerosols cool climate, a reduction in aerosols in order to improve air quality, could lead to an extra warming of climate. Aerosols have also been proposed as a means of mitigating greenhouse gas warming (geo-engineering), either by using them near the Earth's surface to make extra clouds, or by injecting them into the stratosphere to reflect the sun's radiation to space.  However, the impacts of such scheme are complex and uncertain.

    Weather and Climate
    Aerosols and Climate
    Energy and Climate
    Dr Kevin Trenberth
    Climate Change
    Climate Data Sets
    Climate Change by Tim Palmer
    The El Niño Southern Oscillation
    The Indian Monsoon in a Changing Climate
    Has Global Warming Stalled?
    Image gallery
    Profiles of Meteorologists
    Weather Service Providers
    RMetS HQ Webcam
    /.section, /#sidebar-first
    Energy and Climate - Dr Kevin E Trenberth

    This is the first in a series of articles by renowned  scientists. In it, Dr Kevin Trenberth of UCAR talks about energy and climate and addresses the intriguing issue of "missing energy"
    Dr Kevin E Trenberth Biography
    Youtube clip about missing energy
    Climate change is very much involved with energy, most commonly in the form of heat but other forms of energy are also important. Radiation comes in from the sun (solar radiation at short wavelengths), and every body radiates according to its temperature (proportional to the fourth power of absolute temperature), so that on Earth we, and the surface and atmosphere radiate at infrared wavelengths.  Weather and climate on Earth are determined by the amount and distribution of incoming radiation from the sun.  For an equilibrium climate, global mean outgoing longwave radiation (OLR) necessarily balances the incoming absorbed solar radiation (ASR), but with redistributions of energy within the climate system to enable this to happen on a global basis.  Incoming radiant energy may be scattered and reflected by clouds and aerosols (dust and pollution) or absorbed in the atmosphere.  The transmitted radiation is then either absorbed or reflected at the Earth’s surface. Radiant solar (shortwave) energy is transformed into sensible heat (related to temperature), latent energy (involving different water states), potential energy (involving gravity and altitude) and kinetic energy (involving motion) before being emitted as longwave infrared radiant energy.  Energy may be stored, transported in various forms, and converted among the different types, giving rise to a rich variety of weather or turbulent phenomena in the atmosphere and ocean.  Moreover the energy balance can be upset in various ways, changing the climate and associated weather.
    The human influence on climate, arising mostly from the changing composition of the atmosphere, affects energy flows. Increasing concentrations of carbon dioxide and other greenhouse gases have led to a post-2000 imbalance at the TOA of 0.9±0.5 W m-2 (Trenberth et al. 2009) (Fig. 1), that produces “global warming”, or more correctly, an energy imbalance.  Tracking how much extra energy has gone back to space and where this energy has accumulated is possible, with reasonable closure for 1993 to 2003. Over the past 50 years, the oceans have absorbed about 90% of the total heat added to the climate system while the rest goes to melting sea and land ice, and warming the land surface and atmosphere. Because carbon dioxide concentrations have further increased since 2003 the amount of heat subsequently being accumulated should be even greater. However,  there was a slight decrease in solar insolation from 2000 until 2009 with the ebbing 11-year sunspot cycle; enough to offset 10 to 15% of the estimated net human induced warming.
    The coldest month this century was January 2008 as a strong La Niña developed and influenced conditions throughout 2009. The resulting cold conditions around the world led to less longwave radiation back to space, and less convection and fewer clouds over the Pacific leading to increase absorbed solar radiation.  Hence the net radiative imbalance at the top-of-atmosphere, as measured by CERES, showed a marked increase  of order 1 W m-2 relative to surrounding years.  These relative changes are well measured by CERES (Fig. 2).  Hence the conundrum: more energy but colder temperatures.  This gives rise to the concept of “missing energy” (Trenberth and Fasullo 2010).  Where is the energy going?    New estimates of ocean heat content show a growing large discrepancy between ocean heat content integrated for the upper 300 vs 700 vs total depth.  The latter continues a fairly steady upward trend while the surface temperatures and upper ocean heat content undergo a hiatus in warming after about 2004.  The role of the ocean in taking up energy well below the surface is emerging as a major issue in observations and modeling.  Improved monitoring of TOA energy imbalance such as from a suite of small radiometers in space would prove exceedingly useful.

    Fig. 1.  The global annual mean Earth’s energy budget for 2000 to 2005 (W m–2). The broad arrows indicate the schematic flow of energy in proportion to their importance.  From Trenberth et al. (2009).

    Climate Change

    Climate change refers to a significant change in climate (either global or regional) that lasts several decades or longer. This change may happen for several reasons: it could be due to purely natural changes in the climate system, it could arise from natural factors outside the climate system (for example changes in energetic volcanoes or radiation from the sun) or it could be a result of human activity.  Although the earth’s climate has changed considerably in the past (and will due in the future) because of natural factors, it is very likely that most of the global temperature rise observed since the middle of the last century has been caused by increasing greenhouse gases in the atmosphere from human activities such as fossil-fuel burning.

    Google Earth and Climate Change

    Google Earth highlights climate change effects
    Google Earth has teamed up with the UK Government, the Met Office Hadley Centre and the British Antartic Survey to highlight how climate change could affect the planet over the next 100 years and how the Antartic ice shelves have decreased over the last 50 years.
    The aim of this new project is to reach wider audiences and to educate us all about the actions we need to take to mitigate and adapt to our changing climate. The project introduces two new animated layers on top of Google Earth, an interactive mapping application.
    To access the new animations, you will need to have the Google Earth application downloaded onto your pc (Google Earth download link: Then download the new layers from
    Related information
    Rising Sea Level Animation

    by Zoltán Büki
    This file animates one effect of climate change - rising sea levels. You can use the slider to see what will happen near you.
    Note:You need to turn on the terrain in the "Layers" ...
    Open in Google Earth
    What it looks like

    The two overlaying animations show:
    global temperature changes for the next 100 years with the world getting hotter (increasing orange/red colours) over time and some regions warming more than others. The information, from the Met Office Hadley Centre, also includes “pop-ups” detailing the possible impacts of climate change.
    the retreat of the Antartic ice shelves since the 1950s developed by the British Antartic Survey. Information “pop-ups” present scientific facts, stories and news features.

    We can perhaps learn from numerical weather prediction where the benefits of developing global prediction models with high vertical and horizontal resolution are clear cut (confirmed most recently by predictions of Sandy). Of course, predicting a week ahead at these resolutions is much less computationally demanding than predicting a century ahead.
    Just as the nations of the world came together to fund the Large Hadron Collider, allowing scientists to study the moments after the Big Bang in the sort of detail needed to reveal the workings of mother nature, so the nations of the world should come together to fund the sort of supercomputers that would allow us to simulate the climate of the coming century with much greater reliability than is currently possible.  The impact that this will have for mitigation, adaptation and geoengineering policies is likely to be enormous.

    The El Niño Southern Oscillation

    The El Niño Southern Oscillation
    Mat Collins, Exeter Climate Systems, College of Engineering Mathematics and Physical Science, University of Exeter
    The temperature of the sea surface in the Eastern Tropical Pacific is usually around 27°C – pretty balmy by UK standards but reasonably cold for the tropics. Cooler waters from deeper in the ocean rise up in the Eastern Pacific, bringing nutrients that feed a thriving ecosystem. Every so often these cooler sea surface temperatures (SSTs) are replaced by warmer waters and this has a profound influence, not only on the number of fish that S. American fishermen can catch, but also on the atmospheric circulation above and the oceanic circulation below.
    Normally the cold SSTs in the East go along with warm SSTs in the west, which underlie a large area of moist atmospheric convection. This ‘warm pool’ convection is accompanied by strong easterly trade winds forming an atmospheric circulation named after the 19th Century scientist Sir Gilbert Walker – a past president of the Society. Below the surface of the ocean, the trade winds cause upwelling of cold ocean water from below in a process known as Ekman pumping. When this climatological situation is disturbed, this sets in a chain of events. If the trade winds weaken, then the warm SSTs in the west can move towards the east, bringing with them the atmospheric convection and further weakening the trade winds (a feedback first described by Jacob Bjerknes). The weakened trades also lead to reduced upwelling of cold water in the ocean, further enhancing the warm SSTs in the east and causing the ocean thermocline, a sharp vertical gradient of temperature around a few hundred meters below the surface, to become more horizontal in comparison to its normal state of being deeper in the west compared to the east. This is what we now call an El Niño event. The Walker Circulation in the atmosphere is weakened and displaced and, if we measure this by examining the surface pressure across the Pacific, traditionally by differencing the pressure records from Tahiti and Darwin, we see what Walker called the Southern Oscillation. Together they form the El Niño Southern Oscillation (ENSO).
    The study of ENSO has evolved along four prongs; observations, theory, numerical modelling and prediction:
    We now have a network of ocean bouys – the Tropical Atmosphere Ocean Array or TAO Array – which constantly measure the state of the upper-ocean and surface meteorological conditions. Combined with satellites, this gives us the ability to monitor ENSO in real-time. Since the last big El Niño in 1997/98 we have measured a succession of smaller warm and, sometimes protracted cold events, often known as La Niña. There is also some indication that recent El Niño events have had their SST signature concentrated in the central Pacific rather than extending all the way to the east coast of South America.
    Early theories of ENSO invoked ideas of eastward and westward propagating ocean waves carrying signals along the ocean thermocline. Later, such theories were refined to highlight the role of the recharge of heat content in the west as a pre-cursor to ENSO events. Theory has evolved to take into account other ocean and atmosphere processes to describe different types of ENSO events in which different processes dominate the initiation. For example, the difference between a ‘classical’ ENSO event in which the thermocline feedback is the dominant amplifier of SST anomalies, contrasted with a central Pacific or ‘Modoki’ event in which zonal advection of SST anomalies plays a dominate role (as has been seen in recent observations).
    The first numerical models of ENSO used simplified ocean dynamics and ‘static’ or thermodynamic atmospheres, but were able to capture the essential physics of the phenomena. As three-dimensional coupled atmosphere-ocean models were developed, they were initially very poor at generating spontaneous ENSO events. The balance of amplifying and damping processes in the ENSO cycle presents a considerable challenge for numerical models. More recently, coupled models have improved and can now generate ENSO variability that is similar to, if not exactly like, that which we observe. Evaluating and improving the ability of coupled models to simulate ENSO is now one of the high-priority areas for modelling centres.
    While much of the research into ENSO has been driven by a desire to understand the atmosphere-ocean system, ENSO also represents a source of potential predictive skill on seasonal and interannual time scales. Prediction schemes use a variety of tools from statistical models, through intermediate or simplified dynamical models to fully coupled models. Prediction integrates understanding, observation and modelling and we now have predictive skill for many areas that are ‘teleconnected’ to ENSO, many months in advance. Those predictions are regularly used by governments and individuals in future planning and provide an excellent example of the positive impact that science can have on society.
    My own interest in ENSO was motivated by wanting to understand how climate change might have an impact on the phenomena. We are now beginning to see some robust responses of climate models in turns of the mean climate of the tropical Pacific; reduced trade winds, a local maxima in warming along the equator, reduced upwelling and a rising but strengthening thermocline. However, these changes are challenged by recent observations and there is no consensus on how the changes in mean climate will affect the characteristics of ENSO variability in terms of changes in amplitude, frequency or spatial pattern. There is still plenty of research to do.

    Weather and Climate
    Aerosols and Climate
    Energy and Climate
    Climate Change
    Climate Data Sets
    Climate Change by Tim Palmer
    The El Niño Southern Oscillation
    The Indian Monsoon in a Changing Climate
    Has Global Warming Stalled?
    Image gallery
    Profiles of Meteorologists
    Weather Service Providers
    RMetS HQ Webcam
    /.section, /#sidebar-first
    Has Global Warming Stalled?

    by Kevin Trenberth
    Has global warming stalled? This question is increasingly being asked because of impressions about local weather being cool and wet, or because of impressions that the global mean temperature is not increasing at its earlier rate or the long-term rate expected from climate model projections.
    The answer depends a lot on what one means by “global warming”.  For some it is equated to the “global mean temperature”.  That quantity keeps going up but also has ups and downs from year to year.  More on that shortly. Why should it go up?  Well, because the planet is warming from human activities.
    With increasing carbon dioxide and other heat-trapping greenhouse gases in the atmosphere, there is an imbalance in energy flows in and out of the top-of-atmosphere: the greenhouse gases increasingly trap more radiation and hence create warming.   "Warming" really means heating, and so it can be manifested in many ways.  Rising surface temperatures are just one manifestation.  Melting Arctic sea ice is another.  So is melting of glaciers and other land ice that contribute to rising sea levels. Increasing the water cycle and invigorating storms is yet another.  However, most (over 90%) of the energy imbalance goes into the ocean, and several analyses have now shown this.  But even there, how much warms the upper layers of the ocean, which are linked to the surface, vs how much penetrates deeper into the ocean where it may not have much immediate influence, is a key issue.
    We have just published a new analysis showing that in the past decade about 30% of the heat has been dumped at levels below 700m, where most previous analyses stop. The first point is that this is fairly new, it is not there throughout the record.  The cause of the change is a particular change in winds, especially in the Pacific Ocean where the subtropical trade winds have become noticeably stronger, thereby changing ocean currents and increasing the subtropical overturning in the ocean, providing a mechanism for heat to be carried down into the ocean.   This is associated with decadal weather patterns in the Pacific, which are in turn related to the La Niña phase of the El Niño phenomenon.
    The second point is that we have found distinctive variations in global warming with El Niño: a mini global warming, in the sense of a global temperature increase, occurs in the latter stages of an El Niño event, as heat comes out of the ocean and warms the atmosphere.  There are also distinctive volcanic eruption signals in the ocean heat content record.  So these affect the perceptions of global warming.  Normal weather also interferes by generating clouds that reflect the sunshine, and there are fluctuations in the global energy imbalance from month to month.  But these average out over a year or so.  Another prominent source of natural variability in the Earth’s energy imbalance is changes in the sun itself, seen most clearly as the sunspot cycle.  From 2005 to 2010 the sun went into a quiet phase and the warming energy imbalance is estimated to have dropped by about 10 to 15%.
    Some of the penetration of heat into depths of the ocean is reversible, as it comes back in the next El Niño.  However, a lot is not: instead it contributes to the overall warming of the deep ocean that has to occur for the climate system to equilibrate.  It speeds that process up faster than generally assumed.  It means less short term warming at the surface but at the expense of a greater earlier long-term warming, and faster sea level rise.   So this has consequences.
    Coming back to the global temperature record: the past decade is by far the warmest on record. Human induced global warming really kicked in during the 1970s, and warming has been pretty steady since then.  But while the overall warming is about 0.16°C per decade, there are 3 10-year periods where there was a hiatus in warming. From 1977 to 1986, from 1987 to 1996, and from 2001-2012.  But at each end of these periods there were big jumps.   We find exactly the same sort of flat periods in climate model projections, lasting easily up to 15years in length. Focusing on the wiggles and ignoring the bigger picture of unabated warming is foolhardy, but one promoted by climate change deniers.  Global sea level keeps marching up at a rate of over 30 cm per century since 1992 (when global measurements via altimetry on satellites were made possible), and that is perhaps a better indicator that global warming continues unabated. Sea level rise comes from both the melting of land ice, thus adding more water to the ocean, plus the warming and thus expanding ocean itself.

    So the current hiatus in surface warming is a transient and global warming has not gone away: there is a continuing radiative imbalance at the top of atmosphere. But the global warming is manifested in a number of ways.
    Distinctive climate signals in reanalysis of global ocean heat content. M. A. Balmaseda, K. E. Trenberth, E.Källén, Geophys. Res. Lett.,Doi: 10.1002/grl.50382

    navigation table

    Our climate on Earth is different from the climates of other planets because of energy flows. This section is the place to (re-) familiarize yourself with temperature and energy units we’ll use in this course: degrees Celsius (°C), Kelvin (K), Joules (J), Watts (W), and Watts per square meter (W/m2). We’ll also have a look at how changes in energy in Earth’s climate system alter global average temperatures, expressed by an important quantity called the “climate sensitivity”. Is Earth’s temperature highly sensitive, or does it respond very little to changes in energy flows?
    Learning Goals
    By the end of this section, you will be able to:
    1 Translate among Kelvin, Celsius, and Fahrenheit temperature scales.
    2 Generate everyday analogies to describe energy (in Joules) and energy fluxes (in Watts/meter2) in intuitive terms.
    3 Given a change in energy flux, estimate a global temperature change using Earth’s climate sensitivity.

    Dennis' Code
    Weather and 
Climate Basics
Weather Wonders
Climate Change 

    What Is the Difference Between Weather and Climate?
    It’s a sweltering midsummer day. “It must be global warming,” mutters someone. But is it the Earth’s changing climate that has made the day so warm? Or, is it just the weather that is so unbearable?

    Weather is the mix of events that happen each day in our atmosphere including temperature, rainfall and humidity. Weather is not the same everywhere. Perhaps it is hot, dry and sunny today where you live, but in other parts of the world it is cloudy, raining or even snowing. Everyday, weather events are recorded and predicted by meteorologists worldwide.

    Climate in your place on the globe controls the weather where you live. Climate is the average weather pattern in a place over many years. So, the climate of Antarctica is quite different than the climate of a tropical island. Hot summer days are quite typical of climates in many regions of the world, even without the effects of global warming.
    Climates are changing because our Earth is warming, according to the research of scientists. Does this contribute to a warm summer day? It may, however global climate change is actually much more complicated than that because a change in the temperature can cause changes in other weather elements such as clouds or precipitation.
    Explore weather and climate!
    Click on links to the left to explore how dynamic forces within the atmosphere change our weather and climate. Learn what causes weather events and climate change and how NCAR scientists are exploring our atmosphere through scientific research.

    To Fahrenheit
    To Celsius
    To Kelvin
    Fahrenheit (F)
    (F - 32) * 5/9
    (F - 32) * 5/9 + 273.15
    Celsius (C or o)
    (C * 9/5) + 32
    C + 273.15
    Kelvin (K)
    (K - 273.15) * 9/5 + 32
    K - 273.15

    Two-way Temperature Converter

    To use this Converter type your value in a box and then click your mouse anywhere on the page (or press tab key).


    Dr Sara Harris: Welcome to the next lesson in module two.
    This lesson is energy basics and earth's climate sensitivity.
    Before this, you've practiced with the three most commonly used temperature
    scales, degrees Fahrenheit, degrees Celsius, and Kelvin.
    From now on we'll be using degrees Celsius or Kelvin.
    The great thing about these two scales is that the size of one degree
    is the same in both of them, it's just that the numbers
    are offset so zero degrees Celsius is the same as 273
    Kelvin and plus one degree Celsius is the same as 274 Kelvin, et cetera.
    In this lesson, we're going to talk about energy
    and start to get a sense of the energy in earth's climate system
    using some everyday analogies.
    In particular, we're interested in the amount of energy
    that needs to be added or subtracted from earth's climate system
    in order to change earth's average temperature by a degree, that's
    a Celsius or Kelvin degree.
    This quantity is called the climate sensitivity.
    Add energy and Earth's temperature will go up,
    subtract energy and Earth's temperature will go down, but by how much?
    If it only takes a small change in energy to change the temperature a lot,
    that means the climate is really sensitive,
    or if you add a lot of energy and the temperature changes only a little bit,
    the climate isn't very sensitive.
    So let's get started.
    One familiar form of energy is the energy in our food.
    Depending on where you live, you might or you might not
    see foods labeled with energy content.
    On the left, we have a food label that lists energy in quote, calories.
    We're going to call those food calories.
    On the right, we have a food label that list energy
    in both kilojoules, that's the kJ, and kilocalories, that's the kcal.
    The kilocalories on the right are actually the same as the food
    calories on the left.
    Using the data on the right though, we can convert food calories
    that is kcal to kilojoules or kJ.
    Joules are the units that we use in climate science.
    So the point is to develop some sense of what these units mean.
    So let's try it.
    From this label figure out how to convert
    between kcal, which are food calories and kilojoules,
    specifically, figure out how many kilojoules are in one kcal.
    Feel free to use a calculator.

    = 256/61= 4.19 kj/kcal


    Dr Sara Harris: You got it?
    If you divide by 256 kilojoules by 61 kilocalories,
    you find out that each kilocalorie is equivalent
    to a little more than four kilojoules, about 4.2 kilojoules
    to every kilocalorie.
    So there's about four times as much energy in one food calorie
    as there is in one kilojoule.
    Let's look at some examples.
    How much energy is there in a bowl of rice?

    This bowl of rice will get you about 240 food calories,
    which is the same as kilocalories.
    Using the conversion we just figured out,
    if we multiply 240 food calories by 4.2, we get around 1,000 kilojoules.
    So how many joules is that?
    Well, you might be familiar with kilobytes in computers or kilograms
    for how much things weigh, or kilometers for distance,
    so how many bytes are in one kilobyte?
    Well, there are 1,000 bytes.
    Grams in a kilogram, there are 1,000 grams,
    and there are 1,000 meters in a kilometer.
    So if we have 1,000 kilojoules, how many joules is that?


    Dr Sara Harris: If you said a million, you've converted correctly.
    If you said 1, you flipped the relationship
    between joules and kilojoules.
    The energy in a bowl of rice is about a million joules.
    What about an apple?
    An apple has about 100 food calories, or kcal, which is about 418 kilojoules,
    or 418,000 joules.

    When we're using joules, the numbers seem to get pretty big in comparison
    to everyday food calorie units.
    In Earth's climate system, one of the items that matters
    is the energy it takes to raise the temperature of water.
    To heat one gram of liquid water, which in volume is the amount of water
    in a little cubic centimeter-- to heat that by 1 Kelvin,
    it takes about 1/1,000 of a food calorie, or 4.18 joules.

    This is called the heat capacity of water.
    And all substances have a heat capacity.
    It's the amount of energy it takes to heat them up by a degree.
    For water, that's 4.18 joules per gram per Kelvin.
    So how much energy does it take to make a pot of tea?
    Say you start with a liter, which is 1,000 grams of water.
    And that water is just at the freezing point, but it's liquid.
    And you heat it to boiling, which is 100 degrees Celsius, or 373 Kelvin.
    You have to be each one of those 1,000 grams of water by 100 degrees.
    So you'd need 4.1 joules for each gram for each degree,
    or about an apple's worth of energy.
    Now let's add an element of time.
    You've probably heard of watts if you pay an electric bill.
    Watts are a unit that describes energy per time.
    Specifically, watts are joules per second.
    So back to the tea kettle, how fast is it heating up?
    How fast is energy being added?
    To bring your tea kettle boiling in two minutes,
    you would have to add those 418,000 joules within 2 minutes, which
    means you'd need to transfer energy to the water at a rate of about
    3,500 joules a second, or 3,500 watts.
    If all the energy from a 60 watt light bulb
    could go toward heating your kettle, it would take about two hours
    to heat at 60 joules per second.
    It's probably not the best way to get a cup of tea.
    In Earth's climate system, we have energy coming in, going out, traveling
    in all directions all the time.
    How much energy in how much time over what area?
    So now we're going to add area to our energy per time.
    Imagine if you were picnicking on a flying carpet, and your flying carpet
    was 1 meter square, and you were flying at the top of the atmosphere
    in the tropics at high noon.
    Your 1 meter square carpet at that location at that time
    would receive around 1360 watts.
    That's 1360 joules every second.
    You'd have to consume about 12 apples per hour
    to get the equivalent of the energy coming in from the sun,
    the 1360 watts per meter squared.
    With that energy, you could make a cup of tea in about five minutes.

    Because the earth is spherical and it rotates,
    the 1360 watts per meter squared gets spread out
    to an average over time of about 340 watts per meter squared,
    received at the top of the atmosphere.
    It's about like the energy output from 5 or 6 60 watt
    incandescent light bulbs all shining on 1 square meter.
    That last image was about the energy hitting
    the top of the earth's atmosphere.
    We'll get into the details later, but because of reflection,
    and also some absorption in the atmosphere, the Earth's surface
    only absorbs about half the amount received
    by your flying carpet up there.
    If we combine the amount of energy Earth's surface absorbs
    from the sun and the amount it absorbs from greenhouse
    gases in the atmosphere, it turns out that Earth's surface absorbs
    about 500 watts per meter squared.
    That's about equal to 4 and 1/2 apples an hour.
    Now, what if the watts per meter squared absorbed at Earth's surface changed
    for some reason.
    What would happen to earth's temperature?
    The amount of energy Earth's surface receives can change over time.
    And as we'll see, various parts of the climate system respond.
    Some parts respond slowly, like big ice sheets.
    Others respond very quickly, like water vapor in the atmosphere.
    The current best estimates are that if 1 watt per meter squared
    is added-- that's 1 additional joule every second for every square meter
    of Earth's surface-- then after Earth reaches equilibrium
    with the new situation, Earth's temperature
    would have increased by about 3/4 of a degree Celsius.
    This is what's called the climate sensitivity.
    How much warming do you get for a given increase in energy?
    This number, 3/4 of degree Celsius per watt per meter squared,
    has a range of possibility.
    If Earth's climate is a bit less sensitive than this,
    we'll see a weaker temperature response.
    If Earth's climate is a bit more sensitive,
    we'll see a stronger temperature response,
    and more heating than this number would predict.
    There's a range of estimates for the climate sensitivity,
    though many different approaches yield similar ranges.
    In this course, we'll use 1 watt per meter
    squared per 3/4 of a degree Celsius.
    Let's apply this relationship to an example.
    Assuming a climate sensitivity that is of 3/4
    of a degree Celsius for every additional watt per meter squared, what
    would happen if 4 watts per meter squared were added?
    By how much would Earth's temperature increase eventually
    once the planet reached equilibrium again?


    Dr Sara Harris: So if each watt per meter squared yields 3/4 of a degree Celsius,
    then four watts per meter squared yields four times that much, or three degrees
    So what kinds of changes might add four watts per meter squared
    of energy to earth's climate system?
    Earth's reflectivity might change by that much,
    or earth's greenhouse effect might change by that much.
    Or a combination of changes could produce four watts
    per meter squared difference.
    A handy and fairly common way to think about the climate sensitivity
    and relate it to a change in the greenhouse effect
    is that if the concentration of carbon dioxide in the atmosphere
    were to double, we'd get about an additional four
    watts per meter squared on average, over each square meter of earth's surface.
    This number includes some of the fast responses in the climate system
    that occur when CO2 increases, like increasing water vapor
    in the atmosphere.
    The effect, therefore, of doubling CO2 concentration is a temperature
    increase of about three degrees Celsius after the earth
    equilibrates to its new energy balance.
    We could get that four watts per meter squared
    by doubling from 100 parts per million to 200 parts per million CO2,
    and then we could get an additional four watts
    per meter squared by doubling from 200 parts per million
    to 400 parts per million.
    Or the four watts per meter squared might
    come from some other aspect of the climate system,
    perhaps an ice sheet expands, so that four more watts per meter squared
    gets reflected back to space, and earth cools by 3 degrees.
    Perhaps soot landing on white ice decreases the ice's reflectivity
    and adds more watts per meter squared absorbed by earth's surface.
    Or perhaps reflective aerosols increase or decrease.
    The combination of changes in the climate system, many of them
    interconnected, determine changes in the energy balance over time
    and therefore changes in temperature over time.
    In summary, the energy related units we'll be using in climate science
    are joules, watts, and watts per meter squared.
    Ultimately, the amount of energy in earth's climate system
    sets the planet's temperature.
    Temperature is one of the key metrics when we talk about climate.
    A little bit more energy can change our planet's temperature.
    Even though a degree or two might not seem like very much,
    it can make a big difference.

    Earth’s climate system is a dynamic assemblage of parts and interactions. Materials and energy flow through the system via all sorts of different processes. And both stocks and flows can be perturbed. Tweaking one part of the system can induce changes in other parts, which sometimes come back around to influence the first part again, via feedback loops. Climate scientists seek to understand how Earth’s climate system works, at various levels of complexity, and it gets quite complex quite quickly.
    Systems thinking is not easy, so if you find stocks, flows, and feedbacks challenging, you’re not alone. Here we’ll look at some examples, and we’ll use these systems concepts throughout the rest of the course.
    Learning Goals
    By the end of this section, you will be able to:
    1 Define stock, flow, and feedback.
    2 Explain how the combined history of inflows and outflows determines a stock.
    3 Predict what happens to stocks and flows of energy and materials when a system is perturbed.
    4 Construct examples of both amplifying and stabilizing feedbacks.


    Dr Sara Harris: Welcome to the next lesson of module 2.
    This lesson is about systems dynamics.
    We can think of earth's climate as an interconnected
    system in which the parts exchange matter and energy with one another.
    And something that happens in one part of the system
    can influence another part, which, in turn, might
    influence the first part again.
    By the end of the lesson, you should aim to be
    able to describe what's meant by the word stock, flow, and feedback.
    You should be able to make predictions about what might happen when a stock
    or flow is perturbed in some way.
    And you should be able to construct examples of feedback loops.
    We're going to start with a few warm up questions about a party.
    There's some graph reading involved and some thinking about stock and flow.
    In this case, the stock is the number of people at the party.
    And the flow is the numbers of people coming and going
    from the party in some time period.
    It's a big party, and there are people arriving all the time,
    and there are also people leaving all the time.
    We're going to take a look at what happens at the party over time
    to get some practice with stock and flow.
    So here's a graph.
    This graph represents people coming to and leaving the party
    over the course of half an hour.
    You can see on the horizontal axis that the time period we're looking at
    is 30 minutes long.
    It's some half hour, some time in the middle of the party.
    The vertical axis is the flow of people.
    It's in units of people per minute.
    You'll notice that there are two sets of data plotted here.
    The blue line, with the diamond symbols, represents
    the number of people arriving at the party each minute.
    And the red line, with the circles, represents
    the number of people leaving the party each minute.
    Both the blue line and red line have values
    that vary over our half hour of time.
    Take a look at this graph for a bit.

    There are four questions to answer about this party.
    First, during which minute did the most people arrive at the party?


    Dr Sara Harris: The fourth and last question.
    During which minute were the FEWEST people actually at the party?
    When was the stock of people at the party the smallest?


    Dr Sara Harris: OK, let's have a look at this graph and these data.
    The first two questions were likely the easiest, particularly if you already
    have practice reading graphs.
    You needed to find the highest value of the people arriving curve,
    and then the highest value of the people leaving curve.
    20 people arrived in minute five, that's the peak value of the blue curve that
    shows people arriving.
    And 21 people left during minute 25, that's
    the peak of the red curve that shows people leaving.
    So for those questions you needed to identify the highest values
    on each of those curves.
    You could also find the minutes at which the fewest people arrived,
    which is minute 21, and at which the few people left, that's minute 8.
    The third and fourth questions are harder.
    To answer then we have to imagine how the party changes
    over time, given fluctuations in numbers of people
    leaving and arriving every minute.
    Notice that for the first 13 minutes, the numbers of people arriving
    are always higher than the numbers of people leaving.
    So we're getting more and more crowded at the party
    for each of those 13 minutes.
    The area between those two curves represents the addition
    of people over that time period.
    And then, in minute 14, more people leave than arrive.
    And for the rest of the 30 minutes the party
    thins out with the fewest partiers left at minute 30.
    During each minute, between minute 14 and 30, the numbers of people leaving
    exceeds the number of people arriving.
    Again, the area between the two curves is helpful,
    it represents the net loss of people from minute 14 to minute 30.
    We don't actually know anything about what happened at the party
    before our particular half hour, nor after,
    but notice that the orange shaded region on the right
    is larger than the blue shaded region on the left.
    Comparing these, you can tell that there are fewer people at the party
    at the end of the 30 minutes than there were at the beginning.
    We've had a net loss of people during this half hour.
    The purpose of this party exercise is to practice
    thinking about how the balance or imbalance of flows over time,
    in this case people coming and leaving, changes the stock.
    It's the historical combination of stock and flow
    that determines the state of the system at any particular time.
    Let's talk more about stock.
    A stock is the amount of something, somewhere, at some time.
    The amount of food in your kitchen is a stock.
    The number of bicyclists in a city, that's a stock.
    Prisoners in prison, that's a stock, too.
    A stock can also be something that's harder
    to count, like water in a bucket or water in a cloud
    or helium in a balloon.

    Or it could be something completely intangible, like goodwill or memories
    or influence within an organization, all of which can be gained and lost.
    As we saw with the party, stuff flows in and out of stocks.
    We define a flow as a rate at which stuff adds or subtracts from a stock.
    Since flow is a rate, there's always an element of time included.
    For example, we might have apples picked per hour.
    That's the rate at which apples flow out of the stock of apples on the tree,
    and into the stock of apples in the basket.
    During the melting season in the Arctic we
    can measure sea ice melted per month.
    Other examples are, say, fish born per year,
    or knowledge in your brain gained or lost per decade.

    There are two types of flows, there's inflow and outflow.
    Inflow, as the name implies, is the rate at which stuff flows in.
    And outflow is the rate at which stuff flows out.
    The amount of stuff in any particular stock
    can change over time if the inflows don't match the outflows.
    Let's take a look at a classic analogy for systems dynamics, which
    is a bathtub.
    We'll start with no water in the tub, so the stock is zero.
    There's a plug in the drain, so outflow is also 0.
    Now let's turn on the faucet.
    As you'd expect, if you've ever prepared a bath,
    the water level rises over time.
    And it rises at a rate that's determined by the rate of inflow from the faucet.
    OK, let's turn the water off.
    The drain is still plugged, so the output is still 0.
    And now the inflow is also 0.
    Since the flows are now equal, the water level representing the stock,
    stays constant.
    Now let's open the drain and see what happens.
    Inflow is still 0 because the faucet's off.
    But now outflow is greater than zero, so the water level falls over time.
    But let's turn the faucet back on again, before the tab completely drains.
    If we turn the faucet on so that the rate of water flowing in
    equals the rate of water flowing down the drain,
    then the water level stops dropping and it stabilizes.
    Inflow equals outflow again.
    Only this time the flows are nonzero.
    Let's block the drain a little bit so that inflows exceeds outflow.
    Watch the water level rise.
    Now let's open the drain further so that the tub is draining
    faster than the faucet is adding water.
    Watch the water level fall.
    If you've ever been in the position where
    you had to bail out a leaking boat, you have some experience
    with the balance of inflow and outflow.
    To summarize stock and flow with the bathtub,
    the stock, that's the water level in this case, at any moment
    is the result of the combined history of inflow and outflow.
    At equilibrium, or steady state, inflow equals outflow.
    We can have equilibrium at a wide range of different water levels,
    but if inflow is not equal to outflow, the stock will change.
    Now we'll take the bath tub analogy one step further
    to get us into the world of feedbacks.
    In a bathtub, the rate of water leaving through the drain
    depends partly on the water level itself.
    When the water level is lower, the tub drains more slowly.
    Let's start with the tub about half full, at equilibrium,
    so that inflow equals outflow.
    Now let's crank up the faucet to double the inflow, which
    will create an imbalance and cause the water level to rise.
    But as the water level rises, the pressure on the drain
    increases, so the outflow also increases,
    slowing the water level's rate of rise.
    What ends up happening is that the water level rises to a point
    where the pressure on the drain causes a rate of outflow that
    exactly matches the inflow.
    It's a new, higher water level, but we're back at equilibrium.
    This is an example of a feedback, in which the amount of a stock
    influences a flow in or out of that stock.
    And the flow, in turn, feeds back to influence the stock.
    In this particular case, we're looking at what's
    called a stabilizing or balancing feedback, a feedback that brings
    the system back toward equilibrium.
    So flow depends on stock, depends on flow.
    Feedbacks happen when some perturbation occurs and the system responds.
    It responds either by amplifying the perturbation,
    pushing the system even farther in the direction of the perturbation.

    Or the system responds to counteract the perturbation, stabilizing the system,
    like the response of the drain coupled with the stock of water
    brought the tub to steady state.
    A perturbation could happen to either the stock or the flow.
    The ramifications then feedback between the two.
    In the climate system, you can think of feedbacks as processes
    or a sequence of processes that both responds to temperature changes,
    and in turn, influence temperature.
    So they have to both respond and influence.
    For example, imagine a glacier.
    It's a bunch of white ice.
    At equilibrium, the stock of ice in the glacier stays constant.
    Some is added every year through snowfall
    and some leaves each year through melting or calving of icebergs.
    Imagine a perturbation in temperature that makes earth a little bit cooler.
    With cooler temperatures the glacier might grow a little.
    We know that clean, white ice reflects solar radiation back
    to space pretty well.
    It doesn't absorb a lot of incoming energy.
    So a larger glacier would mean a larger area
    covered with ice, which means more solar radiation reflects directly
    back to space without being absorbed.
    So that will cooler earths temperature a little bit more,
    which helps the ice sheet grow bigger, which helps cool the temperature more.
    This is an example of an amplifying feedback.
    It's a response to a perturbation that pushes the system in the same direction
    as the initial perturbation pushed it.
    To generalize, if something caused global temperature to increase,
    an amplifying feedback would increase global temperature
    further, which would keep the feedback process going.
    You can imagine the ice sheet in reverse as well.
    If temperature goes up, the ice sheet will melt a little more,
    decreasing the area covered by reflective ice, which in turn helps
    earth warm a little bit more.
    This is also an amplifying feedback.
    A party can grow with feedback.
    Maybe a small party attracts attention.
    More people come.
    The party attracts more attention and more people come, et cetera.
    Let's take a look at a stabilizing feedback in the climate system.
    The Earth itself is at some temperature and it emits energy.
    The amount of energy objects emit depends on their temperature.
    Warmer objects emit more energy than cooler objects.
    So if, for some reason, the inflow of energy to earth's
    surface increases, warming earth a little, as a noun warmer object,
    earth would respond by emitting more energy than before,
    increasing the energy outflow to match the new level of inflow.
    By emitting more energy, it helps stabilize its temperature
    and brings the system back toward equilibrium.
    That equilibrium might be at a different temperature than it started with,
    but it would be a stable new temperature until, of course,
    the next perturbation.
    This is similar to the bathtub, which could have many different stable water
    This feedback involving radiation is actually
    the most important stabilizing feedback in Earth's climate system.
    To summarize stabilizing feedbacks, they're
    a response to a perturbation that pushes the system in the opposite direction
    as the initial perturbation pushed it.
    To generalize, if something caused global temperature to increase,
    a stabilizing feedback would respond to counteract the temperature rise, which
    would stabilize the system, though not necessarily
    at the original temperature.
    Imagine that the party gets too crowded so people don't like it and they leave,
    until the party reaches a comfortable size again and people stop leaving.
    That would also be a stabilizing feedback.
    Just as a side note, some of you know amplifying feedbacks
    as positive feedbacks and stabilizing feedbacks as negative feedbacks.
    That's fine if you know that terminology.
    In this course, we'll use amplifying and stabilizing,
    because the words positive and negative feedback have
    everyday meanings that are different from their scientific meanings.
    And there tends to be confusion around those terms.
    In summary, earth's climate system has lots of different stocks,
    lots of different flows among those stocks, and many feedback processes.
    Some feedbacks in the climate system amplify perturbations,
    and some feedbacks stabilize the system after a perturbation.
    We've described two important climate feedbacks, an amplifying one involving
    ice and reflectivity, and a stabilizing one,
    involving earth's temperature and the amount of energy it radiates.
    Keep your eye out for feedbacks in the world around you.
    You'll encounter them everywhere if you look.
    We'll examine more climate related ones later.

    What’s been happening with climate on planet Earth for the past million years or so? This relatively recent geologic time period can give us a sense of the “normal” range and pace of variability in the climate system in the not-so-distant past – a relevant backdrop against which to compare what’s happening today. The past million years have seen warm-cold climate cycles, which are linked to variations in Earth’s orbital configuration. We’ll have a look at some data, explore the dominant theory explaining these climate cycles, and examine a couple of key feedback mechanisms.
    Learning Goals
    By the end of this section, you will be able to:
    1 Describe Earth’s geologic variability over the past million years.
    2 Explain evidence that supports the orbital theory of naturally recurring ice ages.
    3 Formulate a hypothesis describing the best orbital configuration to grow (or melt) a continental ice sheet.
    4 Construct feedback loops that likely amplified climate cycles over the past million years.

    There are three main components of Earth’s orbital configuration that change over time (due to gravitational attractions within the solar system). You’ll learn about each in this tutorial:
    1 Click all the buttons; try all the questions.
    2 Consider the influence of these cycles on seasonal contrast. HIGH seasonal contrast would be a situation in which the Earth (or some part of the Earth) has a relatively high temperature contrast between winter and summer. LOW seasonal contrast would be a situation in which the Earth (or some part of the Earth) has a smaller temperature contrast between winter and summer. As an example that has nothing to do with Earth’s orbital cycles, New York City has higher seasonal contrast (colder winters and hotter summers) than does Mexico City (pretty warm year round).
    3 Write down how each of the three cycles (eccentricity, obliquity, and precession) influences seasonal contrast. Consider both the northern and southern hemisphere separately.


    Dr Sara Harris: Hello, and welcome to this lesson about our geologic backdrop.
    How is today's climate situated within what we know about the past?
    The long-term story is that Earth's climate changes over time.
    There's evidence for very icy conditions in the past.
    For example, you might have heard about Snowball Earth.
    And there's evidence for quite warm conditions
    with no ice on the planet all, like when the dinosaurs were around.
    We're going to focus our attention here mostly on our recent geologic scene,
    the ice age cycles of the past 1 million years
    or so, which lead up to our present situation.

    How does our scenario today fit within the context of the past million years?
    How is the climate changing now in ways that
    are unlike what happened in the past million years?
    Here are some estimates of surface temperature data for the past million
    Time runs from left to right.
    Our climate today, at time zero on the right,
    follows a long series of warm-cold climate cycles.
    These cycles occur with regularity.
    They aren't random or chaotic.
    And these data show that the temperature differences
    between the cold periods and the warm periods is about 5 degrees or so.
    So for example, the most recent ice age, 20,000 years ago,
    that valley in the data closest to the right,
    was about 5 degrees Celsius cooler than Earth is today.
    That doesn't sound like much, but that was
    a time when Canada and parts of northern Europe were covered with ice.
    Sea levels were about 120 meters lower than today.
    And woolly mammoths roamed around.
    Let's try a question.
    During this million years of time, we see that these large climate
    cycles happened.
    About how long does each of these cycles last?


    Dr Sara Harris: There's certainly some variability here,
    but the large amplitude cycles in climate each
    lasts around 100,000 years.

    For example, there are about two of these big cycles
    within the last 200,000 years.
    100,000 years might sound familiar because you've already
    had a look at the three primary ways in which Earth's orbit changes over time
    through the online Milankovitch tutorial.

    And you've learned that these three occur at different periodicities.
    It takes about 100,000 years for the Earth's orbital path
    to change its shape from nearly circular to its maximum eccentricity, which
    is a little bit squashed, back to nearly circular again.
    This cycle can change the total amount of solar energy Earth receives
    each year, though just by a little bit.
    It takes about 41,000 years for the tilt of Earth's axis
    to go from maximum tilt to minimum tilt and back to maximum.
    We're currently at about 23 and 1/2 degrees of tilt away from vertical.
    And the tilt's getting smaller.
    We're on our way to standing more upright.
    And for procession, which is the one that's really hardest to grasp,
    the Earth's axis describes a circle in space,
    completing one circle approximately every 26,000 years.
    This is the one that influences what seasons happen where
    along earth's orbital path, and we'll take a look at those.
    We saw pretty easily the big 100,000-year cycles in the temperature
    We can analyze the data statistically, and we find that the 41,000-year tilt
    cycle is also there, and the periodicities associated with
    First we'll try a couple of questions, just dealing with tilt here.
    Which of these scenarios do you think produces the greatest
    seasonal contrast, that is, the hottest summers coupled with the coldest
    You'll need to imagine the Earth traveling
    around the sun over the course of a year
    Answer is E.


    Dr Sara Harris: So let's start answer A. If Earth
    were standing perfectly upright relative to the plane of its orbit,
    we'd have no seasons.
    The equator would always get the most solar energy.
    And the poles would always get the least.
    Moving on to answer B, with a little bit of tilt,
    we now get some seasonal contrast.
    Tilt a little more, and we get more seasonal contrast.
    Those who chose E were correct.
    The maximum tilt yields the maximum seasonal contrast, really cold winters
    and really hot summers.
    OK, this next question is about precession combined with eccentricity.

    The diagram shows a highly exaggerated eccentric orbit,
    just so we can see it better.
    The Earth passes closest to the Sun on the left side of the diagram
    and passes farthest from the Sun six months later
    on the right side of the diagram.
    Figure out which hemisphere is having which
    seasons at the two points on the annual orbit where the Earth is shown.
    Then compare the seasonal contrast in the Northern versus the Southern
    Hemisphere, based on the seasons you figured out.

    Answer: Southern Because it is closest then later farthest from the sun.
    The southern hemisphere has summer when we're slightly closer to the sun and it has winter when we're slightly farther from the sun, so based only on solar radiation coming in, the southern hemisphere has higher seasonal contrast than the northern hemisphere.


    Dr Sara Harris: So in this diagram, Northern hemisphere winter,
    and Southern hemisphere summer are happening
    at the position on the left, when Earth is closest to the sun.
    You can tell the seasons by the tilt.
    At the position on the right, we have Northern hemisphere summer,
    and Southern hemisphere winter.
    In this case, at the farthest point on the orbit from the sun.
    So the Southern hemisphere has summer when we're slightly closer to the sun,
    and it has winter when we're slightly farther.
    So based just on solar radiation coming in,
    the Southern hemisphere has higher seasonal contrast
    than the Northern hemisphere.
    Do note that the seasons have everything to do with the tilt of Earth's axis,
    not Earth's distance from the sun.
    If that seems to contradict your mental model of the seasons,
    remember that when it's winter in the Northern hemisphere,
    its Summer in the southern hemisphere, right?
    If the Earth-sun distance mattered for seasons,
    we'd all have the same seasons at the same time.
    Which we don't.
    This is the case today.

    In early January-- which is Southern hemisphere summer--
    Earth passes through the point on its orbit that's closest to the sun.
    And in early July, we pass through the point that's farthest from the sun.
    But recall that Earth's North polar axis doesn't always point toward polaris,
    like it does today.
    And half a procession cycle ago, we had the situation
    in which the seasonal contrast between the hemispheres was reversed.
    About 11,000 years ago, the Northern hemisphere
    had slightly warmer summers and cooler winters--
    higher seasonal contrast than the Southern hemisphere.
    Let's think about seasonal contrast and ice sheets.
    During the past million years, ice sheets
    have expanded and contracted primarily on land in the Northern hemisphere.
    If one were trying to grow an ice sheet in the Northern hemisphere,
    would it be best to have high seasonal contrast in the Northern hemisphere?
    That means hotter than average summers and colder than average winters.
    Or would it be best to have low seasonal contrast in the Northern hemisphere?
    Kind of coolish summers and warmish winters.

    Answer: Low seasonal contrast. Low seasonal contrast in the Northern hemisphere, because there would still be snowfall in 'warm-ish' winters but during 'cool-ish' summers, not all the snow would melt away, so some would stick around to be built on the following winter.

    Dr Sara Harris: Some of you may have said high seasonal contrast.
    Perhaps using the logic that colder winters might pile up more snow,
    and increase the extent of winter snow cover.
    But the problem that arises in the opposite season--
    the hotter than usual summers-- which would melt that snow back.
    It turns out that low seasonal contrast in the Northern hemisphere
    is ideal for growing an ice sheet there.
    And the logic is that there would still be snowfall during the warmest winters,
    but during cooler summers not all the snow would melt away.
    Some would stick around to be built on during the following winter.
    If a bit extra snow sticks around, and a bit of extra area on our surface
    is therefore white and reflective, then a little more
    of the incoming solar radiation would reflect away.
    Less would be absorbed, and the earth would cool a little bit,
    promoting additional growth in the size of the ice sheet.
    This is the ice-albedo feedback that we saw earlier.
    It's an amplifying feedback, one that pushes the climate
    system in the same direction as the initial perturbation.
    In this case, the perturbation is toward cooling,
    so the ice-albedo feedback keeps promoting cooling.
    Imagine what happens to this feedback loop
    if the perturbation is toward less area covered with ice and snow.
    It still turns out to be an amplifying feedback,
    just pushing in the opposite direction.
    In fact, feedbacks like the ice-albedo feedback
    are crucial for explaining the amplitude of these climate cycles
    over the past million years.
    Let's look at the actual change in total solar energy
    received by earth on average, over that time period.
    Notice that the periodicity of these cycles is about 100,000 years.
    That makes sense, because eccentricity is
    the only one of the orbital parameters that
    changes the Earth-Sun distance, which can change the total energy we get.
    The second important thing to notice is the range
    of numbers shown on the vertical axis.
    At most, there's a change of a little more than 1/2 a watt per meter
    squared, from the highest maximum shown here to the lowest minimum.
    That's not much.
    Think about the number for earth's climate sensitivity that we introduced,
    which was 3/4 of a degree for every watt per meter squared.
    If Earth's climate over the past million years
    were driven only by these small changes in the total solar energy coming in,
    we'd see a tiny change in temperature.
    Not the five to six degree Celsius changes that are observed.
    What matters more, are the changes in where on Earth
    gets the energy, and in which season.
    So it's the distribution of that incoming solar energy that matters.
    The distribution is controlled by a combination of tilt, procession,
    and eccentricity.
    Small changes in total energy coming in, with much larger changes
    in distribution, combined with feedbacks that magnify those changes,
    ultimately result in the change in climate.
    So let's try thinking about an example, and see
    what kind of orbital configuration might help melt an ice sheet.
    So we established earlier that to grow an ice sheet,
    it'd be good to have a low seasonal contrast.
    Conversely, to melt an ice sheet, it'd be good to have high seasonal contrast.
    That is, quite hot summers, and quite cold winters
    in the Northern hemisphere, where the ice sheets of recently
    grown and receded.
    So let's circle back around to orbital configuration.
    What would be a good orbital configuration
    to melt an ice sheet in the Northern hemisphere?

    Hight tilt angle, closest to the sun. To melt an ice sheet it would be helpful to have hotter than average summers in the Northern Hemisphere. A high tilt angle plus having the Northern Hemisphere summer solstice (June 21st) occur at the point on Earth's orbit closest to the Sun will make Northern Hemisphere summers hotter than average.


    Dr Sara Harris: We're looking for high seasonal contrast in the Northern
    So first, it'd be good to have summer happen
    when Earth passes the sun at its closest point of approach.
    Northern Hemisphere summer's in June.
    So we can eliminate two of the answer choices based on that information.
    Next, you already answered a question about tilt and seasonal contrast.
    The greater the tilt of Earth's axis, the greater the seasonal contrast.
    So high tilt angle, June 21, closest to sun.
    The changes in Earth's orbit can nudge the climate system toward warm or cold.
    And then feedbacks, like the ice-albedo feedback, amplify those nudges.
    Here's another important feedback that operates on this time scale
    and also helps amplify changes in temperature.
    Let's look at temperature, which we've already seen.
    It's the blue line, together with atmospheric carbon dioxide
    measurements from ice cores in Antarctica, that's the red line.
    These carbon dioxide measurements are a good representation
    of global atmospheric carbon dioxide.
    Because the atmosphere mixes quickly, there aren't big differences
    at different locations on these time scales.
    If we look at these global temperature estimates and the atmospheric carbon
    dioxide measurements both going back hundreds of thousands of years,
    the two records are clearly correlated.
    High concentrations of carbon dioxide occur at about the same times
    as warm global temperatures.
    Low concentrations of carbon dioxide occurred at about the same time
    there's cool global temperatures.
    Let's have a look at these two combining together in a feedback.
    Imagine that something happens to make Earth's temperature get
    a little warmer.
    This might be something to do with the orbits changing
    the distribution of incoming solar radiation with latitude.
    In any case, imagine a perturbation slightly in the warmer direction.
    In the oceans there is some dissolved carbon dioxide gas.
    At warmer temperatures the water can keep a less carbon dioxide
    gas dissolved in solution.
    So if the water warms up, some of the carbon dioxide gas
    will come out of the water into the atmosphere.
    You're probably familiar with this effect
    if you've ever opened a warm can of soda.

    Often what happens is that a bunch of gas will bubble out immediately.
    But if you open a cold can of soda there's just a subtle fizzy noise.
    Similarly, if the oceans warm up, some of the carbon dioxide in them
    will outgas gas to the atmosphere.
    More carbon dioxide in atmosphere means that the strength of the greenhouse
    effect goes up, which promotes further warming, which promotes further
    out gassing of carbon dioxide from the oceans, et cetera.
    In this example, the perturbation is towards warming.
    So the carbon dioxide temperature feedback keeps promoting warming.
    You can imagine this feedback loop starting
    with a perturbation that makes global temperatures get a little colder.
    Same processes, just in reverse and still an amplifying feedback.
    So this is our geologic backdrop.
    During the past million years, earth's climate
    has cycled between warm and cold periods with the cold periods
    about five to six degrees Celsius colder than the warm periods.
    These cycles happen regularly at periodicities
    that match the periodicities of the cyclic changes in Earth's orbit
    around the sun.
    Look at the values for atmospherics CO2, the red curve.
    Its axis is on the right.
    Over the past million years, CO2 has cycled up and down
    from highs of about 280 parts per million,
    to lows of about 180 parts per million.
    Today, atmospheric CO2 is close to 400 parts per million and rising.
    Notice that at no time in the past 800,000 years,
    has Earth's atmospheric CO2 concentration
    been anywhere near as high as today.
    The value today is highly unusual.
    And the rate of change is highly unusual compared to our geologic context.
    It's not changes in the total amount of energy earth
    receives that matter so much for these climate cycles of the past million
    years, but rather how the solar energy is distributed over the globe
    and how that translates into seasonal contrast.
    Also crucially important are feedbacks happening here on earth, which amplify
    the subtle pushes given by the orbital changes.
    In particular, the ice albedo feedback amplifies warm and cold extremes
    through the melting or growth of ice sheets.
    And feedbacks between carbon dioxide and temperature
    do the same, amplifying global temperature changes
    in the direction of the initial perturbation.
    In a later lesson, we'll take a look at the most recent climate changes,
    those over the past couple of years and compare them
    to what's been happening in the past million.

    If you’re interested in exploring information about Earth’s climate farther back in time (over 100s of millions of years, through changes in solar output, atmospheric composition, positions of continents…), try starting on this page (though it’s a bit technical):
    Read through “Precambrian climate”, “Phanerozoic climate”, and “Cenozoic climate”. This is completely OPTIONAL.

    5.3 The Climate since the Earth's formation
    Table of Child-Links
    5.3.1 Precambrian climate
    5.3.2 Phanerozoic climate
    5.3.3 Cenozoic climate
    End of Table of Child-Links

    Now that we have had a look at the past million years, we will add on Earth’s climate of the most recent couple of centuries. We will look at a variety of observational measurements of how Earth’s climate has changed in the recent past, and compare these to older climate variations.
    Learning Goals
    By the end of this section, you will be able to:
    1 Describe trajectories of various climate metrics since the Industrial Revolution (e.g. temperature, sea level, ice cover, greenhouse gas concentrations).
    2 Compare today’s climate trajectories and rates of change to the climate context of the past one million years.


    Dr Sara Harris: Welcome to this next lesson about more recent changes in climate.
    We've had a look at the past million years of Earth's climate,
    and now we're going to check out some data from the more recent past,
    the last couple of hundred years.
    We'll look at some of the primary metrics
    of climate change-- like temperature, and sea level, ice
    cover, and greenhouse gas concentrations--
    and how these things have measurably changed over time.
    We're going to look at data, since it's good to get practice
    examining data in any realm of science where you want to learn more.
    So we'll check out some recent data, then
    we'll bring the past million years or so back into the picture again
    for a comparison.
    It's only recently that we've been collecting direct observations
    of climate metrics like temperature.
    The surface thermometer record goes back until about 1880.
    The satellite record goes back only until the 1970s.
    And prior to those times we rely on data from other sources,
    like samples from ice sheets at different times in the past
    or the chemistry of deep ocean sediments.
    But here's the data for global average surface temperatures since 1880.
    You can see that there's variability from year
    to year-- that's normal and expected.
    For example, 1998 was an unusually warm average year
    because there was a large El Nino event.
    And during El Ninos, large parts of the tropical Pacific Ocean
    are warmer than usual, so the global average temperature is also
    warmer than usual.
    But putting aside the year-to-year wiggles, the trend for the past century
    has been toward warmer temperatures.
    Temperatures have increased about 0.6 degrees Celsius in the last 50 years,
    about 1 degree Celsius in the past century.
    Recall that during the last ice age temperatures
    were five to six degrees cooler.
    That last image was global average temperatures-- one point
    per year for the entire globe.
    Here's another way of looking at temperature changes over time.
    This global map shows the rate of surface temperature
    change in degrees Celsius per decade for data from 1979 to 2005.
    With this map we can look in greater detail at different regions.
    For example, where I live-- in Vancouver, Canada-- during this period
    my area got warmer at a rate of about a tenth of a degree Celsius per decade.
    You can find where you live and see the approximate rate there.
    If you're not very familiar with looking at maps like this,
    one thing to look for is where are the extremes-- where's the darkest red--
    and what numbers coincide with the dark red areas?
    Where's the darkest blue and what does that mean?
    Then beyond looking at particular regions, what
    are the larger patterns evident in this map?
    Notice how there are more darker red areas over land.
    Just about everywhere, over land, has been warming during this period.
    Some of the strongest warming is at high northern latitudes.
    In the ocean, less area has been warming and in some places
    the sea surface has cooled.
    In general, with more land, the northern hemisphere
    has warmed more than the southern hemisphere.
    Let's break this down in time a bit more.
    First, let's look at a global map of average surface temperatures
    in the 1970s compared to a base period, which is the average surface
    temperatures from 1951 to 1980.
    This base period is a logical and fairly common one to choose,
    because during that time the measured global surface temperatures didn't
    trend upward or downward very much.
    So first, the 1970s.
    You'll notice that the 1970s are actually part of the base period,
    so one wouldn't expect them to be very different from the base period.
    And they weren't.
    The map shows some places that were little warmer in the 1970s-- those
    are the yellow areas-- and some places that were a little cooler-- those
    are the blues and the greens.
    Moving onward, here are the 1980s.
    This decade is a little warmer than the base period, almost everywhere.
    The 1990s are warmer still, and the 2000s warmer again.
    The 2000s are on average about 0.5 to 0.6 degrees
    warmer than the base period.
    Notice again that the northern high latitudes have warmed more and faster
    than other parts of the world.
    One of the reasons I find this display of the temperature data compelling
    is that I was born in the late 1960s just before the beginning of the data
    shown in these images.
    So these maps essentially represent the changes
    in global temperature over my lifetime.
    Maybe you've seen the equivalent of two of these panels, or three,
    or maybe you've see a few more decades than are shown here.
    And I might-- and you might-- get the opportunity to see a few more.
    What are those feature maps going to look like?
    So surface temperatures on Earth have been warming,
    but they haven't actually been warming as fast as they might if we
    didn't have vast oceans on the planet.
    In a previous lesson we mentioned the heat capacity of water
    in the context of the amount of energy it
    takes to heat the water in a tea kettle.
    Compared to other substances, water has a fairly high heat capacity,
    which means it takes quite a lot of energy to heat it up.
    In recent decades, the inflow of energy to Earth
    has been greater than the outflow.
    Just as in any system, if we have an imbalance
    of flows the stock-- in this case the stock of energy-- will change.
    On Earth where has the extra energy been going?
    Well, a lot of it has been going into the oceans.
    Here's one estimate of that.
    On the horizontal axis we're looking at time starting in the 1960s.
    And on the vertical axis we're looking at the change
    in total heat content since 1961.
    The units on that vertical axis are 10 to the 21st joules.
    So add 21 zeros onto the ends of those numbers there on the axis.
    Over this time period, a small portion of the extra energy
    has gone toward heating land surfaces, the atmosphere, and ice.
    That's what's indicated by the lower shaded part.
    But a much larger amount has gone toward heating the ocean.
    In addition to the helpful feature that water has a high heat capacity,
    the water in the oceans also mixes.
    The water on the surface mixes with the water underneath,
    taking energy downward away from the surface.
    Thus, it's not just the surface that's heating,
    it's also water deeper down, which means it takes more energy
    and longer to raise the temperature of the oceans.
    Measurements show that the warming of the oceans
    extends down to at least 2,000 meters water depth.
    It takes a lot of energy to heat up a two kilometer deep bathtub.
    These data show that the climate system has been accumulating energy,
    as energy inflow has exceeded energy outflow for a while now.
    So the oceans are absorbing energy and heating up.
    But there's another additional response to this heating
    that's really important.
    When water heats up, it expands in volume.
    So imagine the entire ocean heats up and thus the entire ocean
    expands in volume.
    Well where's the extra volume go?
    Since the bottom of the ocean isn't changing very fast,
    the only place for that extra volume to go is upward, raising the water level.
    This expansion of ocean water is responsible for about half
    the global sea level rise.
    And melting ice on land accounts for the other half.
    Now the cool thing about making predictions or forecasting
    future changes is that then time passes and we
    can see how good those forecasts actually turned out to be.
    In this figure, the grey area represents the range of possibilities that seemed
    probable to the Intergovernmental Panel on Climate Change with the information
    they had when they did their assessment report back in 1990.
    And then time passed and people continue to monitor sea level.
    And it turned out that the 1990 estimate from the IPCC was quite conservative.
    The real future sea level has followed the upper edge
    of the projections made back in 1990.
    Sea level is a metric that really matters
    on a practical level for many people, since a whole lot of us
    live very close to sea level.
    Some of us already live below sea level and we have
    barriers to protect our communities.
    That's certainly one of the adaptation options we might choose.
    Another, of course, is to relocate to higher ground.
    But that can present a major challenge in places
    with lots of human infrastructure close to sea level.
    Let's use these data to make an estimate of how fast global sea
    level has risen since 1990.
    How many centimeters of sea level rise happened between about 1990 and 2010?
    You can extrapolate a little bit to 2010.
    Answer: 6 cm. The sea level change in 1990 is about 0 cm (this is relative to a baseline). The sea level change in 2010 (if we continue the trend of the line) is about 6 cm. Therefore the change since 1990 is a sea level rise of about 6 cm.


    Dr Sara Harris: In those two decades, sea level went up
    by a little more than 6 centimeters.

    From those data, the rate of rise turns out
    to have been about 3.1 millimeters per year.
    This is, of course, a global average.
    You might actually live in an area where locally sea
    level is falling because the land surface you live on is rising.
    Or you might live in an area where sea level is rising faster
    than the global average if the land you live on is subsiding at the same time.
    It's worth finding out what's happening where you live.
    As a comparison, during the transition from the last ice
    age to the present warm period, the rate of sea level rise
    was sometimes much higher than our present 3.1
    millimeters per year, up to 10 millimeters per year or higher.
    These higher rates of change in the past were
    associated with times when the major ice sheets had episodes of fast collapse,
    sending lots of ice and water into the oceans.
    Here's an image of one of our major ice sheets today.
    All of the major ice sheets, both on Greenland and on Antarctica,
    have been losing ice mass in recent decades.
    They gain some through snowfall, but they lose more
    through melting, which decreases the total stock of ice.
    The net loss of ice on land contributes, as mentioned previously,
    to sea level rise.
    Sometimes large portions of the major ice sheets
    can undergo melting simultaneously, as happened
    on Greenland in the summer of 2012 when 95% of the surface of the ice sheet
    was melting at once.
    That's the grey area on the image on the right.
    Melting the surface produces puddles of water
    and those puddles are darker than the white ice,
    and therefore absorb more incoming solar radiation, helping the melting along.
    Just as a reference to think about, if all the ice on Greenland were to melt,
    we'd see a rise of about 6 meters of sea level.
    And if all of the ice in Antarctica were to melt, we'd see another 17 meters.
    Nobody's forecasting that kind of catastrophic change happening quickly,
    but it's with imagining what your area would
    look like with even an additional 1 to 2 meters of higher sea level.
    Another type of ice, floating sea ice, doesn't influence sea level rise,
    but it does play a role in the flows of energy in Earth's climate system.
    Sea ice is pretty thin, and it floats on the ocean.
    Every year a lot of it melts in summer and grows back in the winter
    and some sea ice sticks around from year to year,
    though that's becoming less common than it used to be.
    In the summertime when sea ice melts, it exposes the darker ocean water
    underneath, so during the melting season as the sea ice coverage declines
    the ice-albedo feedback helps it melt further and faster because the darker
    ocean, more of which is now exposed, absorbs more incoming solar radiation.
    Annually, the sea ice in the Arctic reaches its minimum extent
    in September, which is at the end of the melting season,
    and reaches its maximum in March, at the end of the dark winter.
    In 2007, many people were taken by surprise
    when the sea ice extent in the Arctic Ocean
    decreased by more than had been anticipated to a record low.
    Compare the area covered with ice in this image for September of 2007
    to the pink line, which is the median ice edge for September for all
    the available years of satellite data.
    2007 had a much smaller ice extent than the median.
    Let's look at sea ice extent on a plot over time.
    Here we have data from 1980 through 2012.
    On the vertical axis, we have Arctic sea ice extent
    in September, which is the month at which sea ice is at its minimum.
    You can see the strong decline that happened
    in 2007, taking September sea ice extent down
    to about 4.3 million square kilometers.
    Then just five years later in 2012 the sea ice extent record was broken again,
    and the September extent went down further
    to just 3.6 million square kilometers.
    Given the observed rates of change, there's
    a decent chance the Arctic will be virtually ice
    free in summer within my lifetime.
    Moving to the atmosphere now.
    Here's the atmospheric carbon dioxide record
    since C. D. Keeling began collecting data at Mauna Loa in Hawaii
    in the late 1950s.
    Back then the value for atmospheric carbon dioxide
    was about 315 parts per million.
    Since then the value has been increasing,
    approaching 400 parts per million at the time this lesson was made.
    Plus the rate of change in the past couple of decades
    is faster than the rate of change was in the first couple of decades.
    The reason atmospheric carbon dioxide is rising
    is because the inflow of CO2 to the atmosphere from fossil fuel
    burning, land use change, and cement making, exceeds the outflow of CO2
    from the atmosphere into the ocean and into land-based biomass and soils.
    In addition to the overall upward trend over time, notice the little wiggles.
    These are seasonal cycles related to plant growth and decay, which
    we'll look at in more detail later.
    And here's some interesting data.
    Since the early 1980s, which is when people
    started making these measurements directly from air samples,
    atmospheric methane concentrations rose, then they plateaued, and then
    they started to rise again.
    Here's a stock and flow question for you.
    During which time period were inflow and outflow
    of methane to and from the atmosphere closest to equal?
    Was it about 1984 to 1990?
    Or 1999 to 2005?
    Or 2008 to 2013?
    Or can we just not tell from looking at these data?

    answer: 1999-2005 If inflow and outflow are approximately equal, the stock isn't going to change much, so the middle time period, 1999 - 2005 is the best of the given choices for inflow to equal outflow.


    Dr Sara Harris: During a time period when inflow and outflow are
    approximately equal, that means the stock isn't going to change much.
    So the middle time period, about 1990 to 2005,
    is the best of the given choices for inflow to equal outflow.
    These measurements then raise some interesting questions.
    What happened?
    What you'd have to do is figure out all the major inflows
    and outflows of methane and see how they changed over time.
    You'd have to look at more data or maybe even make more measurements.
    The key point I want to make here is that,
    in order to understand what's happened, we have to reconcile changes in stock,
    like these, with measurements of changes in inflow and outflow processes.
    Looking a bit farther back in time, it's evident
    that the recent rises in both these greenhouse gases,
    that is carbon dioxide and methane, all happened quite fast
    in quite short periods of time compared to the trends over the last 10,000
    years prior to the Industrial Revolution.
    The Industrial Revolution is the sharp rise
    on the right of both of these graphs.
    And to step back for a longer term view again,
    as we saw in a previous lesson, atmospheric carbon dioxide today
    far exceeds any concentrations from at least the past 800,000 years.
    So those are some data, measurements of stuff related
    to climate change in the recent past.
    These data are incredibly important for monitoring what happens over time.
    If Keeling hadn't started collecting and measuring
    atmospheric carbon dioxide in the late 1950s,
    or if that monitoring program had been dropped later,
    we wouldn't have this type of evidence to examine.
    Satellite data starting in the 1970s greatly expanded our abilities
    to look at the planet and measure global changes.
    These kinds of measurements are crucial to continue
    and to expand if we want to continue learning more about how Earth's climate
    system works.
    And last, there's good evidence to link many of these recent changes
    to human activities, evidence we'll examine
    in more detail in a later lesson

    Watch this short video ("Pockets of cold in a warming world" from NOAA), then try the questions below.
    "Pockets of cold in a warming world"
    1 In your area, what was the temperature anomaly last month? Please do this exercise using degrees Celsius.
    First, see if you can find a specific monthly average temperature (for the last full month before this one, so, if it's "October" today, figure it out for September of this year).
    Second, figure out a baseline average temperature for that month in your area. So that we can compare data among the people in this community, we're going to pick a baseline of the 1980s. So see if you can find the average temperature for that month, for your area, for the 10 years including 1980-1989.
    From those two numbers, figure out the temperature anomaly for your area, last month, compared to the 1980s.
    It might be fairly challenging to find these data, and you might have to do some averaging yourself. This activity might give you a sense of some of the complexities involved if you were to try to figure out, say, global average surface temperature, and the choices you'd have to make.
    2 Complete the Temperature Anomaly Survey (next unit in this module): Just for fun, contribute your temperature anomaly data to a class dataset (not graded). We'll try to extract the data in order to share the results later in the course.

    Average temperature per Pockets of Cold in a Warming World:

    Red areas warmer during winter, December to February blue areas colder than the long term averages. Last winter, the western United States was colder but the East was warmer.

    Intense cold blanketed northeastern Asia. Warmer than average just to the West.
    Even though there were many pockets of cold, the overall global temperature was above average. The area with above average temperature outweighed the area with below average temperature.

    Another interesting pattern is clear in this data set.

    The temperature anomalies over the ocean are much more muted than over land. This is because the ocean warms and cools more slowly than land. Notice how much of the ocean is above average though.

    Moving into spring, this March was below average in the 20th century in the US. But the overall global temperature remained above the average. Understanding why one region differs from others takes an understanding about interaction among the atmosphere, the ocean and even human decisions. Sometimes being climate smart can be as complex as the climate system itself.

    In this module, we’ll follow energy through the climate system. There are essentially three main factors to consider: incoming energy from the Sun, reflection of solar energy, and the greenhouse effect. We’ll have a look at Earth’s energy budget, which includes these big three plus some additional processes, and we’ll have a look at balances and imbalances in energy flows. Understanding solar energy, reflection, and the greenhouse effect are crucial for designing effective mitigation efforts. Where are the possible places to intervene in the system?

    Anything with a temperature above absolute zero (0 kelvin) emits energy. That includes stars, planets, humans, chairs, ice cubes, etc. The amount of energy, and the type of energy, different objects emit is related to the object’s temperature. Here, we’ll examine those relationships, and, in particular, the differences between energy given off by the Sun versus energy given off by the Earth. These differences turn out to be crucial to understanding the greenhouse effect.
    Learning Goals
    By the end of this section, you will be able to:
    1 Compare ultraviolet, visible, and infrared radiation in terms of wavelength, frequency, and energy per photon.
    2 Contrast the amount and type of energy emitted by objects at different temperatures, in particular, the Sun versus Earth.

    Electromagnetic spectrum
    From Wikipedia, the free encyclopedia

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    Gamma rays

    300 EHz
    1 pm
    1.24 MeV

    30 EHz
    10 pm
    124 keV
    Hard X-rays

    3 EHz
    100 pm
    12.4 keV
    Soft X-rays

    300 PHz
    1 nm
    1.24 keV

    30 PHz
    10 nm
    124 eV

    3 PHz
    100 nm
    12.4 eV



    300 THz
    1 μm
    1.24 eV
    Near infrared

    30 THz
    10 μm
    124 meV
    Mid infrared

    3 THz
    100 μm
    12.4 meV
    Far infrared

    300 GHz
    1 mm
    1.24 meV


    Extremely high

    30 GHz
    1 cm
    124 μeV
    Super high

    3 GHz
    1 dm
    12.4 μeV
    Ultra high

    300 MHz
    1 m
    1.24 μeV
    Very high

    30 MHz
    10 m
    124 neV

    3 MHz
    100 m
    12.4 neV

    300 kHz
    1 km
    1.24 neV

    30 kHz
    10 km
    124 peV
    Very low

    3 kHz
    100 km
    12.4 peV

    VF /
    Voice frequency /
    Ultra low frequency

    300 Hz
    1 Mm
    1.24 peV
    Super low

    30 Hz
    10 Mm
    124 feV
    Extremely low

    3 Hz
    100 Mm
    12.4 feV

    Sources: File:Light spectrum.svg [1][2][3]
    The electromagnetic spectrum is the range of all possible frequencies of electromagnetic radiation.[4] The "electromagnetic spectrum" of an object has a different meaning, and is instead the characteristic distribution of electromagnetic radiation emitted or absorbed by that particular object.[citation needed]
    The electromagnetic spectrum extends from below the low frequencies used for modern radio communication to gamma radiation at the short-wavelength (high-frequency) end, thereby covering wavelengths from thousands of kilometers down to a fraction of the size of an atom. The limit for long wavelengths is the size of the universe itself, while it is thought that the short wavelength limit is in the vicinity of the Planck length.[5] Until the middle of last century it was believed by most physicists that this spectrum was infinite and continuous.
    Most parts of the electromagnetic spectrum are used in science for spectroscopic and other probing interactions, as ways to study and characterize matter.[6] In addition, radiation from various parts of the spectrum has found many other uses for communications and manufacturing (see electromagnetic radiation for more applications).

    Contents  [hide]
    1 History of electromagnetic spectrum discovery
    2 Range of the spectrum
    3 Rationale for spectrum regional names
    4 Types of radiation
    4.1 Boundaries
    4.2 Regions of the spectrum
    4.3 Radio frequency
    4.4 Microwaves
    4.5 Terahertz radiation
    4.6 Infrared radiation
    4.7 Visible radiation (light)
    4.8 Ultraviolet radiation
    4.9 X-rays
    4.10 Gamma rays
    5 See also
    6 Notes and references
    7 External links

    History of electromagnetic spectrum discovery[edit]
    See also: History of electromagnetism, History of radio, History of electrical engineering and History of optics
    For most of history, visible light was the only known part of the electromagnetic spectrum. The ancient Greeks recognized that light traveled in straight lines and studied some of its properties, including reflection and refraction. The study of light continued, and during the 16th and 17th centuries conflicting theories regarded light as either a wave or a particle.[citation needed]
    The first discovery of electromagnetic radiation other than visible light came in 1800, when William Herschel discovered infrared radiation.[7] He was studying the temperature of different colors by moving a thermometer through light split by a prism. He noticed that the highest temperature was beyond red. He theorized that this temperature change was due to "calorific rays" that were a type of light ray that could not be seen.
    The next year, Johann Ritter, working at the other end of the spectrum, noticed what he called "chemical rays" (invisible light rays that induced certain chemical reactions). These behaved similarly to visible violet light rays, but were beyond them in the spectrum.[8] They were later renamed ultraviolet radiation.
    Electromagnetic radiation had been first linked to electromagnetism in 1845, when Michael Faraday noticed that the polarization of light traveling through a transparent material responded to a magnetic field (see Faraday effect). During the 1860s James Maxwell developed four partial differential equations for the electromagnetic field. Two of these equations predicted the possibility of, and behavior of, waves in the field. Analyzing the speed of these theoretical waves, Maxwell realized that they must travel at a speed that was about the known speed of light. This startling coincidence in value led Maxwell to make the inference that light itself is a type of electromagnetic wave.
    Maxwell's equations predicted an infinite number of frequencies of electromagnetic waves, all traveling at the speed of light. This was the first indication of the existence of the entire electromagnetic spectrum.
    Maxwell's predicted waves included waves at very low frequencies compared to infrared, which in theory might be created by oscillating charges in an ordinary electrical circuit of a certain type. Attempting to prove Maxwell's equations and detect such low frequency electromagnetic radiation, in 1886 the physicist Heinrich Hertz built an apparatus to generate and detect what is now called radio waves. Hertz found the waves and was able to infer (by measuring their wavelength and multiplying it by their frequency) that they traveled at the speed of light. Hertz also demonstrated that the new radiation could be both reflected and refracted by various dielectric media, in the same manner as light. For example, Hertz was able to focus the waves using a lens made of tree resin. In a later experiment, Hertz similarly produced and measured the properties of microwaves. These new types of waves paved the way for inventions such as the wireless telegraph and the radio.
    In 1895 Wilhelm Röntgen noticed a new type of radiation emitted during an experiment with an evacuated tube subjected to a high voltage. He called these radiations x-rays and found that they were able to travel through parts of the human body but were reflected or stopped by denser matter such as bones. Before long, many uses were found for them in the field of medicine.
    The last portion of the electromagnetic spectrum was filled in with the discovery of gamma rays. In 1900 Paul Villard was studying the radioactive emissions of radium when he identified a new type of radiation that he first thought consisted of particles similar to known alpha and beta particles, but with the power of being far more penetrating than either. However, in 1910, British physicist William Henry Bragg demonstrated that gamma rays are electromagnetic radiation, not particles, and in 1914, Ernest Rutherford (who had named them gamma rays in 1903 when he realized that they were fundamentally different from charged alpha and beta particles) and Edward Andrade measured their wavelengths, and found that gamma rays were similar to X-rays, but with shorter wavelengths and higher frequencies.
    Range of the spectrum[edit]
    Electromagnetic waves are typically described by any of the following three physical properties: the frequency f, wavelength λ, or photon energy E. Frequencies observed in astronomy range from 2.4×1023 Hz (1 GeV gamma rays) down to the local plasma frequency of the ionized interstellar medium (~1 kHz). Wavelength is inversely proportional to the wave frequency,[6] so gamma rays have very short wavelengths that are fractions of the size of atoms, whereas wavelengths on the opposite end of the spectrum can be as long as the universe. Photon energy is directly proportional to the wave frequency, so gamma ray photons have the highest energy (around a billion electron volts), while radio wave photons have very low energy (around a femtoelectronvolt). These relations are illustrated by the following equations:

    c = 299792458 m/s is the speed of light in a vacuum
    h = 6.62606896(33)×10−34 J·s = 4.13566733(10)×10−15 eV·s is Planck's constant.[9]
    Whenever electromagnetic waves exist in a medium with matter, their wavelength is decreased. Wavelengths of electromagnetic radiation, no matter what medium they are traveling through, are usually quoted in terms of the vacuum wavelength, although this is not always explicitly stated.
    Generally, electromagnetic radiation is classified by wavelength into radio wave, microwave, terahertz (or sub-millimeter) radiation, infrared, the visible region is perceived as light, ultraviolet, X-rays and gamma rays. The behavior of EM radiation depends on its wavelength. When EM radiation interacts with single atoms and molecules, its behavior also depends on the amount of energy per quantum (photon) it carries.
    Spectroscopy can detect a much wider region of the EM spectrum than the visible range of 400 nm to 700 nm. A common laboratory spectroscope can detect wavelengths from 2 nm to 2500 nm. Detailed information about the physical properties of objects, gases, or even stars can be obtained from this type of device. Spectroscopes are widely used in astrophysics. For example, many hydrogen atoms emit a radio wave photon that has a wavelength of 21.12 cm. Also, frequencies of 30 Hz and below can be produced by and are important in the study of certain stellar nebulae[10] and frequencies as high as 2.9×1027 Hz have been detected from astrophysical sources.[11]
    Rationale for spectrum regional names[edit]
    Electromagnetic radiation interacts with matter in different ways across the spectrum. These types of interaction are so different that historically different names have been applied to different parts of the spectrum, as though these were different types of radiation. Thus, although these "different kinds" of electromagnetic radiation form a quantitatively continuous spectrum of frequencies and wavelengths, the spectrum remains divided for practical reasons related to these qualitative interaction differences.
    Electromagnetic radiation interaction with matter
    Region of the spectrum
    Main interactions with matter
    Collective oscillation of charge carriers in bulk material (plasma oscillation). An example would be the oscillatory travels of the electrons in an antenna.
    Microwave through far infrared
    Plasma oscillation, molecular rotation
    Near infrared
    Molecular vibration, plasma oscillation (in metals only)
    Molecular electron excitation (including pigment molecules found in the human retina), plasma oscillations (in metals only)
    Excitation of molecular and atomic valence electrons, including ejection of the electrons (photoelectric effect)
    Excitation and ejection of core atomic electrons, Compton scattering (for low atomic numbers)
    Gamma rays
    Energetic ejection of core electrons in heavy elements, Compton scattering (for all atomic numbers), excitation of atomic nuclei, including dissociation of nuclei
    High-energy gamma rays
    Creation of particle-antiparticle pairs. At very high energies a single photon can create a shower of high-energy particles and antiparticles upon interaction with matter.
    Types of radiation[edit]

    The electromagnetic spectrum

    A diagram of the electromagnetic spectrum, showing various properties across the range of frequencies and wavelengths
    A discussion of the regions (or bands or types) of the electromagnetic spectrum is given below. Note that there are no precisely defined boundaries between the bands of the electromagnetic spectrum; rather they fade into each other like the bands in a rainbow (which is the sub-spectrum of visible light). Radiation of each frequency and wavelength (or in each band) has a mix of properties of the two regions of the spectrum that bound it. For example, red light resembles infrared radiation in that it can excite and add energy to some chemical bonds and indeed must do so to power the chemical mechanisms responsible for photosynthesis and the working of the visual system.
    Regions of the spectrum[edit]
    The types of electromagnetic radiation are broadly classified into the following classes:[6]
    1 Gamma radiation
    2 X-ray radiation
    3 Ultraviolet radiation
    4 Visible radiation
    5 Infrared radiation
    6 Terahertz radiation
    7 Microwave radiation
    8 Radio waves
    This classification goes in the increasing order of wavelength, which is characteristic of the type of radiation.[6] While, in general, the classification scheme is accurate, in reality there is often some overlap between neighboring types of electromagnetic energy. For example, SLF radio waves at 60 Hz may be received and studied by astronomers, or may be ducted along wires as electric power, although the latter is, in the strict sense, not electromagnetic radiation at all (see near and far field).
    The distinction between X-rays and gamma rays is partly based on sources: the photons generated from nuclear decay or other nuclear and subnuclear/particle process, are always termed gamma rays, whereas X-rays are generated by electronic transitions involving highly energetic inner atomic electrons.[12][13][14] In general, nuclear transitions are much more energetic than electronic transitions, so gamma-rays are more energetic than X-rays, but exceptions exist. By analogy to electronic transitions, muonic atom transitions are also said to produce X-rays, even though their energy may exceed 6 megaelectronvolts (0.96 pJ),[15] whereas there are many (77 known to be less than 10 keV (1.6 fJ)) low-energy nuclear transitions (e.g., the 7.6 eV (1.22 aJ) nuclear transition of thorium-229), and, despite being one million-fold less energetic than some muonic X-rays, the emitted photons are still called gamma rays due to their nuclear origin.[16]
    The convention that EM radiation that is known to come from the nucleus, is always called "gamma ray" radiation is the only convention that is universally respected, however. Many astronomical gamma ray sources (such as gamma ray bursts) are known to be too energetic (in both intensity and wavelength) to be of nuclear origin. Quite often, in high energy physics and in medical radiotherapy, very high energy EMR (in the >10 MeV region)—which is of higher energy than any nuclear gamma ray—is not called X-ray or gamma-ray, but instead by the generic term of "high energy photons."
    The region of the spectrum where a particular observed electromagnetic radiation falls, is reference frame-dependent (due to the Doppler shift for light), so EM radiation that one observer would say is in one region of the spectrum could appear to an observer moving at a substantial fraction of the speed of light with respect to the first to be in another part of the spectrum. For example, consider the cosmic microwave background. It was produced, when matter and radiation decoupled, by the de-excitation of hydrogen atoms to the ground state. These photons were from Lyman series transitions, putting them in the ultraviolet (UV) part of the electromagnetic spectrum. Now this radiation has undergone enough cosmological red shift to put it into the microwave region of the spectrum for observers moving slowly (compared to the speed of light) with respect to the cosmos.
    Radio frequency[edit]
    Main articles: Radio frequency, Radio spectrum and Radio waves
    Radio waves generally are utilized by antennas of appropriate size (according to the principle of resonance), with wavelengths ranging from hundreds of meters to about one millimeter. They are used for transmission of data, via modulation. Television, mobile phones, wireless networking, and amateur radio all use radio waves. The use of the radio spectrum is regulated by many governments through frequency allocation.
    Radio waves can be made to carry information by varying a combination of the amplitude, frequency, and phase of the wave within a frequency band. When EM radiation impinges upon a conductor, it couples to the conductor, travels along it, and induces an electric current on the surface of that conductor by exciting the electrons of the conducting material. This effect (the skin effect) is used in antennas.
    Main article: Microwaves

    Plot of Earth's atmospheric transmittance (or opacity) to various wavelengths of electromagnetic radiation.
    The super-high frequency (SHF) and extremely high frequency (EHF) of microwaves are on the short side of radio waves. Microwaves are waves that are typically short enough (measured in millimeters) to employ tubular metal waveguides of reasonable diameter. Microwave energy is produced with klystron and magnetron tubes, and with solid state diodes such as Gunn and IMPATT devices. Microwaves are absorbed by molecules that have a dipole moment in liquids. In a microwave oven, this effect is used to heat food. Low-intensity microwave radiation is used in Wi-Fi, although this is at intensity levels unable to cause thermal heating.
    Volumetric heating, as used by microwave ovens, transfers energy through the material electromagnetically, not as a thermal heat flux. The benefit of this is a more uniform heating and reduced heating time; microwaves can heat material in less than 1% of the time of conventional heating methods.
    When active, the average microwave oven is powerful enough to cause interference at close range with poorly shielded electromagnetic fields such as those found in mobile medical devices and poorly made consumer electronics.[citation needed]
    Terahertz radiation[edit]
    Main article: Terahertz radiation
    Terahertz radiation is a region of the spectrum between far infrared and microwaves. Until recently, the range was rarely studied and few sources existed for microwave energy at the high end of the band (sub-millimeter waves or so-called terahertz waves), but applications such as imaging and communications are now appearing. Scientists are also looking to apply terahertz technology in the armed forces, where high-frequency waves might be directed at enemy troops to incapacitate their electronic equipment.[17]
    Infrared radiation[edit]
    Main article: Infrared radiation
    The infrared part of the electromagnetic spectrum covers the range from roughly 300 GHz to 400 THz (1 mm - 750 nm). It can be divided into three parts:[6]
    Far-infrared, from 300 GHz to 30 THz (1 mm - 10 μm). The lower part of this range may also be called microwaves or terahertz waves. This radiation is typically absorbed by so-called rotational modes in gas-phase molecules, by molecular motions in liquids, and by phonons in solids. The water in Earth's atmosphere absorbs so strongly in this range that it renders the atmosphere in effect opaque. However, there are certain wavelength ranges ("windows") within the opaque range that allow partial transmission, and can be used for astronomy. The wavelength range from approximately 200 μm up to a few mm is often referred to as "sub-millimeter" in astronomy, reserving far infrared for wavelengths below 200 μm.
    Mid-infrared, from 30 to 120 THz (10 - 2.5 μm). Hot objects (black-body radiators) can radiate strongly in this range, and human skin at normal body temperature radiates strongly at the lower end of this region. This radiation is absorbed by molecular vibrations, where the different atoms in a molecule vibrate around their equilibrium positions. This range is sometimes called the fingerprint region, since the mid-infrared absorption spectrum of a compound is very specific for that compound.
    Near-infrared, from 120 to 400 THz (2,500 - 750 nm). Physical processes that are relevant for this range are similar to those for visible light. The highest frequences in this region can be detected directly by some types of photographic film, and by many types of solid state image sensors for infrared photography and videography.
    Visible radiation (light)[edit]
    Main article: Visible spectrum
    Above infrared in frequency comes visible light. The Sun emits its peak power in the visible region, although integrating the entire emission power spectrum through all wavelengths shows that the Sun emits slightly more infrared than visible light.[18] By definition, visible light is the part of the EM spectrum the human eye is the most sensitive to. Visible light (and near-infrared light) is typically absorbed and emitted by electrons in molecules and atoms that move from one energy level to another. This action allows the chemical mechanisms that underlie human vision and plant photosynthesis. The light that excites the human visual system is a very small portion of the electromagnetic spectrum. A rainbow shows the optical (visible) part of the electromagnetic spectrum; infrared (if it could be seen) would be located just beyond the red side of the rainbow with ultraviolet appearing just beyond the violet end.
    Electromagnetic radiation with a wavelength between 380 nm and 760 nm (400–790 terahertz) is detected by the human eye and perceived as visible light. Other wavelengths, especially near infrared (longer than 760 nm) and ultraviolet (shorter than 380 nm) are also sometimes referred to as light, especially when the visibility to humans is not relevant. White light is a combination of lights of different wavelengths in the visible spectrum. Passing white light through a prism splits it up into the several colors of light observed in the visible spectrum between 400 nm and 780 nm.
    If radiation having a frequency in the visible region of the EM spectrum reflects off an object, say, a bowl of fruit, and then strikes the eyes, this results in visual perception of the scene. The brain's visual system processes the multitude of reflected frequencies into different shades and hues, and through this insufficiently-understood psychophysical phenomenon, most people perceive a bowl of fruit.
    At most wavelengths, however, the information carried by electromagnetic radiation is not directly detected by human senses. Natural sources produce EM radiation across the spectrum, and technology can also manipulate a broad range of wavelengths. Optical fiber transmits light that, although not necessarily in the visible part of the spectrum (it is usually infrared), can carry information. The modulation is similar to that used with radio waves.
    Ultraviolet radiation[edit]
    Main article: Ultraviolet

    The amount of penetration of UV relative to altitude in Earth's ozone
    Next in frequency comes ultraviolet (UV). The wavelength of UV rays is shorter than the violet end of the visible spectrum but longer than the X-ray.
    UV in the very shortest wavelength range (next to X-rays) is capable of ionizing atoms (see photoelectric effect), greatly changing their physical behavior.
    At the middle range of UV, UV rays cannot ionize but can break chemical bonds, making molecules unusually reactive. Sunburn, for example, is caused by the disruptive effects of middle range UV radiation on skin cells, which is the main cause of skin cancer. UV rays in the middle range can irreparably damage the complex DNA molecules in the cells producing thymine dimers making it a very potent mutagen.
    The Sun emits significant UV radiation (about 10% of its total power), including extremely short wavelength UV that could potentially destroy most life on land (ocean water would provide some protection for life there). However, most of the Sun's damaging UV wavelengths are absorbed by the atmosphere and ozone layer before they reach the surface. The higher energy (shortest wavelength) ranges of UV (called "vacuum UV") are absorbed by nitrogen and, at longer wavelengths, by simple diatomic oxygen in the air. Most of the UV in the mid-range of energy is blocked by the ozone layer, which absorbs strongly in the important 200–315 nm range, the lower energy part of which is too long for ordinary dioxygen in air to absorb. The very lowest energy range of UV between 315 nm and visible light (called UV-A) is not blocked well by the atmosphere, but does not cause sunburn and does less biological damage. However, it is not harmless and does create oxygen radicals, mutations and skin damage. See ultraviolet for more information.
    Main article: X-rays
    After UV come X-rays, which, like the upper ranges of UV are also ionizing. However, due to their higher energies, X-rays can also interact with matter by means of the Compton effect. Hard X-rays have shorter wavelengths than soft X-rays and as they can pass through many substances with little absorption, they can be used to 'see through' objects with 'thicknesses' less than that equivalent to a few meters of water. One notable use is diagnostic X-ray imaging in medicine (a process known as radiography). X-rays are useful as probes in high-energy physics. In astronomy, the accretion disks around neutron stars and black holes emit X-rays, enabling studies of these phenomena. X-rays are also emitted by the coronas of stars and are strongly emitted by some types of nebulae. However, X-ray telescopes must be placed outside the Earth's atmosphere to see astronomical X-rays, since the great depth of the atmosphere of Earth is opaque to X-rays (with areal density of 1000 grams per cm2), equivalent to 10 meters thickness of water. [19] This is an amount sufficient to block almost all astronomical X-rays (and also astronomical gamma rays—see below).
    Gamma rays[edit]
    Main article: Gamma rays
    After hard X-rays come gamma rays, which were discovered by Paul Villard in 1900. These are the most energetic photons, having no defined lower limit to their wavelength. In astronomy they are valuable for studying high-energy objects or regions, however as with X-rays this can only be done with telescopes outside the Earth's atmosphere. Gamma rays are used experimentally by physicists for their penetrating ability and are produced by a number of radioisotopes. They are used for irradiation of foods and seeds for sterilization, and in medicine they are occasionally used in radiation cancer therapy.[20] More commonly, gamma rays are used for diagnostic imaging in nuclear medicine, an example being PET scans. The wavelength of gamma rays can be measured with high accuracy through the effects of Compton scattering.

    Dr Sara Harris: Welcome to this next lesson.
    We're going to take a look at the energy coming from the sun,
    and the energy from Earth, too, because these things
    are both important to how energy flows in Earth's climate
    system, and in particular, are important for understanding the greenhouse
    Just about everything radiates energy-- the walls of your room,
    your furniture, the plants in the park, your food, everything around you.
    The Sun gives off energy, and some of that energy
    travels through space to Earth.
    The Earth gives off energy that eventually travels back to space, too.
    But what types of energy, and how much energy do the Sun and the Earth
    give off?
    In this lesson, we're going to learn and apply two physical principles,
    both having to do with the energy radiated by different things.
    The Sun is, of course, different from the Earth, which
    is different from a glacier, which is different for you or me
    or your furniture, and we're all different in terms
    of the amount and type of radiation each thing gives off.
    The two physical relationships that matter for us here are first,
    a relationship between an object's temperature and the wavelengths
    of energy the object emits, and second, a relationship
    between an object's temperature and the total amount of energy the object
    We're going to start with the Sun.

    The Sun is the source of energy for Earth's climate system,
    and it gives off a measurable amount of energy
    with a measurable range of wavelengths, both of which
    are dependent on its temperature.
    We're going to go at this a little bit backwards
    and think about how we might take the Sun's temperature.
    We can't just go stick a thermometer in it
    like we could to take our own temperature.
    But what we can do is measure characteristics
    of the electromagnetic radiation coming from the Sun,
    and then use physical laws to figure out the Sun's temperature.
    Here's a quick review of the electromagnetic spectrum.
    Electromagnetic energy comes in different flavors,

    with different wavelengths, frequencies, and photon energies.
    For our purposes, we're primarily interested in wavelengths
    in the visible range, the infrared, and a little bit of ultraviolet.
    Of these, ultraviolet has the shortest wavelengths, highest frequencies,
    and highest photon energies.
    You already explored that in our reading.
    To get warmed up, let's try a couple of questions.
    Which of these stoves is the hottest?


    Dr Sara Harris: If you said C, you probably have some experience
    with electric stoves like mine.
    And you know it's probably not a good idea
    to put your hand down on a red burner, because it's hot
    and it's giving off a lot of energy and you might get burned.
    A black burner is definitely cooler than a red burner.
    So there seems to be some relationship between a stove
    color and the temperature and the amount of energy the stove gives off.
    Try this question next.
    This one's a little harder.
    Which of these stoves do you think is emitting radiation
    with the longest peak wavelength?
    Think about what part of the electromagnetic spectrum
    would correspond to the emissions of these three stoves.


    Dr Sara Harris: Stove C, we can tell, is red.
    It's emitting some radiation in the visible range,
    which human eyes can see.
    Stove B, however, is black here in this picture,
    which was taken at room temperature.
    That stove is emitting radiation at wavelengths that we can't see.
    These wavelengths are in the infrared part
    of the spectrum, which are longer wavelengths than visible light.
    Infrared is the same range of radiation that you and I also emit.
    We're not actually hot enough to emit visible light.
    If we were able to crank up the temperature on these stoves further,
    the elements would get brighter and might start emitting light
    in the yellow part of the visible spectrum,
    at shorter wavelengths than the red.
    So let's apply that idea to some stars.
    Which of these stars is the hottest

    Skip to a navigable version of this video's transcript.

    Dr Sara Harris: Star A looks like it's mostly emitting red light.
    Star B looks like it's mostly emitting blue light.
    And star C looks like it's mostly emitting yellow light.
    Thinking about the electromagnetic spectrum,
    red is at the long wavelength end of the visible range, yellow is in the middle,
    and blue is at the short wavelength end.
    So just like the stoves, the star that emits the shortest wavelengths
    is the hottest.
    And in this example, that's star B.
    Here's the electromagnetic spectrum again,
    which can help us see that the blue star emits
    shorter wavelengths than the red star.
    So this is pretty cool.
    And we can use it.
    There's even an equation for it.
    A fairly long time ago, some physicists, notably a person named Wilhelm Wien,
    figured out the relationship between an object's temperature
    and the peak wavelength of radiation that it emits.
    In the equation here, the T stands for temperature.
    And that's on the Kelvin temperature scale.
    The lambda, with the little m next to it,
    stands for the peak wavelength emitted, in units of micrometers.
    And then the w is a constant that Wien figured out
    by doing a lot of observations.
    You might not like equations very much.
    And we won't have very many of them.
    But this is one that's important.
    The key thing to note here is that if temperature goes up,
    the wavelengths of maximum emission goes down.
    Hotter objects emit radiation at shorter wavelengths,
    just like those stoves and those stars.
    Getting back to our question about the Sun's temperature,
    this equation let's us figure it out.
    We can save ourselves a trip to the Sun by measuring
    the peak wavelength of the radiation coming off the Sun,
    then using Wien's law to calculate the Sun's temperature.
    So we do it.

    We measure the spectrum of electromagnetic radiation
    emitted by the Sun.
    And we find out that the Sun's wavelength of maximum emission
    is in the visible range.
    Not surprising, you probably knew that.
    And more specifically, the peak is at about half a micron wavelength.
    That's the peak or wavelength of maximum emission in Wien's law.
    Of course, the Sun also emits radiation all across the visible part
    of the spectrum and also emits ultraviolet and infrared radiation.
    But those are on the sloping sides of its emission spectrum.
    OK, with a peak wavelength of half a micrometer, we can now use Wien's law
    and figure out the Sun's temperature.
    After a little algebra, we find out that the Sun's temperature
    is close to 5,800 Kelvin, which is pretty hot.
    So what about Earth?

    You can see here that the spectrum of radiation Earth gives off
    is out in the infrared at longer wavelengths, which
    is expected since we know that the Earth is cooler than the Sun.
    So let's try a question about that.
    At the top of Earth's atmosphere, the planet
    emits infrared radiation at a peak wavelength of about 11.4 micrometers.
    What temperature does that corresponds to?


    Dr Sara Harris: From Wien's Law, we find out
    that the temperature at the top of Earth's atmosphere,
    where energy is radiating to space, is about 255 Kelvin, or choice C here,
    which is about the same as minus 18 degrees Celsius, or about 0 degrees
    It's pretty cold up there.
    So we've determined that the Sun and Earth give off
    different types of energy, which is going to become important when
    we talk about the greenhouse effect.
    But also, as you can probably imagine, every square meter of the Sun's surface
    emits tremendously more energy every second
    than every square meter of Earth emits.
    This is the other important law, relating temperature and energy.
    This one was figured out by two people Stefan and Boltzmann,
    so it's the Stefan-Boltzmann Law.
    This relationship says that as temperature increases,
    the amount of energy given off by an object per second, per area,
    goes up exponentially, to the fourth power.
    So for example, if you double the temperature, the energy given off
    per second, per square meter doesn't just double, it goes up by 16 times.
    So it goes up a lot.
    Recall that the energy per photon is higher
    for shorter wavelength, higher frequency radiation, like ultraviolet radiation.
    Thinking about Wien's Law, as something gets hotter,
    it emits shorter wavelength radiation, which has higher energy per photon.
    The Stefan-Boltzmann Law takes into account
    that increased energy per photon at shorter wavelengths.
    If we actually do the math-- and I'd encourage you to try the math--
    we come up with the answer that each square meter of the Sun's surface
    gives off about 64 million Joules, every second.
    In contrast, the Earth's upper atmosphere gives of only about 240
    Watts per meter squared.
    Just imagine those boxes drawn on the Sun and the Earth
    as only one meter square.
    All right, so key points from this lesson.
    The Sun is hot.
    Because it's hot, it gives off lots of energy per second, per square meter--
    much, much more than Earth gives off.
    Also, because it's hot, the Sun gives off radiation at visible wavelengths.
    And Earth, because it's cooler, gives off radiation at infrared wavelengths.
    The primary reason to spend time on these relationships
    is so we can use them, when we have a look at the different types of energy
    transferring around within Earth's climate system, which
    is coming up in later lessons.
    To close this lesson, wherever you are, take a look around you.
    Pick up four objects, and rank them by their wavelength of maximum emission,
    and the energy they gave off, in Watts per meter squared.

    Explore this interactive simulation from the PhET group at the University of Colorado:
    1 Explore all the features of this simulation.
    2 Using this simulation, see whether you think the relationships described by Wein's Law and the Stefan-Boltzmann Law hold.

    Here we’ll examine the main processes by which energy flows in, out, and within Earth’s climate system. We’ll spend some time with an iconic figure showing Earth’s annual energy budget, and examine it from a stock and flow perspective. This section ends with readings about natural variability in the Sun’s energy output, which changes on timescales of billions of years to decades.
    Learning Goals
    By the end of this section, you will be able to:
    1 Describe how incoming and outgoing electromagnetic radiation interacts with Earth’s surface and its atmosphere.
    2 Balance energy budgets for the top of the atmosphere, the atmosphere, and Earth’s surface.
    3 Predict how changes in incoming solar energy, greenhouse gases, and albedo will affect a planet’s mean surface temperature.


    Dr Sara Harris: Hello, and welcome to our introduction to Earth's energy budget,
    and the various pathways by which energy gets transferred around in the system.
    Here's what we're aiming for in this lesson.
    There are a bunch of processes involved with energy in Earth's climate system.
    Some of them are super important.
    Some are slightly less important.

    But what is important is that you are able to describe some of the processes
    by which energy interacts with parts of Earth's climate system,
    and get some practice checking for balance in energy inflows and outflows.
    Fundamentally, any mitigation actions we choose
    to take have to align with the energy flows
    we're talking about in this lesson.
    Where are the places we can actually do something to alter energy flows?
    Keep your eyes peeled for those opportunities throughout the course.
    We're going to spend this entire lesson focused on this one figure, which
    shows Earth's annual average energy budget-- the energy coming in
    from space and leaving to space, the energy interacting with Earth's surface
    and the energy that interacts with Earth's atmosphere.
    There are a bunch of iterations of this figure.
    We're going to use this one.
    It's based on the IPCC 2007 report updated with numbers from Trenberth
    and others from 2009.
    Scientists continue to update specific numbers,
    but the important pathways are shown well here.
    All the numbers listed on this figure are
    in units of watts per meter squared, with which you're already familiar.
    We'll start working our way through this figure at the top, where
    solar radiation comes in.
    As we saw before, every square meter on the surface of the Sun
    emits 64 million watts because the sun is hot.
    That energy gets spread out over a bigger and bigger sphere
    as it travels away from the Sun, kind of like how
    the color of a brightly colored balloon fades as you blow it up bigger.
    By the time the Sun's energy has traveled to the Earth
    and then has been averaged out over our spinning spherical surface,
    we're down to about 341.3 watts per meter
    squared on average for each square meter at the top of Earth's atmosphere.
    Remember that the type of radiation coming in from the Sun
    is centered at visible wavelengths, with some energy also
    in the ultraviolet and the infrared.
    Things happen to this shortwave energy when it encounters Earth's atmosphere.
    Some of it, about 79 watts per meter squared,
    gets reflected directly back to space, mostly by white things and shiny things
    in the atmosphere.
    White fluffy clouds are responsible for a lot of this reflection,
    but there are also tiny particles and droplets
    in the atmosphere that act like little mirrors
    and reflect away some of the incoming radiation from the Sun.
    The atmosphere also absorbs some of the incoming solar radiation.
    Ozone in the stratosphere absorbs much of the ultraviolet on its way in,
    and water vapor is capable of absorbing some particular wavelengths
    of infrared radiation that overlap with the range of wavelengths coming in
    from the Sun.
    Dark particles in the atmosphere like soot can also absorb radiation.
    The atmosphere is mostly transparent to visible light,
    so a lot of the solar radiation passes through Earth's atmosphere
    and reaches Earth's surface.
    These are wavelengths that are mostly in the visible range,
    and some in the infrared.
    You can see two numbers that involve solar radiation
    reaching Earth's surface.
    On the left, we have 23 watts per meter squared
    reflecting directly back to space-- the surfaces that
    are good at reflecting this radiation are things like ice and light colored
    deserts-- and 161 watts per meter squared
    are absorbed by Earth's surface.
    Notice that if we add together the solar energy directly reflected
    by the atmosphere and the solar energy directly reflected by Earth's surface,
    the two together add up to about 102 watts per meter squared.
    So about 30% of the incoming solar radiation
    is reflecting right back to outer space and not really getting
    involved for very long.
    The other 70% is getting absorbed, either by the atmosphere
    or by Earth's surface, for a total of about 239 watts per meter squared.
    Thinking from a systems perspective, what
    would happen if Earth's climate system continuously
    absorbed 239 watts per meter squared?
    The planet's temperature would go up pretty quickly.
    Now, that doesn't happen because the planet also emits radiation back
    to outer space.
    So there's an outflow to compare to the inflow.
    If you look in the upper right, you'll see
    that approximately 239 watts per meter squared
    are ultimately leaving as longwave radiation, too.
    Things get complicated on the right-hand side of this diagram.
    We've seen that the Earth absorbs some energy from the Sun.
    This helps warm the Earth.
    The Earth, then, as an object at some temperature, also radiates energy,
    and it radiates infrared energy, longwave energy,
    because it's a relatively cool object.
    That's the 396 watts per meter squared labeled "surface radiation."
    A portion of that longwave radiation, about 40 watts per meter squared,
    proceeds directly through the atmosphere to outer space.
    These are particular wavelengths of radiation
    that don't interact with any of the gases in our atmosphere.
    But a lot of the surface radiation doesn't make it directly out to space,
    but instead gets absorbed in the atmosphere by greenhouse gases
    and also clouds.
    These, then, reemit the radiation in random directions,
    though the randomness is not shown particularly well here.
    But it means the energy could go back towards Earth's surface
    where it would get reabsorbed, helping to raise Earth's surface temperature,
    or the energy could go out toward space, or the energy
    could get absorbed by another greenhouse gas molecule, which will then reemit it
    in yet another random direction.
    We'll look at more detail about the greenhouse effect in another lesson.
    The point here is that the presence of greenhouse gases
    slows the passage of radiation from Earth's surface
    to space, increasing the total inflow of energy to Earth's surface,
    warming the surface, which, as a now warmer object, radiates more energy.
    One minor point before we talk about energy balances.
    Most of the energy leaves Earth's surface via radiation,
    but some leaves via latent heat transfer or as thermals.
    In latent heat transfer, water evaporates from the oceans or land,
    which takes energy.
    Then, in the atmosphere, when the water vapor condenses,
    it releases that energy to the atmosphere.
    It's another way to transfer energy from Earth's surface into the atmosphere.
    Thermals rising away from Earth's surface also can transfer energy.
    Time for a couple of questions about balance or imbalance in energy flows.
    Using the numbers highlighted which represent flows
    through the top of the atmosphere, figure out
    whether, according to these numbers, Earth's energy budget is in balance,
    or if Earth is gaining energy, or if Earth is losing energy.
    Which is it?


    Dr Sara Harris: You have to add up the two outflows of energy--
    the one that's from reflection and the one that's from longwave radiation.
    These add up to 340.4, which is 0.9 watts per meter squared smaller
    than the flow of energy coming in.
    So according to these numbers, earth is out of balance
    by about 0.9 watts per meter squared.
    Other estimates, with other approaches and data
    from slightly different timespans, range from about 0.5 to 1 watt
    per meter squared.
    Try that for Earth's surface.
    Figure out all the inflows and all the outflows, and see whether they balance.

    The energy out of the system is the sum of the reflected solar radiation and the outgoing longwave radiation (101.9 + 238.5 = 340.4 W/m2). This number is slightly less than the amount of incoming solar radiation (341.3 W/m2). The Earth is therefore gaining more energy than it is losing.


    Dr Sara Harris: You have to add up the two outflows of energy--
    the one that's from reflection and the one that's from longwave radiation.
    These add up to 340.4, which is 0.9 watts per meter squared smaller
    than the flow of energy coming in.
    So according to these numbers, earth is out of balance
    by about 0.9 watts per meter squared.
    Other estimates, with other approaches and data
    from slightly different timespans, range from about 0.5 to 1 watt
    per meter squared.
    Try that for Earth's surface.
    Figure out all the inflows and all the outflows, and see whether they balance.


    Dr Sara Harris: If you add up all the inflows and subtract away all the outflows,
    you should find a gain of about one watt per meter squared, based on these data.
    Earth's surface is gaining energy.
    That was a short tour of the processes involved in earth's radiation budget.
    It's worth spending some time with the figure.
    Check out other balances or imbalances you can find.
    What about the overall balance of energy in the atmosphere?
    Try that one for yourself.

    At the end of this last video, you're asked to figure out the balance of inflows and outflows of energy to and from the atmosphere. If you do the exercise, you'll have spent a good amount of time examining the various flows and their relative magnitudes, which is great. You will, however, find a difference of inflow and outflow that turns out to not be physically meaningful. The best known numbers on the diagram are the fluxes in and out of the top of the atmosphere, which are measured quite accurately using instruments on satellites. Estimates for Earth's energy imbalance typically fall between about 0.5 and 1 W/m2. Trenberth et al., 2009, the source of these data, find an imbalance of 0.9 W/m2.

    Read about recent variations in incoming solar energy. This looks like a lot of reading, but it's really just a lot of links!
    1 Read this explanation of sunspots over time from NASA:
    2 Be sure to click on the word Sunspots and read the brief descriptions of sunspots and faculae because they are relevant to solar energy output.
    3 Also be sure to click on the image in the paragraph under “Maunder Minimum” in order to see how sunspots have varied since the 1600s.
    4 Read “How do we know the current warming trend isn’t caused by the Sun?” which is pages 11 and 12, in this document: “Climate Change: Evidence, Impacts, and Choices” from the National Research Council of the National Academies in the USA. You can download this document in either English or Spanish here:
    6 Here is the direct link to the English version to read online:
    7 or the PDF file to download:
    9 And here’s the direct link to the Spanish version to read online:
    11 Have a look at the plot shown here:
    13 How would you interpret the data shown in this figure? Note the links to the data under the figure. You can plot and analyze these data yourself if you want!

    The Sunspot Cycle
    (Updated 2015/08/25)
    Please note: Dr. David Hathaway, a member of the MSFC solar physics group for 29 years, has transferred to NASA's Ames Research Center in California. Dr. Hathaway will continue to update his solar cycle pages when he is settled. Dr. Hathaway's email address remains the same.

    Click on image for larger version.
    Sunspot Numbers
    In 1610, shortly after viewing the sun with his new telescope, Galileo Galilei (or was it Thomas Harriot?) made the first European observations of Sunspots. Continuous daily observations were started at the Zurich Observatory in 1849 and earlier observations have been used to extend the records back to 1610. The sunspot number is calculated by first counting the number of sunspot groups and then the number of individual sunspots.
    The "sunspot number" is then given by the sum of the number of individual sunspots and ten times the number of groups. Since most sunspot groups have, on average, about ten spots, this formula for counting sunspots gives reliable numbers even when the observing conditions are less than ideal and small spots are hard to see. Monthly averages (updated monthly) of the sunspot numbers (181 kb JPEG image), (307 kb pdf-file), (62 kb text file) show that the number of sunspots visible on the sun waxes and wanes with an approximate 11-year cycle.

    (Note: there are actually at least two "official" sunspot numbers reported. The International Sunspot Number as compiled by the Solar Influences Data Analysis Center in Belgium, has been revised recently (V2.0 -- summer 2015), and should now more closely match the NOAA sunspot number. The NOAA sunspot number is compiled by the US National Oceanic and Atmospheric Administration. The numbers tabulated in SN_m_tot_V2.0.txt are the monthly averages of the daily sunspot number with error estimates as posted at the WDC-SILSO, Royal Observatory of Belgium, Brussels.)
    The Maunder Minimum
    Early records of sunspots indicate that the Sun went through a period of inactivity in the late 17th century. Very few sunspots were seen on the Sun from about 1645 to 1715 (38 kb JPEG image). Although the observations were not as extensive as in later years, the Sun was in fact well observed during this time and this lack of sunspots is well documented. This period of solar inactivity also corresponds to a climatic period called the "Little Ice Age" when rivers that are normally ice-free froze and snow fields remained year-round at lower altitudes. There is evidence that the Sun has had similar periods of inactivity in the more distant past. The connection between solar activity and terrestrial climate is an area of on-going research.
    The Butterfly Diagram

    Click on image for larger version.
    Detailed observations of sunspots have been obtained by the Royal Greenwich Observatory since 1874. These observations include information on the sizes and positions of sunspots as well as their numbers. These data show that sunspots do not appear at random over the surface of the sun but are concentrated in two latitude bands on either side of the equator. A butterfly diagram (142 kb GIF image) (184 kb pdf-file) (updated monthly) showing the positions of the spots for each rotation of the sun since May 1874 shows that these bands first form at mid-latitudes, widen, and then move toward the equator as each cycle progresses.
    The Greenwich Sunspot Data
    The Royal Greenwich Observatory data has been appended with data obtained by the US Air Force Solar Optical Observing Network since 1977. This newer data has been reformatted to conform to the older Greenwich data and both are available in a local directory of ASCII files. Each file contains records for a given year with individual records providing information on the daily observations of active regions.
    Sunspot Cycle Predictions

    Click on image for larger version.
    MSFC Solar Physics Branch members Wilson, Hathaway, and Reichmann have studied the sunspot record for characteristic behavior that might help in predicting future sunspot activity. Our current predictions of solar activity for the next few years can be found at this link. Although sunspots themselves produce only minor effects on solar emissions, the magnetic activity that accompanies the sunspots can produce dramatic changes in the ultraviolet and soft x-ray emission levels. These changes over the solar cycle have important consequences for the Earth's upper atmosphere.
    Sunspot Cycle Review Articles

    Photospheric Features

    Click on image for larger version.
    Sunspots appear as dark spots on the surface of the Sun. Temperatures in the dark centers of sunspots drop to about 3700 K (compared to 5700 K for the surrounding photosphere). They typically last for several days, although very large ones may live for several weeks. Sunspots are magnetic regions on the Sun with magnetic field strengths thousands of times stronger than the Earth's magnetic field. Sunspots usually come in groups with two sets of spots. One set will have positive or north magnetic field while the other set will have negative or south magnetic field. The field is strongest in the darker parts of the sunspots - the umbra. The field is weaker and more horizontal in the lighter part - the penumbra.

    Click on image for larger version.
    Faculae are bright areas that are usually most easily seen near the limb, or edge, of the solar disk. These are also magnetic areas but the magnetic field is concentrated in much smaller bundles than in sunspots. While the sunspots tend to make the Sun look darker, the faculae make it look brighter. During a sunspot cycle the faculae actually win out over the sunspots and make the Sun appear slightly (about 0.1%) brighter at sunspot maximum that at sunspot minimum.

    Click on image for larger version.
    Granules are small (about 1000 km across) cellular features that cover the entire Sun except for those areas covered by sunspots. These features are the tops of convection cells where hot fluid rises up from the interior in the bright areas, spreads out across the surface, cools and then sinks inward along the dark lanes. Individual granules last for only about 20 minutes. The granulation pattern is continually evolving as old granules are pushed aside by newly emerging ones (470 kB MPEG movie from the Swedish Vacuum Solar Telescope). The flow within the granules can reach supersonic speeds  of more than 7 km/s (15,000 mph) and produce sonic "booms" and other noise that generates waves on the Sun's surface.

    Click on image for larger version.
    Supergranules are much larger versions of granules (about 35,000 km across) but are best seen in measurements of the "Doppler shift" where light from material moving toward us is shifted to the blue while light from material moving away from us is shifted to the red. These features also cover the entire Sun and are  continually evolving. Individual supergranules last for a day or two and have flow speeds of about 0.5 km/s (1000 mph). The fluid flows observed in supergranules carry magnetic field bundles to the edges of the cells where they produce the chromospheric network.

    How do we know that the current warming
    trend is not caused by natural cycles?
    etecting climate trends is
    complicated by the act
    that there are many natural
    variations in temperature,
    precipitation, and other
    climate variables. These
    natural variations are
    caused by many dierent
    processes that can occur
    across a wide range o
    timescales—rom a particularly
    warm summer or snowy winter
    to changes over many millions o
     Among the most well-known short-term cli-
    matic fuctuations are El Niño and La Niña, which
    are periods o natural warming and cooling in the
    tropical Pacic Ocean. Strong El Niño and La Niña
    events are associated with signicant year-to-year
    changes in temperature and rainall patterns across
    many parts o the planet, including the United
    States. These events have been linked to a number
    o extreme weather events, such as the 1992 food-
    ing in midwestern states and the severe droughts
    in southeastern states in 2006 and 2007. Globally,
    temperatures tend to be higher
    during El Niño periods, such as
    1998, and lower during La
    Niña years, such as 2008.
    However, these up-and-
    down fuctuations are
    smaller than the 20th cen-
    tury warming trend; 2008
    was still quite a warm year
    in the long-term record.
    Natural climate variations can
    also be orced by slow changes in
    the Earth’s orbit around the Sun that
    aect the solar energy received by Earth, as
    is the case with the Ice Age cycle (see pp. 18-19)
    or by short-term changes in the amount o volca-
    nic aerosols in the atmosphere. Major eruptions,
    like that o Mount Pinatubo in 1991, spew huge
    amounts o particles into the stratosphere that
    cool Earth. However, surace temperatures typically
    rebound in 2-5 years as the particles settle out o
    the atmosphere. The short-term cooling eects o
    several large volcanic eruptions can be seen in the
    20th century temperature record, as can the global
    temperature variations associated with several

    strong El Niño and La Niña events, but an overall
    warming trend is still evident (Figure 12).
    In order to put El Niño and La Niña events and
    other short-term natural fuctuations into perspec-
    tive, climate scientists examine trends over several
    decades or longer when assessing the human infu-
    ence on the climate system. Based on a rigorous as-
    sessment o available temperature records, climate
     orcing estimates, and sources o natural climate
    variability, scientists have concluded that there is a
    more than 90% chance that most o the observed
    global warming trend over the past 50 to 60 years
    can be attributed to emissions rom the burning o
     ossil uels and other human activities.
    Such statements that attribute climate change
    to human activities also rely on inormation rom
    FIGURE 12
    Short-term Temperature Eects
    o Natural Climate Variations
    Natural actors, such as volcanic
    eruptions and El Niño and La Niña
    events, can cause average global
    temperatures to vary rom one year
    to the next, but cannot explain the
    long-term warming trend over the
    past 60 years.
    Image courtesy o the
    Marian Koshland Science Museum

    FIGURE 13
    Model Runs With and Without
    Human Infuences
    simulations o 20th-century surace
    temperatures more closely match
    observed temperature when both
    natural and human infuences are
    included in the simulations. The
    black line shows an estimate o
    observed surace temperatures
    changes. The blue line shows results
    rom models that only include
    natural orcings (solar activity and
    volcanoes). The red-shaded regions
    show results rom models that
    include both natural and human
    Source: Meehl et al, 2011

    About 30% of the solar energy that arrives at our planet gets reflected back to space nearly immediately. Here we’ll look at some of the important reflective materials in Earth’s climate system, including both substances in the atmosphere and on Earth’s surface. Reflectivity is involved in some important feedback loops in the climate system, and some mitigation strategies involve deliberately influencing reflectivity.
    Learning Goals
    By the end of this section, you will be able to:
    1 Explain how reflection fits into Earth’s overall energy budget.
    2 Rank different surfaces based on their reflectivity (e.g. deserts, forests, clouds, ice, ocean water etc.).
    3 Predict how particular changes in the reflective properties of Earth’s surface or atmosphere would likely affect Earth’s temperature.
    4 Construct feedback loops involving reflectivity.

    Published: May 8, 2010, 3:53 am
    Updated: May 27, 2013, 3:21 am
    Author: Dagmar Budikova
    Contributing Author: C Michael Hogan
    Topic Editor: Michael Pidwirny
    Land-use & Land-cover Change
    Remote Sensing

    Albedo of the Earth's terrestrial surface as measured by the TERRA satellite. Data collected from the period April 7-22, 2002. (Source: NASA Earth Observatory).

    Albedo is the fraction of Sun’s radiation reflected from a surface. The term has its origins from the Latin word albus, meaning “white”. It is quantified as the proportion, or percentage of solar radiation of all wavelengths reflected by a body or surface to the amount incident upon it. An ideal white body has an albedo of 100% and an ideal black body, 0%. Visually we can estimate the albedo of an object’s surface from its tone or color. This method suggests that albedo becomes higher as an object gets lighter in shade. The data in Table 1 verifies this fact. Light toned surfaces like snow do have high albedos. Low albedos are associated with surfaces that appear dark colored to our eyes. Some dark colored surfaces include black-top roads, coniferous forest, and dark soil. Table 1 also indicates that the albedo of water varies with Sun angle. When Sun angles are high, water tends to absorb more than 95% of the insolation falling on it. At low Sun angles, the surface of water becomes much more reflective.

    On average the Earth and its atmosphere typically reflect about 4% and 26%, respectively, of the Sun’s incoming radiation back to space over the course of one year. As a result, the earth-atmosphere system has a combined albedo of about 30%, a value that is dependent on a number of factors including soil type, vegetation cover, and cloud distribution.
    The reflectance of locations on the Earth's surface exhibit large geographic variation. Mean annual albedo values differ considerably between the equator and the poles, largely due to the presence of snow and ice-covered surfaces. As the characteristics of a surface change from one season to another, so do its reflectance properties. This fact is most evident throughout the high latitudes, where snow cover and ice extent reach maximum values during the cold seasons, significantly increasing the surface reflectance values. Melting in the spring exposes bare soils that absorb a significantly greater portion of the incoming solar radiation, decreasing the albedo values.
    Global measurements of the Earth’s surface albedo can be determined with the aid of sensors aboard orbiting space satellites. NASA’s Earth Radiation Budget Experiment (ERBE) was one of the first attempts of making such measurements. This experiment used a variety of satellite sensors aboard Nimbus-7, NOAA-9, and the Earth Radiation Budget Satellite (ERBS) to monitor the Earth’s albedo for a period of about four years. Figures 1 and 2 show the monthly average surface albedo of the Earth for January and July, 1987. In these figures, most of the reflective properties of the atmosphere have been removed. The patterns seen here are probably representative for most other years.  For both January and July, the lowest surface albedos occur over oceans in a zone that covers more than 100 degrees of latitude. Albedo values of this zone are between 8 and 13%, and the center of this zone shifts seasonally. In July, the low albedo zone is located approximately at the Tropic of Cancer (23.5°N), while in January it migrates to the Tropic of Capricorn (23.5°S). At the higher latitudes, the albedo of the ocean surface increases significantly because of low Sun angles or the presence of sea ice. In the July image, the region occupied by the Arctic Ocean has an albedo between 45 to 60%.  On the Earth’s terrestrial surface, vegetated areas have an albedo from 15 to 25%. Non-vegetated regions like the Sahara Desert reflect about 30 to 40% of the Sun’s incoming light. Other land surfaces with high albedos are glaciers and seasonal snowfields. The large glaciers covering Greenland and Antarctica reflect as much as 75% of the insolation falling on their surfaces. Comparing the January and July images, we can see that the albedos of areas with a latitude greater than 45°N vary annually because of seasonal snowfall. In these areas, summer albedos typically are around 20%, while winter values jump to as high as 70%.

    Figure 1. Surface reflectivity of the Earth for January 1987. Cells with missing data are colored white. Measured by sensors aboard a variety of satellites for NASA’s Earth Radiation Budget Experiment (ERBE). (Image Source: NASA - Earth Radiation Budget Experiment).

    Figure 2. Surface reflectivity of the Earth for January and July 1987. Cells with missing data are colored white. Measured by sensors aboard a variety of satellites for NASA’s Earth Radiation Budget Experiment (ERBE). (Image Source: NASA - Earth Radiation Budget Experiment).
    Figures 3 and 4 describe measurements of  combined surface and atmosphere albedo for our planet. Comparing these figures to Figures 1 and 2 illustrates the large effect that clouds have on reflecting incoming sunlight back to space. Significant bands of reflective cloud exist over at the equator and in the mid-latitudes. Skies are generally clear of cloud over the major deserts, subtropical oceans, and the large continental glaciers of Greenland and Antarctica.

    Figure 3. Combined surface and atmosphere reflectivity (or planetary albedo) of the Earth for January 1987. Cells with missing data are colored white. Measured by sensors aboard a variety of satellites for NASA’s Earth Radiation Budget Experiment (ERBE). (Image Source: NASA - Earth Radiation Budget Experiment).

    Figure 4. Combined surface and atmosphere reflectivity (or planetary albedo) of the Earth for July 1987. Cells with missing data are colored white. Measured by sensors aboard a variety of satellites for NASA’s Earth Radiation Budget Experiment (ERBE). (Image Source: NASA - Earth Radiation Budget Experiment).

    Climate forcing
    The proportion of absorbed, emitted, and reflected incoming solar radiation steers the Earth's climate system causing fluctuations in temperature, winds, ocean currents, and precipitation. The climate system remains in equilibrium as long as the amount of absorbed solar radiation is in balance with the amount of terrestrial radiation emitted back to space. Earth's albedo values are very important in shaping local and global climates through the radiation budget, determined as the difference between the amount of absorbed shortwave radiation (input) and the outgoing longwave radiation (output). For instance, clouds control the amount of energy that may reach the Earth’s surface. Since mean cloudiness varies geographically with lowest values observed in the subtropics and highest values in the mid- to high-latitudes, the variation of surface reflectance has a significant impact on the distribution of absorbed solar radiation at the surface. Approximately half of the incident solar energy is absorbed by the Earth's surface. This energy is then used to heat the land and oceans and drive the hydrologic cycle.
    Terrestrial factors affecting albedo
    A variety of factors affect terrestrial albedo including: (a) soil type; (b) soil moisture or icing; (c) vegetation types; (d) soil and vegetative color; (e) micro-topography and (f) macro-topography.
    Soil factors
    Soil color certainly affects reflectivity, with lighter colors having greater albedo than dark colors, and hence exhibit higher albedo. Soil texture is also a factor that affects albedo. Some studies have shown that sandy soils have higher albedo, and data clearly demonstrate that albedo is strongly affected by mineral salt content including sodium chloride and magnesium chloride.
    Vegetative factors
    A variety of factors influence the ability of plants to reflect sunlight. At the most simplistic level, dark coloration provides the greatest absorbtion and hence the lowest albedo. However, leaf shape is quite important, with leaf shapes that are planar providing a higher reflectivity; this effect explains why conifer forests tend to have lower albedo than angiosperm or broadleaf forests. Furthermore, leaf aspect is also contributory, with leaves that have surfaces parallel to the ground surface having the highest albedo.
    Topographic factors
    Macro-topography implies the recognition of overt slope differences; for example, areas of steep slope can be expected to produce lower effective albedo, simply because the angle of reflection forces incoming radiation to endure a subsequent path that is subject to further absorption by secondary incidence and also due to a longer path length of travel for reflected electromagnetic waves. Micro-topography is the presence of dimpled soils which have small crevices and indentations. In these cases there is a similar reduction in albedo where opportunities for multiple reflections from surface complexities exist.
    Measurement of albedo
    Surface reflectance has been derived through the use of satellites and remote sensing technology. The International Satellite Cloud Climatology Project (ISCCP) established as part of the World Climate Research Programme (WCRP) has been collecting surface and atmospheric reflectance data since 1983. A traditional technique for estimating the Earth's albedo is observation of the moon's ashgrey light—earthlight reflected from its dark hemisphere.


    Dr Sara Harris: Welcome to this lesson about some aspects of Earth's
    reflectivity, and in particular some dynamic changes in reflectivity
    and feedbacks involving reflectivity.
    As you know, some surfaces are more reflective than others.
    Clean ice and clouds are highly reflective.
    Ocean water and dark forests are less reflective.
    Tiny particles and droplets in the atmosphere
    can be reflective, like sulfate aerosols from volcanoes and fossil fuel burning
    or particles of sea salt whipped into the atmosphere by breaking waves.
    Or particles in the atmosphere can be less reflective,
    like soot from forest fires.
    The nature of Earth's surface and the stocks
    of different reflective materials in the atmosphere can change over time.
    In this lesson, we'll take a look at some examples
    and get into a few of the feedbacks in Earth's climate system
    that involve reflectivity.
    There are, of course, far more out there in the world
    than we'll be able to talk about here.
    Here's an example of an interaction between different parts of the climate
    system that changes reflectivity.
    This is an image from NASA.
    And it's a picture of snow in the mountains of Colorado.
    And what you can see is that the surface of the snow has a lot of dust on it.
    This is dust that's blowing in from deserts in the Western United States.
    And over time, the dust influx has increased,
    which darkens the snow surfaces, which then absorb more solar energy.
    And then they melt faster.
    The faster melting then changes the seasonal availability
    of water for the ecosystems downstream from this melting snowpack,
    releasing it earlier in the year with various biological ramifications.
    So this is just an example of how reflectivity can influence and also
    be influenced by other parts of the climate system.
    Reflectivity is one of the places in Earth's climate system
    where we humans have opportunities to intervene and change energy flows.
    One way we do it is by emitting things into the atmosphere.
    We emit things like reflective sulfates when we burn coal.
    We also emit black soot, which is not reflective.
    And when it lands on highly reflective surfaces like ice,
    it decreases the reflectivity of the ice,
    like in this Colorado example with dust.
    We also change the nature of land surfaces
    by clearing forests for agriculture, which
    changes the surface from dark to lighter,
    or by abandoning more reflective agricultural land on which forests then
    grow back.
    In some places, we actively plant forests.
    As we think about mitigation options to counter warming,
    it's worth evaluating those that make Earth more reflective.
    We saw earlier that about 30% of incoming solar radiation
    gets reflected right back to space, both by reflective things in the atmosphere
    and reflective things on Earth's surface.
    Reflection in the atmosphere accounts for more watts per meter
    squared going back to space than does reflection off the surface.
    And clouds alone are responsible for about half the total reflection.
    So clouds are important.
    But first let's have a look at the surface without the clouds.
    This is an image of Earth with the clouds removed.
    Notice the dark ocean, the white ice on Antarctica, Greenland,
    and other high northern latitudes.
    You can even see some of the ice on mountain glaciers if you look closely.
    Notice the dark green forests and the light-colored deserts.
    You can see there are bands of forests dominating
    at some latitudes and bands of deserts dominating at other latitudes.
    These patterns are largely related to atmospheric circulation
    and regional temperature and precipitation.
    Here's a beautiful boundary between forest and desert in Africa.
    This is a boundary that shifts a little bit over time.
    So let's just consider some what-if scenarios.
    What if the forested area expanded a little bit northward
    into the desert area?
    What would happen to the reflectivity of this region?


    Dr Sara Harris: If in this part of the world, the area covered by forest
    expanded and that covered by desert decreased,
    then overall the surface would be darker and reflectivity would decrease.
    If this were the only thing going on in the world,
    the surface would absorb more incoming solar radiation and it would warm up.
    You can imagine all sorts of changes in Earth's surface
    that would alter overall albedo.
    What would happen, for example if sea level rose or fell?
    The oceans are generally darker than the land surface,
    so sea level can alter surface reflectivity, too.
    Think about other possible swaps, their effects on reflectivity,
    and ultimately, on temperature.
    In an earlier lesson, we've already seen at least one feedback
    involving reflectivity.
    That's the ice albedo feedback.
    And that one is an amplifying feedback.
    Here we're going to have a look at some others including both amplifying
    and stabilizing feedbacks.
    Let's look at a feedback involving vegetation reflectivity.
    This one actually involves snow, as well.
    We saw earlier that the northern high latitudes are warming faster
    than other parts of the world.
    So warmer temperatures up there are make it
    possible for taller shrub and even trees to start gaining a foothold
    and expanding into tundra ecosystems.
    The taller, darker vegetation sticks up further above the snow.
    And this area then becomes less reflective, absorbs more solar energy,
    and that all helps promote warming.
    This is an amplifying feedback, because the response
    helps push the system in the same direction
    as the perturbation, which was an initial warming.
    Heading into the atmosphere now, since that's where a lot of the reflection
    takes place particularly by clouds, but also aerosols,
    like dust and sulfuric acid droplets.
    Some clouds are highly reflective and others are less reflective.
    And also, different particles are more or less reflective
    depending on what they are.
    About clouds, characteristics that make particular clouds better reflectors are
    first, cloud thickness.
    Thick clouds are more reflective than thin clouds.
    Second, there's droplet size.
    Small droplets are more reflected than large droplets.
    And third, there's droplet concentration.
    The more droplets present in a given volume of the atmosphere,

    the more reflective the clouds.
    One way to get smaller droplets sizes and potentially, higher concentrations

    is where there are lots of aerosols in the atmosphere, which
    act as tiny nucleation services for the droplets.
    And when the cloud is composed of smaller droplets,
    the small droplets tend not to rain out to as readily as larger droplets.
    So the cloud lifetime in the atmosphere has a chance to the extended,
    too, which gives it a chance to reflect more solar radiation.
    Clouds are complicated.
    Feedbacks involving clouds are one of the parts of the climate system
    that's least well understood right now.
    So we'll have a look at a couple of what if scenarios in order
    to think about the processes involved in cloud feedbacks.
    But the devil is really in the details when we're dealing with clouds.
    So imagine a perturbation toward warming,
    which means that overall there'd be more water in the atmosphere.
    Take a look at this loop and decide what happens
    next where the question mark is, and therefore,
    whether this is an amplifying feedback or a stabilizing feedback.


    Dr Sara Harris: So we have more water in the atmosphere.
    And if that extra water is in liquid or ice forms,
    say as droplets or ice crystals in clouds, then cloud cover
    would increase, then overall reflectivity would increase,
    more incoming solar radiation would get reflected,
    and all that would counteract the warming.
    This will be a stabilizing feedback.
    Another of the possibilities is that a perturbation toward warming
    translates into more of the water present in the atmosphere being
    there in the form of water vapor, not as droplets or ice crystals.
    At warmer temperatures in general a greater proportion of the water
    is in vapor form.
    With warming, liquid droplets in the atmosphere might actually evaporates.
    In this case, there'd be less cloud cover, lower reflectivity,
    and the warming would be amplified by this type of response.
    In addition, the water vapor is a greenhouse gas,
    but that's a different feedback.
    From recent research it's looking like cloud feedbacks in a warming world
    are likely to be overall amplifying.
    But the ranges of possibility include clouds
    acting as a net stabilizing feedback, or having little feedback effect.
    It's an area of active research.
    We've barely scratched the surface of reflectivity issues in the climate
    system here.
    Ultimately, just like in all the other parts of the climate system,
    it's changes in the stocks of things that can influence energy flows.
    If the stock of clouds, or reflective particles,
    or forests, or ocean water changes, the amount of energy
    reflected directly back to space will also change,
    and will alter earth's energy balance.
    For each one of the reflective players, we
    have to take a close look at the processes involved
    in inflow and outflow for that particular substance.
    We have to look at which one of the flows is winning over time,
    and how they're interacting with the other parts of the system.

    Read: “Stratospheric sulfur aerosols” from Wikipedia:
    1 What are the basic processes by which large explosive volcanic eruptions like Mt. Pinatubo influence Earth’s climate? Do these eruptions warm or cool the planet?
    2 There will be other large explosive volcanic eruptions in the future. How would you expect global temperature to respond to one of these future eruptions? How long would you expect the effects to last?
    3 What do you think about the geoengineering idea to imitate volcanoes?
    Stratospheric sulfur aerosols
    From Wikipedia, the free encyclopedia

    Jump to: navigation, search
    Stratospheric sulfur aerosols are sulfur-rich particles which exist in the stratosphere region of the Earth's atmosphere. The layer of the atmosphere in which they exist is known as the Junge layer, or simply the stratospheric aerosol layer. These particles consist of a mixture of sulfuric acid and water. They are created naturally, such as by photochemical decomposition of sulfur-containing gases, e.g. carbonyl sulfide. When present in high levels, e.g. after a strong volcanic eruption such as Mount Pinatubo, they produce a cooling effect, by reflecting sunlight, and by modifying clouds as they fall out of the stratosphere.[1] This cooling may persist for a few years before the particles fall out.
    An aerosol is a suspension of fine solid particles or liquid droplets in a gas. The sulfate particles or sulfuric acid droplets in the atmosphere are about 0.1 to 1.0 micrometer (a millionth of a meter) in diameter.
    Sulfur aerosols are common in the troposphere as a result of pollution with sulfur dioxide from burning coal, and from natural processes. Volcanos are a major source of particles in the stratosphere as the force of the volcanic eruption propels sulfur-containing gases into the stratosphere. The relative influence of volcanoes on the Junge layer varies considerably according to the number and size of eruptions in any given time period, and also of quantities of sulfur compounds released. Only stratovolcanoes containing primarily granitic rocks are responsible for these fluxes, as basaltic rock erupted in shield volcanoes doesn't result in plumes which reach the stratosphere.
    Creating stratospheric sulfur aerosols deliberately is a proposed geoengineering technique which offers a possible solution to some of the problems caused by global warming. However, this will not be without side effects [2] and it has been suggested that the cure may be worse than the disease.[3]

    Pinatubo eruption cloud. This volcano released huge quantities of stratospheric sulfur aerosols and contributed greatly to understanding of the subject.

    Contents  [hide]
    1 Origins
    2 Chemistry
    3 Scientific study
    4 Effects
    5 Climate engineering
    6 See also
    7 References


    Volcanic "injection"
    Natural sulfur aerosols are formed in vast quantities from the SO2 ejected by volcanoes,[4] which may be injected directly into the stratosphere during very large (Volcanic Explosivity Index, VEI, of 4 or greater) eruptions. A comprehensive analysis, dealing largely with tropospheric sulfur compounds in the atmosphere, is provided by Bates et al.[5]
    The IPCC AR4 says explosive volcanic events are episodic, but the stratospheric aerosols resulting from them yield substantial transitory perturbations to the radiative energy balance of the planet, with both shortwave and longwave effects sensitive to the microphysical characteristics of the aerosols.[6]
    During periods lacking volcanic activity (and thus direct injection of SO2 into the stratosphere), oxidation of COS (carbonyl sulfide) dominates the production of stratospheric sulfur aerosol.[7]
    Main article: Sulfur cycle
    The chemistry of stratospheric sulfur aerosols varies significantly according to their source. Volcanic emissions vary significantly in composition, and have complex chemistry due to the presence of ash particulates and a wide variety of other elements in the plume.[8]
    The chemical reactions affecting both the formation and elimination of sulfur aerosols are not fully understood. It is difficult to estimate accurately, for example, whether the presence of ash and water vapour is important for aerosol formation from volcanic products, and whether high or low atmospheric concentrations of precursor chemicals (such as SO2 and H2S) are optimal for aerosol formation. This uncertainty makes it difficult to determine a viable approach for geoengineering uses of sulfur aerosol formation.
    Scientific study[edit]

    Stratospheric sulfates from volcanic emissions cause transient cooling; the purple line showing sustained cooling is from tropospheric sulfate
    Understanding of these aerosols comes in large part from the study of volcanic eruptions,[9] notably Mount Pinatubo in the Philippines,[10] which erupted in 1991 when scientific techniques were sufficiently far advanced to study the effects carefully.[11]
    The formation of the aerosols and their effects on the atmosphere can also be studied in the lab. Samples of actual particles can be recovered from the stratosphere using balloons or aircraft.[12]
    Computer models can be used to understand the behaviour of aerosol particles, and are particularly useful in modelling their effect on global climate.[13]
    Biological experiments in the lab, and field/ocean measurements can establish the formation mechanisms of biologically derived volatile sulfurous gases.[5]
    It has been established that emission of precursor gases for sulfur aerosols is the principal mechanism by which volcanoes cause episodic global cooling.[14] The Intergovernmental Panel on Climate Change AR4 regards stratospheric sulfate aerosols as having a low level of scientific understanding. The aerosol particles form a whitish[3] haze in the sky. This creates a global dimming effect, where less of the sun's radiation is able to reach the surface of the Earth. This leads to a global cooling effect. In essence, they act as the reverse of a greenhouse gas, which tends to allow visible light from the sun through, whilst blocking infra-red emitted from the Earth's surface and its atmosphere. The particles also radiate infra red energy directly, as they lose heat into space.

    Solar radiation reduction due to volcanic eruptions
    All aerosols both absorb and scatter solar and terrestrial radiation. This is quantified in the Single Scattering Albedo (SSA), the ratio of scattering alone to scattering plus absorption (extinction) of radiation by a particle. The SSA tends to unity if scattering dominates, with relatively little absorption, and decreases as absorption increases, becoming zero for infinite absorption. For example, sea-salt aerosol has an SSA of 1, as a sea-salt particle only scatters, whereas soot has an SSA of 0.23, showing that it is a major atmospheric aerosol absorber.
    Aerosols, natural and anthropogenic, can affect the climate by changing the way radiation is transmitted through the atmosphere. Direct observations of the effects of aerosols are quite limited so any attempt to estimate their global effect necessarily involves the use of computer models. The Intergovernmental Panel on Climate Change, IPCC, says: While the radiative forcing due to greenhouse gases may be determined to a reasonably high degree of accuracy... the uncertainties relating to aerosol radiative forcings remain large, and rely to a large extent on the estimates from global modelling studies that are difficult to verify at the present time.[15] However, they are mostly talking about tropospheric aerosol.
    The aerosols have a role in the destruction of ozone[4] due to surface chemistry effects.[16] Destruction of ozone has in recent years created large holes in the ozone layer, initially over the Antarctic and then the Arctic. These holes in the ozone layer have the potential to expand to cover inhabited and vegetative regions of the planet, leading to catastrophic environmental damage.
    Ozone destruction occurs principally in polar regions,[17] but the formation of ozone occurs principally in the tropics.[18] Ozone is distributed around the planet by the Brewer-Dobson circulation.[19] Therefore, the source and dispersal pattern of aerosols is critical in understanding their effect on the ozone layer.

    Turner was inspired by dramatic sunsets caused by volcanic aerosols
    Aerosols scatter light, which affects the appearance of the sky and of sunsets. Changing the concentration of aerosols in the atmosphere can dramatically affect the appearance of sunsets. A change in sky appearance during the year without a summer (attributed to the eruption of Mount Tambora) was the inspiration for the paintings of J. M. W. Turner. Further volcanic eruptions and geoengineering projects involving sulfur aerosols are likely to affect the appearance of sunsets significantly,[20] and to create a haze in the sky.
    Aerosol particles are eventually deposited from the stratosphere onto land and ocean. Depending on the volume of particles descending, the effects may be significant to ecosystems, or may not be. Modelling of the quantities of aerosols used in likely geoengineering scenarios suggest that effects on terrestrial ecosystems from deposition is not likely to be significantly harmful.[21]
    Climate engineering[edit]
    Main articles: Climate engineering and Stratospheric sulfate aerosols (geoengineering)
    The ability of stratospheric sulfur aerosols to create this global dimming effect has made them a possible candidate for use in climate engineering projects to limit the effect and impact of climate change due to rising levels of greenhouse gases.[22][23] Delivery of precursor gases such as H2S and SO2 by artillery, aircraft and balloons has been proposed.[citation needed]
    Understanding of this proposed technique is partly based on the fact that it is the adaptation of an existing atmospheric process.[24] The technique is therefore potentially better understood than are comparable (but purely speculative) climate engineering schemes. It is also partly based on the speed of action of any such solution deployed,[25] in contrast to carbon sequestration projects such as carbon dioxide air capture which would take longer to work.[2] However, gaps in understanding of these processes exist, for example the effect on stratospheric climate and on rainfall patterns,[1] and further research is needed.[26]

    The greenhouse effect is the reason planet Earth’s average surface temperature is above freezing. Particular gases (greenhouse gases) in the atmosphere have chemical structures that allow them to absorb, then re-emit infrared radiation coming from Earth’s surface. Here we’ll examine the basics of greenhouse gases and how the greenhouse effect works, which helps us understand why human additions of greenhouse gases to the atmosphere cause warming. Influencing flows of greenhouse gases to and from the atmosphere are another place to look for mitigation options.
    Learning Goals
    By the end of this section, you will be able to:
    1 Identify greenhouse gases; identify non-greenhouse gas air molecules.
    2 Contrast the molecular structure of greenhouse gases and non-greenhouse gases.
    3 Describe how greenhouse gases themselves absorb and emit radiation, including what kinds of radiation (shortwave or longwave).
    4 Explain how the greenhouse effect warms Earth in terms of energy flows.
    5 Describe feedbacks involving the greenhouse effect.

    Atmosphere of Earth
    From Wikipedia, the free encyclopedia

    Jump to: navigation, search
    "Air" redirects here. For other uses, see Air (disambiguation).
    "Qualities of air" redirects here. It is not to be confused with Air quality.

    Blue light is scattered more than other wavelengths by the gases in the atmosphere, giving Earth a blue halo when seen from space onboard ISS at a height of 402–424 km.

    Composition of Earth's atmosphere by volume. The lower pie represents the trace gases that together compose about 0.038% of the atmosphere (0.043% with CO2 at 2014 concentration). The numbers are from a variety of years (mainly 1987, with CO2 and methane from 2009) and do not represent any single source.
    The atmosphere of Earth is the layer of gases surrounding the planet Earth that is retained by Earth's gravity. The atmosphere protects life on Earth by absorbing ultraviolet solar radiation, warming the surface through heat retention (greenhouse effect), and reducing temperature extremes between day and night (the diurnal temperature variation).
    The common name air (English pronunciation: /ɛər/) is given to the atmospheric gases used in breathing and photosynthesis. By volume, dry air contains 78.09% nitrogen, 20.95% oxygen,[1] 0.93% argon, 0.039% carbon dioxide, and small amounts of other gases. Air also contains a variable amount of water vapor, on average around 1% at sea level, and 0.4% over the entire atmosphere. Air content and atmospheric pressure vary at different layers, and air suitable for the survival of terrestrial plants and terrestrial animals is found only in Earth's troposphere and artificial atmospheres.
    The atmosphere has a mass of about 5.15×1018 kg,[2] three quarters of which is within about 11 km (6.8 mi; 36,000 ft) of the surface. The atmosphere becomes thinner and thinner with increasing altitude, with no definite boundary between the atmosphere and outer space. The Kármán line, at 100 km (62 mi), or 1.57% of Earth's radius, is often used as the border between the atmosphere and outer space. Atmospheric effects become noticeable during atmospheric reentry of spacecraft at an altitude of around 120 km (75 mi). Several layers can be distinguished in the atmosphere, based on characteristics such as temperature and composition.
    The study of Earth's atmosphere and its processes is called atmospheric science (aerology). Early pioneers in the field include Léon Teisserenc de Bort and Richard Assmann.[3]

    Contents  [hide]
    1 Composition
    2 Structure of the atmosphere
    2.1 Principal layers
    2.1.1 Exosphere
    2.1.2 Thermosphere
    2.1.3 Mesosphere
    2.1.4 Stratosphere
    2.1.5 Troposphere
    2.2 Other layers
    3 Physical properties
    3.1 Pressure and thickness
    3.2 Temperature and speed of sound
    3.3 Density and mass
    4 Optical properties
    4.1 Scattering
    4.2 Absorption
    4.3 Emission
    4.4 Refractive index
    5 Circulation
    6 Evolution of Earth's atmosphere
    6.1 Earliest atmosphere
    6.2 Second atmosphere
    6.3 Third atmosphere
    6.4 Air pollution
    7 Images from space
    8 See also
    9 References
    10 External links

    Main article: Atmospheric chemistry

    Mean atmospheric water vapor
    Air is mainly composed of nitrogen, oxygen, and argon, which together constitute the major gases of the atmosphere. Water vapor accounts for roughly 0.25% of the atmosphere by mass. The concentration of water vapor (a greenhouse gas) varies significantly from around 10 ppmv in the coldest portions of the atmosphere to as much as 5% by volume in hot, humid air masses, and concentrations of other atmospheric gases are typically provided for dry air without any water vapor.[4] The remaining gases are often referred to as trace gases,[5] among which are the greenhouse gases such as carbon dioxide, methane, nitrous oxide, and ozone. Filtered air includes trace amounts of many other chemical compounds. Many substances of natural origin may be present in locally and seasonally variable small amounts as aerosols in an unfiltered air sample, including dust of mineral and organic composition, pollen and spores, sea spray, and volcanic ash. Various industrial pollutants also may be present as gases or aerosols, such as chlorine (elemental or in compounds), fluorine compounds and elemental mercury vapor. Sulfur compounds such as hydrogen sulfide and sulfur dioxide (SO2) may be derived from natural sources or from industrial air pollution.
    Major constituents of dry air, by volume[6]
    in ppmv(B)
    in %
    Carbon dioxide
    Not included in above dry atmosphere:
    Water vapor(C)
    (A) volume fraction is equal to mole fraction for ideal gas only,
        also see volume (thermodynamics)
    (B) ppmv: parts per million by volume
    (C) Water vapor is about 0.25% by mass over full atmosphere
    (D) Water vapor strongly varies locally[4]

    Explore Explore this interactive simulation about the greenhouse effect from the PhET group at the University of Colorado.
    Click image to download:

    1 Go to
    2 Click the “Run Now” button to start the simulation. Or you can download it.  Note: You might need to update Java on your computer.  And, if you're on a Mac, you might need to download the simulation, then go to your downloads folder and right-click on the file and choose "Open".
    What to do:
    1 Along the top, click on the “Photon Absorption” tab.
    2 Explore all the features of this simulation.
    3 Figure out which of the five gases interact with visible photons.
    4 Figure out which of the five gases interact with infrared photons.
    5 Set yourself up in the simulation to observe photons getting absorbed (you have a variety of setup options you might choose).
    6 Decide what kind of data you can collect using the simulation (probably with help from a pencil and paper to keep track of your observations) to describe what happens to photons AFTER they’re absorbed.
    7 Write down a one-sentence description of what happens to photons after they get absorbed by gases in the atmosphere, according to this simulation.


    Dr Sara Harris: Welcome to the greenhouse effect lesson.
    We're going to talk about what greenhouse gases do in the atmosphere
    and how they influence energy flows.

    In particular, we'll have a look at the basic molecular structures
    of some different gases to see if they yield any clue as to which gases
    ARE greenhouse gases and which are not.
    Then we'll talk about inflows and outflows of energy
    to and from greenhouse gas molecules.
    Greenhouse gases don't just absorb energy, they also emit energy.
    And the sum of all the greenhouse gas actions
    together helps warm Earth to temperatures higher
    than it would be without greenhouse gases in the atmosphere.
    The greenhouse effect makes earth comfortably habitable.
    We'll start with a little context.

    The greenhouse effect is another one of those places in Earth's climate system
    where we have opportunities to perturb flows of energy.
    We've been perturbing energy flows by the greenhouse effect
    pathway pretty well so far, and the way we
    do it is by increasing the inflow of carbon dioxide and other greenhouse
    gases to the atmosphere so that their stocks go up,
    We've seen this plot before.
    It's the increase in atmospheric carbon dioxide since the late 1950s.
    These particular measurements were made at Mauna Loa Observatory in Hawaii,
    which is a good place, because it's fairly high altitude,
    and it's far enough away from local CO2 sources that might cause problems
    with the measurements.
    Also, Earth's atmosphere is generally well mixed with respect to CO2.
    And the long-term upward trend in the Mauna Loa data
    is a good indication of what's happening globally, and what's been happening
    is that inflows from burning fossil fuels, land use changes,
    and cement making have exceeded outflows to the oceans and plants and soils
    on land.
    So the CO2 stock goes up.
    As we think about mitigation options going forward,
    actions that could bring the concentration of greenhouse gases
    back down would help counteract these historical greenhouse perturbations.
    Here's that diagram of Earth's energy budget again.

    The parts of most interest to us in this lesson
    are those involved in the greenhouse effect, which
    is all the stuff on the right side of the diagram.
    It's the stuff like surface radiation, the stuff absorbed
    by the atmosphere, emitted by the atmosphere, greenhouse gases,
    back radiation absorbed by the surface.
    All of those arrows.
    We'll start with a question.
    What would you expect to happen to the surface radiation flow
    if greenhouse gases increased?

    Dr Sara Harris: If greenhouse gases increased,
    the energy emitted by greenhouse gases would increase.
    And some of that energy would go back toward earth's surface
    to be reabsorbed.
    So we'd expect the back radiation values shown on this image
    to increase as greenhouse gases increase.
    So that's making the total inflows of energy to earth's surface go up.
    To balance that extra inflow, we need additional outflow.
    Of course, some of the outflow could be made up
    by latent heat transfer or thermals, which we talked about before.
    But likely, some of the extra outflow would be via surface radiation.
    So that would go up, associated with an increase in temperature.
    And try this review question.
    Here are the distributions of radiation emitted by the sun and by earth.
    The types of radiation each emits depends on their temperature,
    which we saw earlier.
    And since the sun is hot, it emits ultraviolet, visible, and infrared
    radiation with a peak wave length in the visible.
    The earth is much cooler than the sun, and therefore it emits radiation
    in the infrared, which we can't see.
    What's closest to your idea about the type of radiation
    with which greenhouse gases interact?


    Dr Sara Harris: Here it is on the energy budget diagram again.
    The radiation with which greenhouse gases interact,
    is the long wave radiation coming from earth's surface.

    It's not short wave radiation coming in from the sun.
    The greenhouse effect is all about long wave infrared radiation.
    Let's talk a bit now about molecular structure of gases.
    What makes a good greenhouse gas?
    Well, a good greenhouse gas is one that can absorb and emit radiation
    within the same range of infrared wavelengths,
    as are emitted by earth's surface.
    What's your initial impression of these gases?
    The circles represent atoms and the lines are bonds between the atoms.
    Which ones might be good?


    Dr Sara Harris: One thing to consider is what kinds of vibrational motions
    a gas molecule can do.
    If a gas molecule can vibrate in a way that creates small, asymmetrical charge
    imbalances, or a little dipole-- which means that part of the molecule
    gets a slightly more positive charge and another part of the molecule
    gets a slightly more negative charge-- then
    it can absorb and emit infrared radiation.

    This is even though the molecules are electrically neutral overall.
    Molecules with two atoms both of the same element can stretch,
    so their atoms move toward and away from one another.
    But they can only stretch symmetrically.
    With symmetrical stretching, the molecule's center of mass
    stays in the same place.
    The center charge also stays in the same place.
    And no localized charge imbalances happen.
    This type of stretching does not interact with infrared radiation.
    So molecules with two atoms of the same element are not greenhouse gases.
    In our atmosphere, the most common gases are N2 and O2, two atom molecules.
    These are not greenhouse gases.
    Molecules with three atoms can also stretch symmetrically.
    And again, this type of stretching doesn't
    interact with infrared radiation.
    However, molecules with three atoms can also do other things.
    They can vibrate by stretching asymmetrically.
    And they can bend, also an asymmetrical movement.
    This type of asymmetrical motion does create localized charge imbalances,
    and these nodes of vibration do interact with infrared radiation.
    The fact that greenhouse gases can have more than one bending, stretching,
    or vibrational mode means that a single gas
    is capable of absorbing and emitting infrared radiation
    at different wavelengths.

    The particular wavelengths each gas likes
    are very specific to the chemical structure of the gas
    and which wavelengths of infrared radiation
    match the frequencies at which the molecule vibrates.
    A useful analogy is like when you push someone on a swing.
    If you add energy by pushing at the right frequency,
    the person will swing higher.
    If you push at the wrong time, you'll damp the swing's motion.
    Greenhouse gas molecules only vibrate when they get a chance encounter
    with energy of the right frequency.
    Here are examples of the two most important greenhouse gases,
    water vapor and carbon dioxide, and a couple of ways in which each of them
    can stretch and bend when they absorb and emit infrared radiation.
    With water vapor, the hydrogen atoms can stretch toward and away
    from the oxygen, or the angle between the arms of the molecule
    can change a bit as the molecule bends back and forth.
    CO2 can manage an asymmetrical stretch if the central carbon atom alternately
    gets a bit closer to one of the oxygens than a bit closer to the other.
    Or it can bend a little back and forth, forming a slight v shape.
    These are just a few examples.
    Let's take a more detailed look at what's happening in the atmosphere.
    After a greenhouse gas molecule absorbs infrared energy coming from Earth's
    surface, what happens next?
    What would happen if you just kept eating, which is gaining energy,
    but you never lost any energy?
    We lose energy, for example, as heat radiating from our bodies.
    If you did that, you'd quickly have a serious imbalance.
    Greenhouse gases have to get rid of the energy they absorb, too,
    so they emit or radiate the infrared energy away again.
    They're also constantly undergoing collisions with other gas molecules,
    gaining and losing energy that way.
    But about emission, the greenhouse gases emit radiation in random directions
    at all sorts of different angles.
    Some of the re-emitted radiation heads upward, some heads downward,
    some sideways.
    It could go in any direction.
    Some of the re-emitted radiation then encounters
    another greenhouse gas molecule, which in turn absorbs,
    then re-emits the energy, again in a random direction.
    So after potentially lots of encounters with greenhouse gas molecules,
    some of the radiation makes its way back to Earth's surface where it's absorbed.
    Since Earth's surface is absorbing radiation
    from the sun and radiation from greenhouse gases,
    the surface warms up until it can radiate the sum of those
    two sources back to the atmosphere, as we've seen.
    And in order for the whole planet to be in balance,
    the radiation leaving to outer space has to match
    the radiation coming in the top of the atmosphere
    from the sun, or else the planet will warm or cool.
    The main point of this figure is that energy may be absorbed and re-emitted
    by greenhouse gases in the atmosphere many times
    before it either leaves to outer space or gets reabsorbed
    by Earth's surface for another round.
    Notice that there are more greenhouse gas molecules nearer the surface, just
    like all the gases that are well mixed in the atmosphere.
    The atmosphere gets thinner higher up, so the higher up the energy
    makes it, the more likely it is to escape to space if it happens
    to get emitted in the right direction.
    Note also that one pathway here represents infrared radiation
    of the special infrared wavelengths that don't
    interact with any atmospheric gases.
    This radiation proceeds directly back to space.

    So again, the greenhouse gases are those that absorb
    and re-emit infrared radiation coming from Earth's surface.
    And we mentioned that greenhouse gases can
    have more than one mode of vibration, and can therefore
    absorb and emit infrared radiation at different particular wavelengths.
    This figure is a good way to look at the wavelengths each gas can interact with.
    The upper panel shows the emission spectra
    for the sun and Earth, which we've seen before.
    Those are the smooth curves.
    And the lower panels show the wavelengths at which
    different gases absorb and re-emit.
    There are a bunch of little panels, each for a different gas.
    The vertical axis for each of these lower plots
    is absorption with high absorption being up and low absorption being down.
    Based on these plots, which gas do you think would be the best greenhouse gas?
    That is, absorbs and emits the most radiation in the wavelength range
    of energy given off by Earth.


    Dr Sara Harris: Water vapor is a great greenhouse gas.
    It has a bunch of different vibrational modes,
    and it's capable of absorbing and re-emitting radiation
    at a lot of different wavelengths.
    Carbon dioxide has one major absorption band
    centered around 15 micrometers wavelength, which
    is nicely situated toward the middle of Earth's emission spectrum.
    So there are lots of those 15 micrometer photons available.
    Ozone primarily absorbs incoming ultraviolet radiation from the sun.
    You can see that on the far left side of the plot.
    But it also has an absorption band out there in the infrared.
    So at that infrared wavelength, ozone behaves as a greenhouse gas.
    And the remaining two gases, methane and nitrous oxide,
    have very particular tastes in infrared radiation and narrow absorption bands.
    The last thing to notice about this plot is that blue part of the upper panel.
    This represents those wavelengths of infrared radiation emitted by Earth
    that none of the greenhouse gases like very much.
    So those wavelengths are the ones that pass straight through the atmosphere,
    directly to space.
    That's the 40 watts per meter squared we saw on the Earth's radiation budget
    So here are some key points about the greenhouse effect.
    The greenhouse effect involves infrared radiation,
    the stuff emitted by Earth's surface, not incoming solar radiation.
    The greenhouse gases have chemical structures,
    such that they can wiggle and vibrate and absorb and re-emit
    infrared radiation.
    They re-emit it in random directions, which means the energy sticks around
    in Earth's climate system longer, and Earth's surface
    absorbs more total energy, warming it up until it's
    warm enough to emit the same amount of energy back,
    equal to the total it absorbs.
    Greenhouse gas concentrations in the atmosphere
    have been increasing, which increases the magnitude of the greenhouse effect.

    Watch and read about the water vapor feedback
    The water vapor feedback is one of the most important amplifying feedbacks in the climate system, and it’s directly related to water vapor’s role as a greenhouse gas.
    1 Here are two short readings from NASA that (among other things) describe the water vapor feedback:
    2 Alternatives to the NASA readings about the water vapor feedback:
    3 Draw for yourself a diagram of the water vapor feedback, similar to the feedback loops you’ve seen in the videos so far.

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    Water Vapor Confirmed as Major Player in Climate Change

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    The distribution of atmospheric water vapor, a significant greenhouse gas, varies across the globe. During the summer and fall of 2005, this visualization shows that most vapor collects at tropical latitudes, particularly over south Asia, where monsoon thunderstorms swept the gas some 2 miles above the land.
    Credit: NASA
    > Watch video
    Water vapor is known to be Earth’s most abundant greenhouse gas, but the extent of its contribution to global warming has been debated. Using recent NASA satellite data, researchers have estimated more precisely than ever the heat-trapping effect of water in the air, validating the role of the gas as a critical component of climate change.

    Andrew Dessler and colleagues from Texas A&M University in College Station confirmed that the heat-amplifying effect of water vapor is potent enough to double the climate warming caused by increased levels of carbon dioxide in the atmosphere.

    With new observations, the scientists confirmed experimentally what existing climate models had anticipated theoretically. The research team used novel data from the Atmospheric Infrared Sounder (AIRS) on NASA’s Aqua satellite to measure precisely the humidity throughout the lowest 10 miles of the atmosphere. That information was combined with global observations of shifts in temperature, allowing researchers to build a comprehensive picture of the interplay between water vapor, carbon dioxide, and other atmosphere-warming gases. The NASA-funded research was published recently in the American Geophysical Union's Geophysical Research Letters.

    "Everyone agrees that if you add carbon dioxide to the atmosphere, then warming will result,” Dessler said. “So the real question is, how much warming?"

    The answer can be found by estimating the magnitude of water vapor feedback. Increasing water vapor leads to warmer temperatures, which causes more water vapor to be absorbed into the air. Warming and water absorption increase in a spiraling cycle.

    Based on climate variations between 2003 and 2008, the energy trapped by water vapor is shown from southern to northern latitudes, peaking near the equator.
    Credit: Andrew Dessler
    > Larger image
    Water vapor feedback can also amplify the warming effect of other greenhouse gases, such that the warming brought about by increased carbon dioxide allows more water vapor to enter the atmosphere.

    "The difference in an atmosphere with a strong water vapor feedback and one with a weak feedback is enormous," Dessler said.

    Climate models have estimated the strength of water vapor feedback, but until now the record of water vapor data was not sophisticated enough to provide a comprehensive view of at how water vapor responds to changes in Earth's surface temperature. That's because instruments on the ground and previous space-based could not measure water vapor at all altitudes in Earth's troposphere -- the layer of the atmosphere that extends from Earth's surface to about 10 miles in altitude.

    AIRS is the first instrument to distinguish differences in the amount of water vapor at all altitudes within the troposphere. Using data from AIRS, the team observed how atmospheric water vapor reacted to shifts in surface temperatures between 2003 and 2008. By determining how humidity changed with surface temperature, the team could compute the average global strength of the water vapor feedback.

    “This new data set shows that as surface temperature increases, so does atmospheric humidity,” Dessler said. “Dumping greenhouse gases into the atmosphere makes the atmosphere more humid. And since water vapor is itself a greenhouse gas, the increase in humidity amplifies the warming from carbon dioxide."

    Specifically, the team found that if Earth warms 1.8 degrees Fahrenheit, the associated increase in water vapor will trap an extra 2 Watts of energy per square meter (about 11 square feet).

    "That number may not sound like much, but add up all of that energy over the entire Earth surface and you find that water vapor is trapping a lot of energy," Dessler said. "We now think the water vapor feedback is extraordinarily strong, capable of doubling the warming due to carbon dioxide alone."

    Because the new precise observations agree with existing assessments of water vapor's impact, researchers are more confident than ever in model predictions that Earth's leading greenhouse gas will contribute to a temperature rise of a few degrees by the end of the century.

    "This study confirms that what was predicted by the models is really happening in the atmosphere," said Eric Fetzer, an atmospheric scientist who works with AIRS data at NASA's Jet Propulsion Laboratory in Pasadena, Calif. "Water vapor is the big player in the atmosphere as far as climate is concerned."

    Related Links:

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    How Much More Will Earth Warm?
    To further explore the causes and effects of global warming and to predict future warming, scientists build climate models—computer simulations of the climate system. Climate models are designed to simulate the responses and interactions of the oceans and atmosphere, and to account for changes to the land surface, both natural and human-induced. They comply with fundamental laws of physics—conservation of energy, mass, and momentum—and account for dozens of factors that influence Earth’s climate.
    Though the models are complicated, rigorous tests with real-world data hone them into powerful tools that allow scientists to explore our understanding of climate in ways not otherwise possible. By experimenting with the models—removing greenhouse gases emitted by the burning of fossil fuels or changing the intensity of the Sun to see how each influences the climate—scientists use the models to better understand Earth’s current climate and to predict future climate.
    The models predict that as the world consumes ever more fossil fuel, greenhouse gas concentrations will continue to rise, and Earth’s average surface temperature will rise with them. Based on a range of plausible emission scenarios, average surface temperatures could rise between 2°C and 6°C by the end of the 21st century.

    Model simulations by the Intergovernmental Panel on Climate Change estimate that Earth will warm between two and six degrees Celsius over the next century, depending on how fast carbon dioxide emissions grow. Scenarios that assume that people will burn more and more fossil fuel provide the estimates in the top end of the temperature range, while scenarios that assume that greenhouse gas emissions will grow slowly give lower temperature predictions. The orange line provides an estimate of global temperatures if greenhouse gases stayed at year 2000 levels. (©2007 IPCC WG1 AR-4.)
    Climate Feedbacks
    Greenhouse gases are only part of the story when it comes to global warming. Changes to one part of the climate system can cause additional changes to the way the planet absorbs or reflects energy. These secondary changes are called climate feedbacks, and they could more than double the amount of warming caused by carbon dioxide alone. The primary feedbacks are due to snow and ice, water vapor, clouds, and the carbon cycle.
    Snow and ice
    Perhaps the most well known feedback comes from melting snow and ice in the Northern Hemisphere. Warming temperatures are already melting a growing percentage of Arctic sea ice, exposing dark ocean water during the perpetual sunlight of summer. Snow cover on land is also dwindling in many areas. In the absence of snow and ice, these areas go from having bright, sunlight-reflecting surfaces that cool the planet to having dark, sunlight-absorbing surfaces that bring more energy into the Earth system and cause more warming.

    Canada’s Athabasca Glacier has been shrinking by about 15 meters per year. In the past 125 years, the glacier has lost half its volume and has retreated more than 1.5 kilometers. As glaciers retreat, sea ice disappears, and snow melts earlier in the spring, the Earth absorbs more sunlight than it would if the reflective snow and ice remained. (Photograph ©2005 Hugh Saxby.)
    Water Vapor
    The largest feedback is water vapor. Water vapor is a strong greenhouse gas. In fact, because of its abundance in the atmosphere, water vapor causes about two-thirds of greenhouse warming, a key factor in keeping temperatures in the habitable range on Earth. But as temperatures warm, more water vapor evaporates from the surface into the atmosphere, where it can cause temperatures to climb further.
    The question that scientists ask is, how much water vapor will be in the atmosphere in a warming world? The atmosphere currently has an average equilibrium or balance between water vapor concentration and temperature. As temperatures warm, the atmosphere becomes capable of containing more water vapor, and so water vapor concentrations go up to regain equilibrium. Will that trend hold as temperatures continue to warm?
    The amount of water vapor that enters the atmosphere ultimately determines how much additional warming will occur due to the water vapor feedback. The atmosphere responds quickly to the water vapor feedback. So far, most of the atmosphere has maintained a near constant balance between temperature and water vapor concentration as temperatures have gone up in recent decades. If this trend continues, and many models say that it will, water vapor has the capacity to double the warming caused by carbon dioxide alone.
    Closely related to the water vapor feedback is the cloud feedback. Clouds cause cooling by reflecting solar energy, but they also cause warming by absorbing infrared energy (like greenhouse gases) from the surface when they are over areas that are warmer than they are. In our current climate, clouds have a cooling effect overall, but that could change in a warmer environment.

    Clouds can both cool the planet (by reflecting visible light from the sun) and warm the planet (by absorbing heat radiation emitted by the surface). On balance, clouds slightly cool the Earth. (NASA Astronaut Photograph STS31-E-9552 courtesy Johnson space Center Earth Observations Lab.)
    If clouds become brighter, or the geographical extent of bright clouds expands, they will tend to cool Earth’s surface. Clouds can become brighter if more moisture converges in a particular region or if more fine particles (aerosols) enter the air. If fewer bright clouds form, it will contribute to warming from the cloud feedback.
    See Ship Tracks South of Alaska to learn how aerosols can make clouds brighter.
    Clouds, like greenhouse gases, also absorb and re-emit infrared energy. Low, warm clouds emit more energy than high, cold clouds. However, in many parts of the world, energy emitted by low clouds can be absorbed by the abundant water vapor above them. Further, low clouds often have nearly the same temperatures as the Earth’s surface, and so emit similar amounts of infrared energy. In a world without low clouds, the amount of emitted infrared energy escaping to space would not be too different from a world with low clouds.

    Clouds emit thermal infrared (heat) radiation in proportion to their temperature, which is related to altitude. This image shows the Western Hemisphere in the thermal infrared. Warm ocean and land surface areas are white and light gray; cool, low-level clouds are medium gray; and cold, high-altitude clouds are dark gray and black. (NASA image courtesy GOES Project Science.)
    High cold clouds, however, form in a part of the atmosphere where energy-absorbing water vapor is scarce. These clouds trap (absorb) energy coming from the lower atmosphere, and emit little energy to space because of their frigid temperatures. In a world with high clouds, a significant amount of energy that would otherwise escape to space is captured in the atmosphere. As a result, global temperatures are higher than in a world without high clouds.
    If warmer temperatures result in a greater amount of high clouds, then less infrared energy will be emitted to space. In other words, more high clouds would enhance the greenhouse effect, reducing the Earth’s capability to cool and causing temperatures to warm.
    See Clouds and Radiation for a more complete description.
    Scientists aren’t entirely sure where and to what degree clouds will end up amplifying or moderating warming, but most climate models predict a slight overall positive feedback or amplification of warming due to a reduction in low cloud cover. A recent observational study found that fewer low, dense clouds formed over a region in the Pacific Ocean when temperatures warmed, suggesting a positive cloud feedback in this region as the models predicted. Such direct observational evidence is limited, however, and clouds remain the biggest source of uncertainty--apart from human choices to control greenhouse gases—in predicting how much the climate will change.
    The Carbon Cycle
    Increased atmospheric carbon dioxide concentrations and warming temperatures are causing changes in the Earth’s natural carbon cycle that also can feedback on atmospheric carbon dioxide concentration. For now, primarily ocean water, and to some extent ecosystems on land, are taking up about half of our fossil fuel and biomass burning emissions. This behavior slows global warming by decreasing the rate of atmospheric carbon dioxide increase, but that trend may not continue. Warmer ocean waters will hold less dissolved carbon, leaving more in the atmosphere.

    About half the carbon dioxide emitted into the air from burning fossil fuels dissolves in the ocean. This map shows the total amount of human-made carbon dioxide in ocean water from the surface to the sea floor. Blue areas have low amounts, while yellow regions are rich in anthropogenic carbon dioxide. High amounts occur where currents carry the carbon-dioxide-rich surface water into the ocean depths. (Map adapted from Sabine et al., 2004.)
    See The Ocean’s Carbon Balance on the Earth Observatory.
    On land, changes in the carbon cycle are more complicated. Under a warmer climate, soils, especially thawing Arctic tundra, could release trapped carbon dioxide or methane to the atmosphere. Increased fire frequency and insect infestations also release more carbon as trees burn or die and decay.
    On the other hand, extra carbon dioxide can stimulate plant growth in some ecosystems, allowing these plants to take additional carbon out of the atmosphere. However, this effect may be reduced when plant growth is limited by water, nitrogen, and temperature. This effect may also diminish as carbon dioxide increases to levels that become saturating for photosynthesis. Because of these complications, it is not clear how much additional carbon dioxide plants can take out of the atmosphere and how long they could continue to do so.
    The impact of climate change on the land carbon cycle is extremely complex, but on balance, land carbon sinks will become less efficient as plants reach saturation, where they can no longer take up additional carbon dioxide, and other limitations on growth occur, and as land starts to add more carbon to the atmosphere from warming soil, fires, and insect infestations. This will result in a faster increase in atmospheric carbon dioxide and more rapid global warming. In some climate models, carbon cycle feedbacks from both land and ocean add more than a degree Celsius to global temperatures by 2100.
    Emission Scenarios
    Scientists predict the range of likely temperature increase by running many possible future scenarios through climate models. Although some of the uncertainty in climate forecasts comes from imperfect knowledge of climate feedbacks, the most significant source of uncertainty in these predictions is that scientists don’t know what choices people will make to control greenhouse gas emissions.
    The higher estimates are made on the assumption that the entire world will continue using more and more fossil fuel per capita, a scenario scientists call “business-as-usual.” More modest estimates come from scenarios in which environmentally friendly technologies such as fuel cells, solar panels, and wind energy replace much of today’s fossil fuel combustion.
    It takes decades to centuries for Earth to fully react to increases in greenhouse gases. Carbon dioxide, among other greenhouse gases, will remain in the atmosphere long after emissions are reduced, contributing to continuing warming. In addition, as Earth has warmed, much of the excess energy has gone into heating the upper layers of the ocean. Like a hot water bottle on a cold night, the heated ocean will continue warming the lower atmosphere well after greenhouse gases have stopped increasing.
    These considerations mean that people won’t immediately see the impact of reduced greenhouse gas emissions. Even if greenhouse gas concentrations stabilized today, the planet would continue to warm by about 0.6°C over the next century because of greenhouses gases already in the atmosphere.
    See Earth’s Big Heat Bucket, Correcting Ocean Cooling, and Climate Q&A: If we immediately stopped emitting greenhouse gases, would global warming stop? to learn more about the ocean heat and global warming.
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    Dr Sara Harris: Welcome to this lesson about some basics of the carbon cycle.
    The reason we're interested in the carbon cycle
    is because carbon is a compound of carbon dioxide, which
    is an important greenhouse gas.
    And, therefore, the natural and human processes
    that influence exchanges of carbon with the atmosphere
    influence the greenhouse effect, and therefore influence earth's climate.
    The carbon cycle is complicated.
    People spend careers exploring even just pieces of it.
    Here we're going to look at the carbon cycle
    broadly within a systems dynamics framework
    and examine stocks and flows of carbon primarily to and from the atmosphere.
    In this lesson, we're going to focus on flows of carbon that are not
    directly related to human activities.
    We're going to see how much carbon moves around every year, where it goes,
    and how it gets there.
    We'll spend some time with the seasonal cycles of atmospheric carbon dioxide
    from a stock and flow perspective to get some practice with that.
    Here's a version of the carbon cycle on earth.

    To orient you, the numbers in parentheses
    indicate the number of gigatons of carbon in a particular place.
    A gigaton is a billion tons.
    So, for example, the atmosphere has about 830 billion tons of carbon in it.
    Looking at the opposite corner, the deep ocean
    has about 37,000 billion tons of carbon in it.
    That's a lot more than the atmosphere.
    All the plants on land have a mere 550 tons.
    But don't worry too much about the exact numbers.
    You'll find slightly different numbers on different versions of the carbon
    But the comparisons should be pretty similar.
    The yellow numbers are flows with units of gigatons of carbon per year.
    So, for example, photosynthesis on land takes about 120 billion tons
    of carbon out of the atmosphere every year.
    Another example, on the other side of the diagram,
    shows that the oceans released about 90 billion tons of carbon
    to the atmosphere each year.
    The red numbers are flows of carbon associated with human activities, which
    will be in a different lesson.
    So first we'll take a look at the most important processes
    by which the atmosphere exchanges carbon with biology on land.
    You're probably familiar with the basic processes
    of photosynthesis and respiration.

    During photosynthesis, plants use energy from the sun
    to combine carbon dioxide, water, and nutrients, which are
    things like nitrogen and phosphorus.
    And, in the process, they produce organic matter and release
    oxygen to the atmosphere.
    The key thing to notice is that the source of CO2 for photosynthesis
    is the atmosphere.

    That's where the plants are getting their carbon.
    When the plants respire or decay, or animals respire or decay,
    the organic matter recombines with oxygen,
    and the CO2, water, and nutrients are released along with some energy.
    This back and forth exchange is happening all the time.
    Most of the carbon that's drawn out of the atmosphere by plants each year
    goes back into the atmosphere fairly quickly.
    Just a tiny amount of organic matter gets buried every year
    and sent into long term storage in rocks.
    Notice the magnitude of the yearly exchange
    of carbon between land biology and the atmosphere.
    120 billion tons of carbon gets transferred in both directions
    each year.
    And the other big player that exchanges carbon with the atmosphere
    on fairly short timescales is the oceans.

    Gases are constantly exchanging across the boundary
    between the air and the water, going back and forth depending
    on the relative pressures of those gases in the atmosphere compared
    to the ocean.
    Some CO2 two goes into the ocean where marine plants can
    use it to photosynthesize.
    Just like biology on land, when the marine organisms die,
    they mostly decay and release the carbon back to the water.
    All of the photosynthesis in the oceans is happening close to the surface
    where there is light available.
    And much of the carbon involved in biology close to the surface
    sticks around there and gets recycled.
    But there's a leak of organic matter from the surface to the deep ocean
    as some portion of dead stuff sinks down through the water.
    And it's partly because of that leak that the deep ocean
    has a lot of carbon stored down there.
    But it doesn't stay in the deep ocean forever, because the ocean mixes.
    So circulation eventually brings carbon-rich water back
    to the surface where it exchanges with the atmosphere again.
    The mixing, though, takes several hundred to 1,000 years, approximately,
    so the deep ocean is a pretty good place to store carbon on those time scales,
    as occurred during the cold-warm climate cycles of the past million years.
    And last, notice here, too, that the oceans exchange a lot of carbon
    with the atmosphere each year, with about 90 billion tons going
    back and forth between them.
    We're going to have to add to the carbon cycle figure,
    because there are some geologic processes that
    both draw CO2 out of the atmosphere and return it to the atmosphere.

    Volcanoes add a little bit of CO2 to the atmosphere when they erupt.
    And the weathering of rocks, which involves CO2 and water,
    takes it out of the atmosphere.
    We mentioned there's a little bit of leakage of organic matter
    which gets buried every year.
    And older rocks with carbon in them get exposed each year,
    returning that carbon to the atmosphere.
    These flows are tiny compared to the massive exchanges happening
    between the atmosphere and the biosphere,
    and the atmosphere and the oceans.
    They're far less than a gigaton per year.
    One important thing to note here, which we'll get to later,
    is that we've increased the rate of flow of carbon
    from the fossil carbon pool to the atmosphere
    by extracting and burning fossil fuels.
    Another thing to note here is that geologic burial is also
    an important option to consider for mitigation efforts.
    Can we purposefully increase the flow of carbon
    into long term storage underground?
    This is another potential place to intervene.
    Now we're going to work in a little more detail with stock and flow.
    Here's the atmospheric CO2 data from Mauna Loa again showing
    the upward trend.

    But more important for us here-- the seasonal wiggles that happen.
    So what's your expectation?
    In which season do the little peaks occur?
    When do the little valleys occur?
    What do you think?

    Perturbations of the carbon cycle happen when inflows and outflows get out of balance. In this section, we’ll examine observational data linking human activities to increasing inflows of carbon to the atmosphere. Since outflows have not kept pace with inflows, the stock of atmospheric CO2 has increased. We’ll examine both recent data – from the Industrial Revolution forward – and also some older data, going back several thousand years.
    Learning Goals
    By the end of this section, you will be able to:
    1 Quantify carbon flow imbalances due to anthropogenic activities. Compare to natural sources and sinks.
    2 Evaluate chemical and mass balance evidence linking human activities to the atmospheric carbon increase in the recent past.
    3 Evaluate hypotheses regarding when human activities began to measurably alter atmospheric greenhouse gas concentrations.


    Dr Sara Harris: Welcome to this lesson about human perturbations
    of the carbon cycle.
    We're going to take a look at various lines of evidence
    and a few different data sets in order to see whether it makes sense
    that human activities have increased the carbon dioxide concentrations
    in the atmosphere recently.
    Then we're also going to take a step back
    into the slightly more distant past, thousands of years ago,
    and look at some data regarding when our activities might
    have begun to measurably change the composition of the atmosphere.
    We do a bunch of things that perturb the carbon cycle, most of which
    involve adding carbon to the atmosphere.
    We've mentioned these things before.
    They're things like burning fossil fuels,
    clearing previously forested land for agriculture or other uses,
    and making cement.
    How much carbon do these things add up to?
    Well, here are some data that are based on historical records, records
    of land use change, fossil fuel extraction and sales and cement making.

    People have been keeping records of these things over time
    and this is data that compiles available information back to 1850.
    Some of the data is based on written records
    and some also incorporates direct observations,
    like satellite data which started in the 1970s and added to the information
    available about land use change, for example.
    You can see that our annual emissions have generally
    gone up over this time period from something around half
    a billion tons of carbon per year to around 10 billion more recently.
    And if we add up all the carbon emissions over this time period
    based on our own records and observations,
    we've emitted somewhere around 540 billion tons of carbon
    to the atmosphere.
    Now given the volume of the atmosphere and the concentrations of molecules
    in it, it turns out that it takes about 2.1 billion tons of carbon
    to increase atmospheric carbon dioxide by about one part per million.
    So if all of this 540 billion tons of carbon went into the atmosphere
    as CO2, which most of it does, and if it all stayed there,
    the atmospheric carbon dioxide concentration in the atmosphere
    should have increased by 540 divided by 2.1,
    which is about 257 parts per million.

    Fortunately, the carbon dioxide concentration
    didn't rise by 257 parts per million since 1850.
    Instead it rose by about 110 parts per million.
    That's the green line with the axis on the right.
    Which means that not all the carbon we emit stays in the atmosphere,
    but certainly some of it does stay each year.
    So here we have another imbalance of flows.
    We have a known inflow from historical records of human activities.
    We have a measured stock, which is the atmospheric carbon dioxide.
    And there has to be an outflow somewhere because the stock didn't increase
    as much as the inflow would imply.
    And it turns out that the outflow is carbon going into plants and soils
    on land and into the ocean.
    Let's just take a recent number for human emissions of carbon
    to the atmosphere, about nine billion tons in a year.
    The data we just looked at tell us that not all of it stays in the atmosphere.
    We also saw earlier that the land exchanges
    about 120 billion tons of carbon back and forth
    with the atmosphere each year.
    But in addition to that exchange, it's taking up an extra three billion tons
    of carbon every year.
    The oceans are doing their part too by taking up an extra two billion tons
    or so of carbon every year.
    That extra CO2 is also helping lower the pH of the ocean,
    contributing to ocean acidification.
    So we have outflows, but we have a flow imbalance.
    If the land and oceans were taking up all nine of those gigatons
    we released, then the flows would be in balance
    and the stock of carbon dioxide in the atmosphere wouldn't change.
    But that hasn't happened.
    Here's a question for you.
    Based on these numbers, approximately what percentage
    of human carbon emissions stays in the atmosphere each year?
    Choose is the closest answer.


    Dr Sara Harris: So of the nine billion tons of inflow, five flow out--
    three to land and two to the oceans.
    So four billion tons stays in the atmosphere.
    That's about 45% of the nine billion tons of emissions.
    That percentage seems to have been fairly stable over time.
    If, for example, we go back to our cumulative carbon emissions, which
    would have produced a rise in CO2 of 257 parts per million, but instead
    it only rose by 110 parts per million.
    That's, again, around 45%.
    Whether the land and ocean will continue to absorb 55% of our emissions
    in the future is an open question.
    Most projections suggest that land and ocean uptake will slow down,
    assuming that emissions continue unabated,
    and therefore, a larger percentage of emissions each year
    will stay in the atmosphere in the future.
    So up until now, we looked at inflows to the atmosphere
    from known human activities and outflows to the land and oceans,
    and the resulting change in carbon stock in the atmosphere.
    But what if there were some other source of carbon that we're not considering?
    Is there some other line of evidence that would help?
    Let's look at some chemistry data.
    This is another approach, and this one helps
    us identify the source of the carbon.
    If you think back to chemistry, which might or might not
    be too far in the past, you'll remember that most carbon
    atoms have an atomic mass of about 12.
    The vast majority of carbon in the world is carbon-12.
    But there's some carbon out there that has
    an extra neutron, which means it's just a little bit heavier, even though it's
    still carbon.
    This is carbon-13, which is another stable isotope of carbon.
    And only about 1% or so of the carbon here is carbon-13.
    I'm sure you've also heard carbon-14.
    That one's radioactive and, interestingly, also
    provides a chemical line of evidence for us to explore,
    regarding the source of the atmosphere of CO2 increase.
    But we're going focus on carbon-12 and -13 here.
    The CO2 in the atmosphere can have a carbon-12 as its carbon atom,
    or it can have a carbon-13.
    And we can measure the ratio of carbon-13
    to carbon-12 in different samples from the atmosphere,
    or in plants, or in rocks.

    And it turns out that these have different ratios of these isotopes.
    For reference, we consider a sample to be, quote,
    "heavy" if it has a relatively high ratio of carbon-13 to carbon-12.
    The heavy one is on the top of the fraction.
    And we consider a sample to be "light" if it has a relatively low ratio.
    OK, here's a question to practice with carbon isotopes.
    We learned that plants get their carbon from the atmosphere.
    And here, I'm adding the information that plants
    prefer carbon-12 over carbon-13, because it takes less energy to use carbon-12.
    Which of these do you think has the lighter
    ratio of carbon-13 to carbon-12?
    We can measure the ratio in plants and we can measure it in the atmosphere.
    How do they compare?


    Dr Sara Harris: So plants are selectively taking up more C12 than C13
    compared to what's available to them.
    So they end up with a lighter value for this ratio.
    The atmosphere is, therefore, heavier isotopically than plants.
    So why does this matter?
    Well, human emissions of carbon are largely from plants.
    There's land-use change, like deforestation,
    which returns carbon previously stored in plants back to the atmosphere.
    But the big one is, of course, burning fossil fuels.
    Fossil fuels are ancient organic material.
    They used to be plants.
    So fossil fuels have isotopic ratios that are also light.
    What would we expect to happen over time to the carbon in the atmosphere
    if, through human activities, we were adding more and more light carbon?
    Here are the data.
    Over time, the carbon in CO2 in the atmosphere
    has been getting lighter and lighter.

    These data show that trend since 1980.
    You can ignore the fancy units on the vertical axis.
    The key thing here is that more negative values, which are down,
    are lighter than less negative values.
    This is the pattern we'd expect from burning fossil fuels
    and changing forested land to agricultural land.
    And the actual change in the values over time
    matches well with the amounts of light carbon that we know we've emitted.
    And here's an additional piece of chemistry data
    that aligns with the stock and flow data and the carbon isotope data.
    When we burn fossil fuel or wood, we're oxidizing organic carbon,
    releasing energy, and ending up with carbon dioxide.

    To oxidize takes oxygen, in most cases anyway.
    So we'd expect to see atmospheric oxygen go down over time, too,
    which is what we see.
    That's the purple line.
    It's nothing to really worry about because we're not
    going to run out of oxygen. It's just another chemical indicator
    that fossil fuel burning and land-use change
    are the source of the increase in atmospheric carbon dioxide.
    So we have solid evidence that human activities have
    altered the composition of the atmosphere and, in particular,
    have added CO2, which as a greenhouse gas, increases the greenhouse effect.
    But when did we start our atmosphere-altering activities?
    A compelling idea, which comes from climate scientist Bill Ruddiman,

    suggests that we've been doing this for thousands of years.
    Here's the carbon dioxide data going back 11,000 years.
    The world had just warmed up after the recent ice age.
    If we look at what happened when Earth came out of other ice ages
    over the past million years, it looks like,
    for those other times in the past, atmospheric CO2 peaks and then
    declines, as shown in the blue line on the plot.
    But not this time around.
    About 8,000 years ago, CO2 reversed direction and started to climb again.
    This timing corresponds to when humans started and continued
    clearing forested land for agriculture, which
    would release CO2 to the atmosphere.
    It's certainly nothing like the rate of rise in CO2
    since the Industrial Revolution, which is shown in the upper right,
    but it is an unexpected rise nonetheless.
    Atmospheric concentrations of methane exhibit quite a similar pattern
    with an anomalous rise starting about 5,000 years ago.
    Again, based on observations from past climate cycles,
    we'd expect methane to decline further, as shown by the green line.
    But it increases instead.
    And this timing happens to correspond well with the initiation and expansion
    of irrigation for rice farming, which forms artificial wetlands, which
    produce methane.
    So the main points from this lesson are that our own records of emissions
    align well with measurements of carbon dioxide concentrations
    over time and with chemical evidence from carbon isotopes and oxygen.

    These records link human activities to the recent increase
    in greenhouse gas concentrations.
    The land and the ocean take up the extra carbon back out of the atmosphere
    but not all of it.
    About 45% stays in the atmosphere.
    And there's compelling evidence that we've
    been altering atmospheric composition for several thousand years,
    though the large and fast changes have happened since the Industrial

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    Changes in the Carbon Cycle
    Left unperturbed, the fast and slow carbon cycles maintain a relatively steady concentration of carbon in the atmosphere, land, plants, and ocean. But when anything changes the amount of carbon in one reservoir, the effect ripples through the others.
    In Earth’s past, the carbon cycle has changed in response to climate change. Variations in Earth’s orbit alter the amount of energy Earth receives from the Sun and leads to a cycle of ice ages and warm periods like Earth’s current climate. (See Milutin Milankovitch.) Ice ages developed when Northern Hemisphere summers cooled and ice built up on land, which in turn slowed the carbon cycle. Meanwhile, a number of factors including cooler temperatures and increased phytoplankton growth may have increased the amount of carbon the ocean took out of the atmosphere. The drop in atmospheric carbon caused additional cooling. Similarly, at the end of the last Ice Age, 10,000 years ago, carbon dioxide in the atmosphere rose dramatically as temperatures warmed.

    Levels of carbon dioxide in the atmosphere have corresponded closely with temperature over the past 800,000 years. Although the temperature changes were touched off by variations in Earth’s orbit, the increased global temperatures released CO2 into the atmosphere, which in turn warmed the Earth. Antarctic ice-core data show the long-term correlation until about 1900. (Graphs by Robert Simmon, using data from Lüthi et al., 2008, and Jouzel et al., 2007.)
    Shifts in Earth’s orbit are happening constantly, in predictable cycles. In about 30,000 years, Earth’s orbit will have changed enough to reduce sunlight in the Northern Hemisphere to the levels that led to the last ice age.
    Today, changes in the carbon cycle are happening because of people. We perturb the carbon cycle by burning fossil fuels and clearing land.
    When we clear forests, we remove a dense growth of plants that had stored carbon in wood, stems, and leaves—biomass. By removing a forest, we eliminate plants that would otherwise take carbon out of the atmosphere as they grow. We tend to replace the dense growth with crops or pasture, which store less carbon. We also expose soil that vents carbon from decayed plant matter into the atmosphere. Humans are currently emitting just under a billion tons of carbon into the atmosphere per year through land use changes.

    The burning of fossil fuels is the primary source of increased carbon dioxide in the atmosphere today. (Photograph ©2009 stevendepolo.)
    Without human interference, the carbon in fossil fuels would leak slowly into the atmosphere through volcanic activity over millions of years in the slow carbon cycle. By burning coal, oil, and natural gas, we accelerate the process, releasing vast amounts of carbon (carbon that took millions of years to accumulate) into the atmosphere every year. By doing so, we move the carbon from the slow cycle to the fast cycle. In 2009, humans released about 8.4 billion tons of carbon into the atmosphere by burning fossil fuel.

    Emissions of carbon dioxide by humanity (primarily from the burning of fossil fuels, with a contribution from cement production) have been growing steadily since the onset of the industrial revolution. About half of these emissions are removed by the fast carbon cycle each year, the rest remain in the atmosphere. (Graph by Robert Simmon, using data from the Carbon Dioxide Information Analysis Center and Global Carbon Project.)

    Effects of Changing the Carbon Cycle
    All of this extra carbon needs to go somewhere. So far, land plants and the ocean have taken up about 55 percent of the extra carbon people have put into the atmosphere while about 45 percent has stayed in the atmosphere. Eventually, the land and oceans will take up most of the extra carbon dioxide, but as much as 20 percent may remain in the atmosphere for many thousands of years.
    The changes in the carbon cycle impact each reservoir. Excess carbon in the atmosphere warms the planet and helps plants on land grow more. Excess carbon in the ocean makes the water more acidic, putting marine life in danger.
    It is significant that so much carbon dioxide stays in the atmosphere because CO2 is the most important gas for controlling Earth’s temperature. Carbon dioxide, methane, and halocarbons are greenhouse gases that absorb a wide range of energy—including infrared energy (heat) emitted by the Earth—and then re-emit it. The re-emitted energy travels out in all directions, but some returns to Earth, where it heats the surface. Without greenhouse gases, Earth would be a frozen -18 degrees Celsius (0 degrees Fahrenheit). With too many greenhouse gases, Earth would be like Venus, where the greenhouse atmosphere keeps temperatures around 400 degrees Celsius (750 Fahrenheit).

    Rising concentrations of carbon dioxide are warming the atmosphere. The increased temperature results in higher evaporation rates and a wetter atmosphere, which leads to a vicious cycle of further warming. (Photograph ©2011 Patrick Wilken.)
    Because scientists know which wavelengths of energy each greenhouse gas absorbs, and the concentration of the gases in the atmosphere, they can calculate how much each gas contributes to warming the planet. Carbon dioxide causes about 20 percent of Earth’s greenhouse effect; water vapor accounts for about 50 percent; and clouds account for 25 percent. The rest is caused by small particles (aerosols) and minor greenhouse gases like methane.
    Water vapor concentrations in the air are controlled by Earth’s temperature. Warmer temperatures evaporate more water from the oceans, expand air masses, and lead to higher humidity. Cooling causes water vapor to condense and fall out as rain, sleet, or snow.
    Carbon dioxide, on the other hand, remains a gas at a wider range of atmospheric temperatures than water. Carbon dioxide molecules provide the initial greenhouse heating needed to maintain water vapor concentrations. When carbon dioxide concentrations drop, Earth cools, some water vapor falls out of the atmosphere, and the greenhouse warming caused by water vapor drops. Likewise, when carbon dioxide concentrations rise, air temperatures go up, and more water vapor evaporates into the atmosphere—which then amplifies greenhouse heating.
    So while carbon dioxide contributes less to the overall greenhouse effect than water vapor, scientists have found that carbon dioxide is the gas that sets the temperature. Carbon dioxide controls the amount of water vapor in the atmosphere and thus the size of the greenhouse effect.
    Rising carbon dioxide concentrations are already causing the planet to heat up. At the same time that greenhouse gases have been increasing, average global temperatures have risen 0.8 degrees Celsius (1.4 degrees Fahrenheit) since 1880.

    With the seasonal cycle removed, the atmospheric carbon dioxide concentration measured at Mauna Loa Volcano, Hawaii, shows a steady increase since 1957. At the same time global average temperatures are rising as a result of heat trapped by the additional CO2 and increased water vapor concentration. (Graphs by Robert Simmon, using CO2 data from the NOAA Earth System Research Laboratory and temperature data from the Goddard Institute for Space Studies.)
    This rise in temperature isn’t all the warming we will see based on current carbon dioxide concentrations. Greenhouse warming doesn’t happen right away because the ocean soaks up heat. This means that Earth’s temperature will increase at least another 0.6 degrees Celsius (1 degree Fahrenheit) because of carbon dioxide already in the atmosphere. The degree to which temperatures go up beyond that depends in part on how much more carbon humans release into the atmosphere in the future.
    About 30 percent of the carbon dioxide that people have put into the atmosphere has diffused into the ocean through the direct chemical exchange. Dissolving carbon dioxide in the ocean creates carbonic acid, which increases the acidity of the water. Or rather, a slightly alkaline ocean becomes a little less alkaline. Since 1750, the pH of the ocean’s surface has dropped by 0.1, a 30 percent change in acidity.

    Some of the excess CO2 emitted by human activity dissolves in the ocean, becoming carbonic acid. Increases in carbon dioxide are not only leading to warmer oceans, but also to more acidic oceans. (Photograph ©2010 Way Out West News.)
    Ocean acidification affects marine organisms in two ways. First, carbonic acid reacts with carbonate ions in the water to form bicarbonate. However, those same carbonate ions are what shell-building animals like coral need to create calcium carbonate shells. With less carbonate available, the animals need to expend more energy to build their shells. As a result, the shells end up being thinner and more fragile.
    Second, the more acidic water is, the better it dissolves calcium carbonate. In the long run, this reaction will allow the ocean to soak up excess carbon dioxide because more acidic water will dissolve more rock, release more carbonate ions, and increase the ocean’s capacity to absorb carbon dioxide. In the meantime, though, more acidic water will dissolve the carbonate shells of marine organisms, making them pitted and weak.
    Warmer oceans—a product of the greenhouse effect—could also decrease the abundance of phytoplankton, which grow better in cool, nutrient-rich waters. This could limit the ocean’s ability to take carbon from the atmosphere through the fast carbon cycle.
    On the other hand, carbon dioxide is essential for plant and phytoplankton growth. An increase in carbon dioxide could increase growth by fertilizing those few species of phytoplankton and ocean plants (like sea grasses) that take carbon dioxide directly from the water. However, most species are not helped by the increased availability of carbon dioxide.
    Plants on land have taken up approximately 25 percent of the carbon dioxide that humans have put into the atmosphere. The amount of carbon that plants take up varies greatly from year to year, but in general, the world’s plants have increased the amount of carbon dioxide they absorb since 1960. Only some of this increase occurred as a direct result of fossil fuel emissions.
    With more atmospheric carbon dioxide available to convert to plant matter in photosynthesis, plants were able to grow more. This increased growth is referred to as carbon fertilization. Models predict that plants might grow anywhere from 12 to 76 percent more if atmospheric carbon dioxide is doubled, as long as nothing else, like water shortages, limits their growth. However, scientists don’t know how much carbon dioxide is increasing plant growth in the real world, because plants need more than carbon dioxide to grow.
    Plants also need water, sunlight, and nutrients, especially nitrogen. If a plant doesn’t have one of these things, it won’t grow regardless of how abundant the other necessities are. There is a limit to how much carbon plants can take out of the atmosphere, and that limit varies from region to region. So far, it appears that carbon dioxide fertilization increases plant growth until the plant reaches a limit in the amount of water or nitrogen available.
    Some of the changes in carbon absorption are the result of land use decisions. Agriculture has become much more intensive, so we can grow more food on less land. In high and mid-latitudes, abandoned farmland is reverting to forest, and these forests store much more carbon, both in wood and soil, than crops would. In many places, we prevent plant carbon from entering the atmosphere by extinguishing wildfires. This allows woody material (which stores carbon) to build up. All of these land use decisions are helping plants absorb human-released carbon in the Northern Hemisphere.

    Changes in land cover—forests converted to fields and fields converted to forests—have a corresponding effect on the carbon cycle. In some Northern Hemisphere countries, many farms were abandoned in the early 20th century and the land reverted to forest. As a result, carbon was drawn out of the atmosphere and stored in trees on land. (Photograph ©2007 Husein Kadribegic.)
    In the tropics, however, forests are being removed, often through fire, and this releases carbon dioxide. As of 2008, deforestation accounted for about 12 percent of all human carbon dioxide emissions.
    The biggest changes in the land carbon cycle are likely to come because of climate change. Carbon dioxide increases temperatures, extending the growing season and increasing humidity. Both factors have led to some additional plant growth. However, warmer temperatures also stress plants. With a longer, warmer growing season, plants need more water to survive. Scientists are already seeing evidence that plants in the Northern Hemisphere slow their growth in the summer because of warm temperatures and water shortages.
    Dry, water-stressed plants are also more susceptible to fire and insects when growing seasons become longer. In the far north, where an increase in temperature has the greatest impact, the forests have already started to burn more, releasing carbon from the plants and the soil into the atmosphere. Tropical forests may also be extremely susceptible to drying. With less water, tropical trees slow their growth and take up less carbon, or die and release their stored carbon to the atmosphere.
    The warming caused by rising greenhouse gases may also “bake” the soil, accelerating the rate at which carbon seeps out in some places. This is of particular concern in the far north, where frozen soil—permafrost—is thawing. Permafrost contains rich deposits of carbon from plant matter that has accumulated for thousands of years because the cold slows decay. When the soil warms, the organic matter decays and carbon—in the form of methane and carbon dioxide—seeps into the atmosphere.
    Current research estimates that permafrost in the Northern Hemisphere holds 1,672 billion tons (Petagrams) of organic carbon. If just 10 percent of this permafrost were to thaw, it could release enough extra carbon dioxide to the atmosphere to raise temperatures an additional 0.7 degrees Celsius (1.3 degrees Fahrenheit) by 2100.

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    Studying the Carbon Cycle
    Many of the questions scientists still need to answer about the carbon cycle revolve around how it is changing. The atmosphere now contains more carbon than at any time in at least two million years. Each reservoir of the cycle will change as this carbon makes its way through the cycle.
    What will those changes look like? What will happen to plants as temperatures increase and climate changes? Will they remove more carbon from the atmosphere than they put back? Will they become less productive? How much extra carbon will melting permafrost put into the atmosphere, and how much will that amplify warming? Will ocean circulation or warming change the rate at which the ocean takes up carbon? Will ocean life become less productive? How much will the ocean acidify, and what effects will that have?

    Time series of satellite data, like the imagery available from the Landsat satellites, allow scientists to monitor changes in forest cover. Deforestation can release carbon dioxide into the atmosphere, while forest regrowth removes CO2. This pair of false-color images shows clear cutting and forest regrowth between 1984 and 2010 in Washington State, northeast of Mount Rainier. Dark green corresponds to mature forests, red indicates bare ground or dead plant material (freshly cut areas), and light green indicates relatively new growth. (NASA image by Robert Simmon, using Landsat data from the USGS Global Visualization Viewer.)
    NASA’s role in answering these questions is to provide global satellite observations and related field observations. As of early 2011, two types of satellite instruments were collecting information relevant to the carbon cycle.
    The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, flying on NASA’s Terra and Aqua satellites, measure the amount of carbon plants and phytoplankton turn into matter as they grow, a measurement called net primary productivity. The MODIS sensors also measure how many fires occur and where they burn.
    Two Landsat satellites provide a detailed view of ocean reefs, what is growing on land, and how land cover is changing. It is possible to see the growth of a city or a transformation from forest to farm. This information is crucial because land use accounts for one-third of all human carbon emissions.
    Future NASA satellites will continue these observations, and also measure carbon dioxide and methane in the atmosphere and vegetation height and structure.
    All of these measurements will help us see how the global carbon cycle is changing through time. They will help us gauge the impact we are having on the carbon cycle by releasing carbon into the atmosphere or finding ways to store it elsewhere. They will show us how our changing climate is altering the carbon cycle, and how the changing carbon cycle is altering our climate.
    Most of us, however, will observe changes in the carbon cycle in a more personal way. For us, the carbon cycle is the food we eat, the electricity in our homes, the gas in our cars, and the weather over our heads. We are a part of the carbon cycle, and so our decisions about how we live ripple across the cycle. Likewise, changes in the carbon cycle will impact the way we live. As each of us come to understand our role in the carbon cycle, the knowledge empowers us to control our personal impact and to understand the changes we are seeing in the world around us.
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    The Anthropogenic Greenhouse Era Began Thousands of Years Ago
    William F. Ruddiman

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    The anthropogenic era is generally thought to have begun 150 to 200 years ago, when the industrial revolution began producing CO2 andCH4 at rates sufficient to alter their compositions in the atmosphere. A different hypothesis is posed here: anthropogenic emissions of these gases first altered atmospheric concentrations thousands of years ago. This hypothesis is based on three arguments. (1) Cyclic variations in CO2 andCH4 driven by Earth-orbital changes during the last 350,000 years predict decreases throughout the Holocene, but the CO2 trend began ananomalous increase 8000 years ago, and the CH4 trend did so 5000 years ago.(2) Published explanations for these mid- to late-Holocene gas increases basedon natural forcing can be rejected based on paleoclimatic evidence. (3) A wide array of archeological, cultural, historical and geologic evidence points to viable explanations tied to anthropogenic changes resulting from early agriculture in Eurasia, including the start of forest clearance by 8000 years ago and of rice irrigation by 5000 years ago. In recent millennia, the estimated warming caused by these early gas emissions reached a global-mean value of ∼ 0.8 °C and roughly 2 °C at high latitudes, large enough to have stopped a glaciation of northeastern Canada predicted by two kinds of climatic models. CO2 oscillations of ∼ 10 ppm in the last 1000 years are toolarge to be explained by external (solar-volcanic) forcing, but they can be explained by outbreaks of bubonic plague that caused historically documented farm abandonment in western Eurasia. Forest regrowth on abandoned farms sequestered enough carbon to account for the observed CO2decreases. Plague-driven CO2 changes were also a significant causal factor in temperature changes during the Little Ice Age (1300–1900 AD).

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    Dr Sara Harris: Welcome to this next lesson.
    This one is about carbon cycle responses to human perturbations.
    We've seen that human activities perturb the carbon cycle.
    In this lesson, we're going to think through some of the possible carbon
    cycle responses to those perturbations.
    We'll look at a couple of feedbacks, and we'll also
    think about how Earth's climate system will respond in the long-term, what's
    likely to happen to the concentration of atmospheric CO2,
    and how long is that going to take.
    In lab experiments, people have shown that when
    plants grow under conditions with higher carbon dioxide in the air
    they grow more.
    So if they grow more, they take up more CO2 from the atmosphere
    and store it in plants, which in turn decreases the stock of atmospheric CO2.
    This is called the CO2 fertilization effect,
    and it's a stabilizing feedback, a response to increased CO2
    that pushes the system in the opposite direction
    from the initial perturbation.
    However, in natural ecosystems, it's unclear
    how large this effect really is.
    Plants also depend on water availability and nutrient
    availability for their growth.
    So in a warmer, high CO2 world, changes to water and nutrients
    might actually limit plant growth, regardless of the CO2 fertilization
    An interesting carbon cycle feedback has been happening
    in our area in Western Canada.
    Warmer temperatures around here mean that there
    are fewer hard frosts in the wintertime, which
    means that greater populations of this little critter
    called the mountain pine beetle survive through the winter.
    The life cycle of the mountain pine needle
    involves chewing the inner bark of pine trees.
    And if there are enough beetles in a tree, then they can kill it.
    Here you can see some of the pine trees in British Columbia that have
    been fairly recently killed by beetles.
    And in fact, vast swaths of the forest in this province
    have been killed by beetles in recent decades.
    So here's a question to try.
    Complete this feedback loop.
    Then decide if you think it's an amplifying feedback or a stabilizing


    Dr Sara Harris: So more beetles kill more trees.
    These dead trees now release CO2 as they decay,
    transferring their carbon from the forest stock back to the atmosphere
    So this kind of feedback can actually add CO2 to the atmosphere
    and limit the global ability of the land biosphere to take up excess CO2.
    Another potentially amplifying feedback involves forest fires.
    With increased CO2, some places experience both warmer temperatures
    and also more severe, longer periods of drought.
    Drought plus warmer summer temperatures are pretty good conditions
    for forest fires.
    And when the forests burn, the carbon is released to the atmosphere amplifying
    that perturbation.
    Of course not all regions are expected to get warmer and drier,
    and this effect looks like it's mostly prevalent at mid latitudes.
    The forest fire shown here is actually one
    that people deliberately set in Western Alberta, partly in fact
    to try to slow the spread of the mountain pine beetle.
    So those are a few vegetation-related feedbacks in the carbon cycle.
    Some likely responses to increased CO2 in the atmosphere.
    There are others, including things like soil bacteria, which
    are more active in warmer soils, and so risk fire more,
    which releases more CO2.
    But this affect also depends on how wet or dry the soils are.
    It looks likely in a future world with higher
    CO2 that the net feedbacks involving land biology are amplifying feedbacks,
    pushing the climate system toward higher atmospheric CO2 in response
    to the increase in atmospheric CO2.
    Here's another feedback you've probably heard something about.
    There's a lot of methane and carbon dioxide
    stored in permafrost, which are frozen soils located mostly at high latitudes.

    We've seen before that recent warming has been larger
    in regions near the poles than it has been at lower latitude.
    And this warming increases the thawing of permafrost
    and releases carbon dioxide and methane that's been stored there.
    You can see this is another amplifying feedback.
    There's also a lot of methane and CO2 stored
    in these icy hydrates in marine sediments under the ocean water.
    So as the oceans warm, if these thaw, that's another potentially large source
    of greenhouse gases to the atmosphere and would be another amplifying
    feedback in the carbon cycle.
    So we're in a situation where atmospheric CO2 is rising rapidly,
    but that spike won't last forever.
    Natural processes will eventually draw the CO2 back out of the atmosphere
    and stabilize CO2 concentrations.
    We've seen that some of the excess is currently
    going into land, plants, and soils, and into the oceans.
    But here's a little chemistry.
    When CO2 goes into the ocean, it reacts with water
    and makes the water more acidic.
    The equation listed here shows that this process ends up
    using some of what's called the carbonate ion, which is the CO32minus.
    This equation shown is actually the sum of a bunch of chemical reactions
    that are happening.
    The deal is that fewer carbonate ions correspond to more acidic water,
    for reasons we're really not going to get into.
    The point here is that the carbonate ion is
    getting used up as more CO2 goes into the ocean,
    but it can get replaced by pretty readily available materials.
    Many marine organisms make shells out of calcium carbonate, that's the CAC03,
    like the white, popcorn-looking thing here.
    And when that stuff dissolves, it releases more carbonate ion,
    replacing some that was used up.
    So dissolving things made of calcium carbonate like dead shells
    from marine organisms, helps buffer ocean pH
    and keeps it from getting too acidic.
    If you've ever taken an antaci for indigestion,
    it's kind of the same thing.
    Another source of calcium carbonate is from limestone rocks on land
    like the White Cliffs of Dover shown here.
    These rocks on land also dissolve and the dissolved carbonate ion
    washes into the ocean and helps buffer the pH, too.
    In the fairly near term geologically speaking,
    the extra CO2 that's going into the oceans today
    is going to react with sediments and rocks made of calcium carbonate.
    These are eventually going to neutralize the acidifying
    effects of CO2 in the ocean, but it's going to take several thousand years.
    Another even a longer-term process is what
    will eventually bring the atmospheric CO2 back to some equilibrium value.
    This is the weathering of silicate rocks on land, rocks like granite or basalt,
    if you've ever heard of those kinds of rocks.
    CO2 in the atmosphere combines with water to form slightly acidic rain.
    The slightly acidic rainwater then helps dissolve rocks on land.
    The dissolved chemicals in the rocks plus the CO2 in water
    end up flowing off the land into the where marine critters use
    those dissolved parts to make shells.
    Some of these shells end up buried in sediments on the bottom of the ocean,
    effectively returning the carbon to longer-term storage.
    There's a bunch of chemistry that's not shown here,
    but the main point is the dissolving silicate rocks on land
    takes CO2 out of the atmosphere.
    This is a slow process.
    It's going to take a couple thousand years to draw down
    the current spike in atmospheric CO2.
    Here's an example from the past to illustrate that last point.
    About at 55 million years ago something happened
    that perturbed the carbon cycle, and atmospheric CO2 increased fast.
    Global temperatures went up, the ocean got
    acidic, lots of shells of marine organisms dissolved,
    and a bunch of things went extinct.
    This event is called the Paleocene Eocene Thermal Maximum
    if you want to look up more information about it.
    What's shown here is 2 million years of data with this event in the middle.
    Time runs from left to right.
    The blue line represents deep ocean temperature,
    and you can see that at about 55 million years ago temperatures went up fast.
    This timing corresponds to a rapid change in carbon isotopes in the ocean.
    We've looked at carbon isotopes once before,
    and these are now plotted so that the lighter isotopic values are up
    on the axis.
    So what's going on is at the same time as temperature went up,
    a big slug of isotopically light carbon got released from somewhere,
    and it happened pretty fast.
    It's kind of like what's going on today.
    We're not quite sure how fast this event unfolded.
    The rapid increase might have happened over a few thousand years,
    maybe up to about 20,000 years, but what we can tell from this example
    is that recovery was pretty slow.
    At least it was slow on human kinds of time scales.
    The oceans took up a lot of the excess CO2.
    Carbonates slowly dissolved to neutralize the acid.
    And eventually the really slow process of silicate weathering
    brought things back close to the previous baseline.
    And if you look at these data, you'll see
    that the recovery back to something we could consider baseline
    took a couple hundred thousand years.
    Our current perturbation of the carbon cycle
    may have a similarly lengthy recovery time.
    So we've seen a few feedbacks initiated by increases in atmospheric CO2
    that involve carbon on land.
    Most of these turn out to be amplifying feedbacks,
    pushing the climate system toward higher atmospheric CO2, which is
    the same direction as the perturbation.
    And we've had a look at what's likely to happen over
    the long term to the carbon we emit to the atmosphere today.
    The oceans will absorb some, which will gradually
    get neutralized by dissolving carbonate rocks in the sediments.
    And eventually the process of weathering silicate rocks on land
    will draw atmospheric CO2 back to equilibrium.
    This carbon is going to be with us for a while,
    unless of course, we start actively removing it from the atmosphere.

    "Tipping elements' in the climate system
    Read Tipping elements in the Earth’s climate system by Lenton et al., 2008 (Proceedings of the National Academy of Sciences of the USA, vol 105, no 6, p 1786-1793). If you’re not likely to read the full paper, then focus your attention on the sub-section “Policy-relevant Tipping Elements in the Climate System”. Read through the sub-sections here titled “Arctic Sea Ice”, “Greenland Ice Sheet”, etc.
    How do Lenton et al. define “tipping element”?
    Which of these tipping elements do you think poses the greatest threat to humanity?
    Lenton et al. identify a list of tipping elements as “policy-relevant”. In what ways do you think policymakers could use information similar to that presented in this paper? You could consider this question broadly, or in detail.
    Here’s the link to the PDF version, and here’s the link to the html version.

    Tipping elements in the Earth’s climate system
    Timothy M. Lenton*†, Hermann Held‡, Elmar Kriegler‡§, Jim W. Hall¶, Wolfgang Lucht‡, Stefan Rahmstorf‡,
    and Hans Joachim Schellnhuber†‡􏰀**
    *School of Environmental Sciences, University of East Anglia, and Tyndall Centre for Climate Change Research, Norwich NR4 7TJ, United Kingdom; ‡Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412 Potsdam, Germany; §Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213-3890; ¶School of Civil Engineering and Geosciences, Newcastle University, and Tyndall Centre for Climate Change Research, Newcastle NE1 7RU, United Kingdom; and 􏰀Environmental Change Institute, Oxford University, and Tyndall Centre for Climate Change Research, Oxford OX1 3QY, United Kingdom
    **This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected on May 3, 2005. Edited by William C. Clark, Harvard University, Cambridge, MA, and approved November 21, 2007 (received for review June 8, 2007)
    The term ‘‘tipping point’’ commonly refers to a critical threshold at which a tiny perturbation can qualitatively alter the state or development of a system. Here we introduce the term ‘‘tipping element’’ to describe large-scale components of the Earth system that may pass a tipping point. We critically evaluate potential policy-relevant tipping elements in the climate system under anthropogenic forcing, drawing on the pertinent literature and a recent international workshop to compile a short list, and we assess where their tipping points lie. An expert elicitation is used to help rank their sensitivity to global warming and the uncertainty about the underlying physical mechanisms. Then we explain how, in principle, early warning systems could be established to detect the proximity of some tipping points.
    Earth system 􏰁 tipping points 􏰁 climate change 􏰁 large-scale impacts 􏰁 climate policy
    Human activities may have the potential to push com- ponents of the Earth system past critical states into qualitatively different modes of operation, implying large-scale impacts on human and ecological systems. Examples that have received recent attention include the po- tential collapse of the Atlantic thermohaline circulation (THC) (1), dieback of the Amazon rainforest (2), and decay of the Greenland ice sheet (3). Such phenomena have been described as ‘‘tipping points’’ following the popular notion that, at a particular moment in time, a small change can have large, long-term consequences for a system, i.e., ‘‘little things can make a big difference’’ (4).
    In discussions of global change, the term tipping point has been used to describe a variety of phenomena, including the appearance of a positive feedback, reversible phase transitions, phase transitions with hysteresis effects, and bifurcations where the transition is smooth but the future path of the system depends on the noise at a critical point. We offer a formal definition, introducing the term ‘‘tipping element’’ to describe subsystems of the Earth system that are at least subcontinental in scale and can be switched—under certain circumstances— into a qualitatively different state by small perturbations. The tipping point is the corresponding critical point—in forcing and a feature of the system—at which the future state of the system is qualitatively altered.
    Many of the systems we consider do not yet have convincingly established tipping points. Nevertheless, increasing political demand to define and justify binding temperature targets, as well as wider societal interest in nonlinear climate changes, makes it timely to review potential tipping elements in the climate system under anthropogenic forcing (5) (Fig. 1). To this end, we organized a workshop entitled ‘‘Tipping Points in the Earth System’’ at the British Embassy, Berlin, which brought together 36 leading experts, and we conducted an expert elicitation that involved 52 members of the international scientific community. Here we combine a critical review of the literature with the results of the workshop to compile a short list of potential policy-relevant future tipping elements in the climate system. Results from the expert elicitation are used to rank a subset of these tipping elements in terms of their sensitivity to global warming and the associated uncertainty. Then we consider the prospects for early warning of an approaching tipping point.
    Defining a Tipping Element and Its Tipping Point
    Previous reviews (6–10) have defined ‘‘abrupt climate change’’ as occurring ‘‘when the climate system is forced to cross some
    1786–1793 􏰁 PNAS 􏰁 February 12, 2008 􏰁 vol. 105 􏰁 no. 6
    threshold, triggering a transition to a new state at a rate determined by the climate system itself and faster than the cause’’ (8), which is a case of bifurcation (i.e., one that focuses on equilibrium properties, implying some degree of irreversibil- ity). We have formulated a much broader definition of a tipping element, because (i) we wish to include nonclimatic variables; (ii) there may be cases where the transition is slower than the anthropogenic forcing causing it; (iii) there may be no abrupt- ness, but a slight change in control may have a qualitative impact in the future; and (iv) for several important phase changes, state-of-the-art models differ as to whether the transition is reversible or irreversible (in principle).
    We consider ‘‘components’’ (􏰃) of the Earth system that are associated with a specific region (or collection of regions) of the globe and are at least subcontinental in scale (length scale of order 􏰄1,000 km). A full formal definition of a tipping element is given in supporting information (SI) Appendix 1. For the cases considered herein, a system 􏰃 is a tipping element if the following condition is met:
    The parameters controlling the system can be transparently combined into a single control 􏰏, and there exists a critical control value 􏰏crit from which any significant variation by 􏰐􏰏 􏰅 0 leads to a qualitative change (Fˆ) in a crucial system feature F, after some observation time T 􏰅 0, measured with respect to a reference feature at the critical value, i.e.,
    􏰁F􏰆􏰏􏰑􏰏 􏰈􏰐􏰏􏰁T􏰇􏰋F􏰆􏰏 􏰁T􏰇􏰁􏰑Fˆ􏰅0. [1] crit crit
    This inequality applies to forcing trajectories for which a slight deviation above a critical value that continues for some time inevitably induces a qualitative change. This change may oc-
    Author contributions: T.M.L., H.H., E.K., J.W.H., and H.J.S. designed research; T.M.L., H.H., E.K., J.W.H., W.L., S.R., and H.J.S. performed research; T.M.L., H.H., E.K., and J.W.H. analyzed data; and T.M.L., H.H., E.K., and H.J.S. wrote the paper.
    The authors declare no conflict of interest.
    This article is a PNAS Direct Submission.
    Freely available online through the PNAS open access option.
    †To whom correspondence may be addressed. E-mail: or john@pik-
    This article contains supporting information online at 0705414105/DC1.
    © 2008 by The National Academy of Sciences of the USA􏰂cgi􏰂doi􏰂10.1073􏰂pnas.0705414105

    cur immediately after the cause or much later. The definition encompasses equilibrium properties with threshold behavior as well as critical rates of forcing. In its equilibrium application, it includes all orders of phase transition and the most common bifurcations found in nature: saddle-node and Hopf bifurcations. The definition could in principle be applied at any time, e.g., in Earth’s history. The feature of the system and the parameter(s) that influence it need not be climate variables. Critical condi- tions may be reached autonomously (without human interfer- ence), and natural variability could trigger a qualitative change.
    Here we restrict ourselves to tipping elements that may be accessed by human activities and are potentially relevant to current policy. We define the subset of policy-relevant tipping elements by adding to condition 1 the following conditions:
    2. Human activities are interfering with the system 􏰃 such that decisions taken within a ‘‘political time horizon’’ (TP 􏰅 0) can determine whether the critical value for the control 􏰏crit is reached. This occurs at a critical time (tcrit) that is usually within TP but may be later because of a commitment to further change made during TP.
    3. The time to observe a qualitative change plus the time to trigger it lie within an ‘‘ethical time horizon’’ (TE); tcrit 􏰈 T 􏰒 TE. TE recognizes that events too far away in the future may not have the power of influencing today’s decisions.
    4. A significant number of people care about the fate of the component 􏰃, because it contributes significantly to the overall mode of operation of the Earth system (such that tipping it modifies the qualitative state of the whole system), it contributes significantly to human welfare (such that tipping it impacts on many people), or it has great value in itself as a unique feature of the biosphere. A qualitative change should correspondingly be defined in terms of impacts.
    Conditions 2–4 give our definition of a policy-relevant tipping
    element an ethical dimension, which is inevitable because a focus on policy requires the inclusion of normative judgements. These enter in the choices of the political time horizon (TP), the ethical time horizon (TE), and the qualitative change that fulfills con- dition 4. We suggest a maximum TP 􏰉 100 years based on the human life span and our (limited) ability to consider the world we are leaving for our grandchildren, noting also the Intergov- ernmental Panel on Climate Change (IPCC) focus on this timescale. We suggest TE 􏰉 1,000 years based on the lifetime of civilizations, noting that this is longer than the timescale of
    Fig. 1. Map of potential policy-relevant tipping elements in the climate system, up- dated from ref. 5 and overlain on global population density. Subsystems indicated could exhibit threshold-type behavior in re- sponse to anthropogenic climate forcing, where a small perturbation at a critical point qualitatively alters the future fate of the system. They could be triggered this century and would undergo a qualitative change within this millennium. We exclude from the map systems in which any threshold appears inaccessible this century (e.g., East Antarctic Ice Sheet) or the qualitative change would appear beyond this millennium (e.g., marine methane hydrates). Question marks indicate systems whose status as tipping elements is particularly uncertain.
    nation states and current political entities. Thus, we focus on the consequences of decisions enacted within this century that trigger a qualitative change within this millennium, and we exclude tipping elements whose fate is decided after 2100.
    In the limit 􏰐􏰏 3 0, condition 1 would only include vanishing equilibria and first-order phase transitions. Instead we consider that a ‘‘small’’ perturbation 􏰐􏰏 should not exceed the magnitude of natural variability in 􏰏. Considering global temperature, climate variability on interannual to millennial timescales is 0.1–0.2°C. Alternatively, a popular target is to limit anthropo- genic global mean temperature increase to 2°C, and we take a ‘‘small’’ perturbation to be 10% of this. Either way, 􏰐􏰏 􏰉 0.2°C seems reasonable.
    One useful way of classifying tipping elements is in terms of the time, T, over which a qualitative change is observed: (i) rapid, abrupt, or spasmodic tipping occurs if the observation time is very small compared with TP (but T 􏰊 0); (ii) gradual or episodic tipping occurs if the observation time is intermediate (e.g., of order TP); and (iii) slow or asymptotic tipping occurs if the observation time is very long (in particular, T 3 TE).
    Several key questions arise. What are the potential policy- relevant tipping elements of the Earth system? And for each: What is the mechanism of tipping? What is the key feature F of interest? What are the parameter(s) projecting onto the control 􏰏, and their value(s) near 􏰏crit? How long is the transition time T? What are the associated uncertainties?
    Policy-Relevant Tipping Elements in the Climate System
    Earth’s history provides evidence of nonlinear switches in state or modes of variability of components of the climate system (6–10). Such past transitions may highlight potential tipping elements under anthropogenic forcing, but the boundary con- ditions under which they occurred were different from today, and anthropogenic forcing is generally more rapid and often different in pattern (11). Therefore, locating potential future tipping points requires some use of predictive models, in com- bination with paleodata and/or historical data.
    Here we focus on policy-relevant potential future tipping elements in the climate system. We considered a long list of candidates (Fig. 1, Table 1), and from literature review and the aforementioned workshop, we identified a short list of candi- dates that meet conditions 1–4 (top nine rows in Table 1). To meet condition 1, there needed to be some theoretical basis (􏰅1 model study) for expecting a system to exhibit a critical threshold
    Lenton et al.
    PNAS 􏰁 February 12, 2008 􏰁 vol. 105 􏰁 no. 6 􏰁 1787
    Table 1. Policy-relevant potential future tipping elements in the climate system and (below the empty line) candidates that we considered but failed to make the short list*
    Tipping element Arctic summer sea-ice
    Greenland ice sheet (GIS) West Antarctic ice sheet
    Atlantic thermohaline
    circulation (THC) El Nin ̃ o–Southern
    Oscillation (ENSO) Indian summer monsoon
    Sahara/Sahel and West
    African monsoon (WAM) Amazon rainforest
    Boreal forest
    Antarctic Bottom Water (AABW)*
    Permafrost* Marine methane
    hydrates* Ocean anoxia*
    Arctic ozone*
    Feature of system, F (direction of change)
    Areal extent (􏰋) Ice volume (􏰋)
    Ice volume (􏰋)
    Overturning (􏰋)
    Amplitude (􏰈)
    Rainfall (􏰋)
    Vegetation fraction (􏰈)
    Tree fraction (􏰋)
    Tree fraction (􏰋)
    Formation (􏰋)
    Tree fraction (􏰈)
    Volume (􏰋) Hydrate volume (􏰋)
    Ocean anoxia (􏰈) Column depth (􏰋)
    Control parameter(s), 􏰏
    Local 􏰌Tair, ocean heat transport
    Local 􏰌Tair
    Local 􏰌Tair, or less
    Freshwater input to N
    Atlantic Thermocline depth,
    sharpness in EEP Planetary albedo over
    India Precipitation
    Precipitation, dry season length
    Local 􏰌Tair Precipitation–
    Evaporation Growing degree days
    above zero 􏰌Tpermafrost
    􏰌Tsediment Phosphorus input to
    Polar stratospheric
    cloud formation
    Critical Global value(s),† 􏰏crit warming†‡
    Unidentified§ 􏰈0.5–2°C
    Transition timescale,† T
    􏰄10 yr (rapid) 􏰅300 yr (slow)
    􏰅300 yr (slow)
    􏰄100 yr (gradual)
    􏰄100 yr (gradual)
    􏰄1 yr (rapid)
    􏰄10 yr (rapid)
    􏰄50 yr (gradual)
    􏰄50 yr (gradual)
    􏰄100 yr (gradual)
    􏰄100 yr (gradual)
    􏰍100 yr (gradual) 103 to 105 yr (􏰅TE)
    􏰄104 yr (􏰅TE) 􏰍1 yr (rapid)
    Key impacts
    Amplified warming, ecosystem change
    Sea level 􏰈2–7 m Sea level 􏰈5 m
    Regional cooling, sea level, ITCZ shift
    Drought in SE Asia and elsewhere
    Drought, decreased carrying capacity
    Increased carrying capacity
    Biodiversity loss, decreased rainfall
    Biome switch
    Ocean circulation, carbon storage
    Amplified warming, biome switch
    CH4 and CO2 release Amplified global warming
    Marine mass extinction Increased UV at surface
    􏰈􏰄3°C 􏰈􏰄5–8°C
    􏰈0.1–0.5 Sv Unidentified§ 0.5
    100 mm/yr 1,100 mm/yr 􏰈􏰄7°C
    􏰈100 mm/yr Missing􏰀
    􏰈1–2°C 􏰈3–5°C
    􏰈3–5°C 􏰈3–6°C N/A 􏰈3–5°C 􏰈3–4°C 􏰈3–5°C Unclear¶ —

    Unidentified§ Unclear¶
    􏰈􏰄20% Unclear¶ 195 K Unclear¶
    N, North; ITCZ, Inter-tropical Convergence Zone; EEP, East Equatorial Pacific; SE, Southeast.
    *See SI Appendix 2 for more details about the tipping elements that failed to make the short list.
    †Numbers given are preliminary and derive from assessments by the experts at the workshop, aggregation of their opinions at the workshop, and review of the
    ‡Global mean temperature change above present (1980 –1999) that corresponds to critical value of control, where this can be meaningfully related to global
    §Meaning theory, model results, or paleo-data suggest the existence of a critical threshold but a numerical value is lacking in the literature. ¶Meaning either a corresponding global warming range is not established or global warming is not the only or the dominant forcing. 􏰀Meaning no subcontinental scale critical threshold could be identified, even though a local geographical threshold may exist.
    (􏰏crit) at a subcontinental scale, and/or past evidence of threshold behavior. Where the proposed 􏰏crit could be meaningfully related to temperature, condition 2 was evaluated based on an ‘‘acces- sible neighborhood’’ of global temperatures from the IPCC (12) of 1.1–6.4°C above 1980–1999 that could be committed to over the next TP 􏰉 100 years, and on recognition that transient warming is generally greater toward the poles and greater on land than in the ocean. Condition 3 was evaluated on the basis of model projections, known shortcomings of the models, and paleodata. Our collective judgement was used to evaluate condition 4.
    Our short list differs from that of the IPCC (ref. 12, chapter 10, especially p. 775 ff, p. 818 ff) because our definition and criteria differ from, and are more explicit than, the IPCC notion of abrupt climate change. The evidence base we use is also slightly different because it encompasses some more recent studies. The authors of this paper and the workshop participants are a smaller group of scientists than the IPCC members, the groups are only partially overlapping, and our analysis was undertaken largely in parallel. We seek to add value to the IPCC overview by injecting a more precise definition and undertaking a complementary, in-depth evaluation.
    We now discuss the entries that made our short list and seek to explain significant discrepancies from the IPCC where they
    arise. Those candidates that did not make the short list (and why) are discussed in SI Appendix 2.
    Arctic Sea-Ice. As sea-ice melts, it exposes a much darker ocean surface, which absorbs more radiation–amplifying the warming. Energy-balance models suggest that this ice-albedo positive feedback can give rise to multiple stable states of sea-ice (and land snow) cover, including finite ice cap and ice-free states, with ice caps smaller than a certain size being unstable (13). This small ice-cap instability is also found in some atmospheric general circulation models (AGCMs), but it can be largely eliminated by noise due to natural variability (14). The instability is not expected to be relevant to Southern Ocean sea-ice because the Antarctic continent covers the region over which it would be expected to arise (15). Different stable states for the flow rate through the narrow outlets that drain parts of the Arctic basin have also been found in a recent model (16). For both summer and winter Arctic sea-ice, the area coverage is declining at present (with summer sea-ice declining more markedly; ref. 17), and the ice has thinned significantly over a large area. Positive ice-albedo feedback dominates external forcing in causing the thinning and shrinkage since 1988, indicating strong nonlinearity and leading some to suggest that this system may already have passed a tipping point (18), although others disagree (19). In IPCC projections with ocean-atmosphere general circulation
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    models (OAGCMs) (12), half of the models become ice-free in September during this century (19), at a polar temperature of 􏰋9°C (9°C above present) (20). The transition has nonlinear steps in many of the models, but a common critical threshold has yet to be identified (19). Thinning of the winter sea-ice increases the efficiency of formation of open water in summer, and abrupt retreat occurs when ocean heat transport to the Arctic increases rapidly (19). Only two IPCC models (12) exhibit a complete loss of annual sea-ice cover under extreme forcing (20). One shows a nonlinear transition to a new stable state in 􏰍10 years when polar temperature rises above 􏰋5°C (13°C above present), whereas the other shows a more linear transition. We conclude that a critical threshold for summer Arctic sea-ice loss may exist, whereas a further threshold for year-round ice loss is more uncertain and less accessible this century. Given that the IPCC models significantly underestimate the observed rate of Arctic sea-ice decline (17), a summer ice-loss threshold, if not already passed, may be very close and a transition could occur well within this century.
    Greenland Ice Sheet (GIS). Ice-sheet models typically exhibit mul- tiple stable states and nonlinear transitions between them (21). In some simulations with the GIS removed, summer melting prevents its reestablishment (22), indicating bistability, although others disagree (23). Regardless of whether there is bistability, in deglaciation, warming at the periphery lowers ice altitude, increasing surface temperature and causing a positive feedback that is expected to exhibit a critical threshold beyond which there is ongoing net mass loss and the GIS shrinks radically or eventually disappears. During the last interglacial (the Eemian), there was a 4- to 6-m higher sea level that must have come from Greenland and/or Antarctica. Increased Arctic summer insola- tion caused an estimated 􏰍3.5°C summertime warming of Greenland, and shrinkage of the GIS contributed an estimated 1.9–3.0 m to sea level, although a widespread ice cap remained (24). Broadly consistent with this, future projections suggest a GIS threshold for negative surface mass balance resides at 􏰑􏰄3°C local warming (above preindustrial) (3, 25). Uncertain- ties are such that IPCC (12) put the threshold at 􏰄1.9 – 4.6°C global warming (above preindustrial), which is clearly accessible this century. We give a closer and narrower range (above present) because amplification of warming over Greenland may be greater (26) than assumed (12, 25) because of more rapid sea-ice decline than modeled (17). Also, recent observations show the surface mass balance is declining (12) and contributing to net mass loss from the GIS (27, 28) that is accelerating (28, 29). Finally, existing ice-sheet models are unable to explain the speed of recent changes. These changes include melting and thinning of the coastal margins (30) and surging of outlet gla- ciers (29, 31), which may be contributed to by the intrusion of warming ocean waters (32). This is partly compensated by some mass gain in the interior (33). There is a lack of knowl- edge of natural GIS variability, and Greenland temperature changes have differed from the global trend (26), so interpre- tation of recent observations remains uncertain. If a threshold is passed, the IPCC (12) gives a 􏰅1,000-year timescale for GIS collapse. However, given the acknowledged (12) lack of processes that could accelerate collapse in current models, and their inability to simulate the rapid disappearance of con- tinental ice at the end of the last ice age, a lower limit of 300 years is conceivable (34).
    West Antarctic Ice Sheet (WAIS). Most of the WAIS is grounded below sea level and has the potential to collapse if grounding-line retreat triggers a strong positive feedback whereby ocean water undercuts the ice sheet and triggers further separation from the bedrock (35–37). The WAIS has retreated at least once during the Pleistocene (38), but the full extent of retreat is not known, nor is
    whether it occurred in the Eemian or the long, warm interglacial MIS-11 􏰄400 ka. Approximately 1–4 m of the Eemian sea-level rise may have come from Antarctica, but some could have been from parts of the East Antarctic Ice Sheet grounded below sea level (and currently thinning at a rapid rate). WAIS collapse may be preceded by the disintegration of ice shelves and the acceleration of ice streams. Ice shelf collapse could be triggered by the intrusion of warming ocean water beneath them or by surface melting. It requires 􏰄5°C of local warming for surface atmospheric tempera- tures to exceed the melting point in summer on the major (Ross and Fischner-Ronne) ice shelves (12, 37). The threshold for ocean warming is estimated to be lower (37). The WAIS itself requires 􏰄8°C of local warming of the surface atmosphere at 75–80°S to reach the melting point in summer (37). Although the IPCC (12) declines to give a threshold, we estimate a range that is clearly accessible this century. Concern is raised by recent inferences from gravity measurements that the WAIS is losing mass (39), and observations that glaciers draining into the Amundsen Sea are losing 60% more ice than they are gaining and hence contributing to sea-level rise (40). They drain a region containing 􏰄1.3 m of a total 􏰄5 m of global sea-level rise contained in the WAIS. Although the timescale is highly uncertain, a qualitative WAIS change could occur within this millennium, with collapse within 300 years being a worst-case scenario. Rapid sea-level rise (􏰅1 m per century) is more likely to come from the WAIS than from the GIS.
    Atlantic Thermohaline Circulation (THC). A shutoff in North Atlantic Deep Water formation and the associated Atlantic THC can occur if sufficient freshwater (and/or heat) enters the North Atlantic to halt density-driven North Atlantic Deep Water formation (41). Such THC reorganizations play an important part in rapid climate changes recorded in Greenland during the last glacial cycle (42, 43). Hysteresis of the THC has been found in all models that have been systematically tested thus far (44), from conceptual ‘‘box’’ representations of the ocean (45) to OAGCMs (46). The most complex models have yet to be systematically tested because of excessive computational cost. Under sufficient North Atlantic freshwater forcing, all models exhibit a collapse of convection. In some experiments, this collapse is reversible (47) (after the forcing is removed, convec- tion resumes), whereas in others, it is irreversible (48)— indicating bistability. In either case, a tipping point has been passed according to condition 1. The proximity of the present climate to this tipping point varies considerably between models, corresponding to an additional North Atlantic freshwater input of 0.1–0.5 Sv (44). The sensitivity of North Atlantic freshwater input to anthropogenic forcing is also poorly known, but regional precipitation is predicted to increase (12) and the GIS could contribute significantly (e.g., GIS melt over 1,000 years is equivalent to 0.1 Sv). The North Atlantic is observed to be freshening (49), and estimates of recent increases in freshwater input yield 0.014 Sv from melting sea ice (18), 0.007 Sv from Greenland (29), and 0.005 Sv from Eurasian rivers (50), totaling 0.026 Sv, without considering precipitation over the oceans or Canadian river runoff. The IPCC (12) argues that an abrupt transition of the THC is ‘‘very unlikely’’ (probability 􏰍10%) to occur before 2100 and that any transition is likely to take a century or more. Our definition encompasses gradual transitions that appear continuous across the tipping point; hence, some of the IPCC runs (ref. 12, p. 773 ff) may yet meet our criteria (but would need to be run for longer to see if they reach a qualitatively different state). Furthermore, the IPCC does not include freshwater runoff from GIS melt. Subsequent OAGCM simulations clearly pass a THC tipping point this century and undergo a qualitative change before the next mil- lennium (48). Both the timescale and the magnitude of forc- ing are important (51), because a more rapid forcing to a given level can more readily overwhelm the negative feedback
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    that redistributes salt in a manner that maintains whatever is the current circulation state.
    El Nin ̃ o–Southern Oscillation (ENSO). Gradual anthropogenic forc- ing is expected, on theoretical grounds, to interact with natural modes of climate variability by altering the relative amount of time that the climate system spends in different states (52). ENSO is the most significant ocean-atmosphere mode, and its variability is controlled by (at least) three factors: zonal mean thermocline depth, thermocline sharpness in the EEP, and the strength of the annual cycle and hence the meridional temper- ature gradient across the equator (53, 54). Increased ocean heat uptake could cause a permanent deepening of the thermocline in the EEP and a consequent shift from present day ENSO variability to greater amplitude and/or more frequent El Nin ̃os (55). However, a contradictory theory postulates sustained La Nin ̃a conditions due to stronger warming of the West Equatorial Pacific than the East, causing enhanced easterly winds and reinforcing the up-welling of cold water in the EEP (56). The mid-Holocene had a reduction in ENSO amplitude related to a stronger zonal temperature gradient (57, 58). The globally 􏰄3°C warmer early Pliocene is characterized by some as having persistent El Nin ̃o conditions (59), whereas others disagree (60). Under future forcing, the first OAGCM studies showed a shift from the current ENSO variability to more persistent or frequent El Nin ̃o-like conditions. Now that numerous OAGCMs have been intercompared, there is no consistent trend in their tran- sient response and only a small collective probability of a shift toward more persistent or frequent El Nin ̃o conditions (61, 62). However, in response to a warmer stabilized climate, the most realistic models simulate increased El Nin ̃o amplitude (with no clear change in frequency) (54). This would have large-scale impacts, and even if the transition is smooth and gradual, a tipping point may exist by condition 1. Given also that past climate changes have been accompanied by changes in ENSO, we differ from IPCC (12) and consider there to be a significant probability of a future increase in ENSO amplitude. The re- quired warming can be accessed this century (54) with the transition happening within a millennium, but the existence and location of any threshold is particularly uncertain.
    Indian Summer Monsoon (ISM). The land-to-ocean pressure gradi- ent, which drives the monsoon circulation is reinforced by the moisture the monsoon itself carries from the adjacent Indian Ocean (moisture-advection feedback) (63). Consequently, any perturbation that tends to weaken the driving pressure gradient has the potential to destabilize the monsoon circulation. Green- house warming that is stronger over land and in the Northern Hemisphere tends to strengthen the monsoon, but increases in planetary albedo over the continent due to aerosol forcing and/or land-use change tend to weaken it. The ISM exhibited rapid changes in variability during the last ice age (64) and the Holocene (65), with an increased strength during recent centu- ries consistent with Northern Hemisphere warming (66). Recent time series display strongly nonlinear characteristics, from the intraseasonal via the interannual and the decadal to the centen- nial timescale (67), with the interannual variations lag correlated with the phases of ENSO, although this may be increasingly masked by anthropogenic forcing (68). A simple model (63) predicts collapse of the ISM if regional planetary albedo exceeds 􏰄0.5, whereas increasing CO2 stabilizes the monsoon. IPCC projections do not show obvious threshold behavior this century (12), but they do agree that sulfate aerosols would dampen the strength of ISM precipitation, whereas increased greenhouse gases increase the interannual variability of daily precipitation (69). We differ from IPCC (12) on the basis of past apparent threshold behavior of the ISM and because brown haze and land-use-change forcing are poorly captured in the models.
    Furthermore, conceptual work on the potentially chaotic nature of the ISM (70) has been developed (V. Petoukhov, K. Zickfeld, and H.J.S., unpublished work) to suggest that under some plausible decadal-scale scenarios of land use and greenhouse gas and aerosol forcing, switches occur between two highly nonlinear metastable regimes of the chaotic oscillations corresponding to the ‘‘active’’ and ‘‘weak’’ monsoon phases, on the intraseasonal and interannual timescales. Sporadic bifurcation transitions may also happen from regimes of chaotic oscillations to regimes with highly deterministic oscillations, or to regimes with very weak oscillations.
    Sahara/Sahel and West African Monsoon (WAM). Past greening of the Sahara occurred in the mid-Holocene (71–73) and may have happened rapidly in the earlier Bo ̈lling-Allerod warming. Col- lapse of vegetation in the Sahara 􏰄5,000 years ago occurred more rapidly than orbital forcing (71, 72). The system has been modeled and conceptualized in terms of bistable states that are maintained by vegetation–climate feedback (71, 74). However, it is intimately tied to the WAM circulation, which in turn is affected by sea surface temperatures (SSTs), particularly anti- symmetric patterns between the Hemispheres. Greenhouse gas forcing is expected to increase the interhemispheric SST gradi- ent and thereby increase Sahel rainfall; hence, the recent Sahel drought has been attributed to increased aerosol loading cooling the Northern Hemisphere (75). Future 21st century projections differ (75, 76); in two AOGCMs, the WAM collapses, but in one this leads to further drying of the Sahel, whereas in the other it causes wetting due to increased inflow from the West. The latter response is more mechanistically reasonable, but it requires a 􏰄3°C warming of SSTs in the Gulf of Guinea (76). A third AOGCM with the most realistic present-day WAM predicts no large trend in mean rainfall but a doubling of the number of anomalously dry years by the end of the century (76). If the WAM is disrupted such that there is increased inflow from the West (76), the resulting moisture will wet the Sahel and support greening of the Sahara, as is seen in mid-Holocene simulations (73). Indeed, in an intermediate complexity model, increasing atmospheric CO2 has been predicted to cause future expansion of grasslands into up to 45% of the Sahara, at a rate of up to 10% of Saharan area per decade (11). In the Sahel, shrub vegetation may also increase due to increased water use efficiency (stomatal closure) under higher atmospheric CO2 (77). Such greening of the Sahara/Sahel is a rare example of a beneficial potential tipping element.
    Amazon Rainforest. A large fraction of precipitation in the Am- azon basin is recycled, and, therefore, simulations of Amazon deforestation typically generate 􏰄20–30% reductions in precip- itation (78), lengthening of the dry season, and increases in summer temperatures (79) that would make it difficult for the forest to reestablish, and suggest the system may exhibit bist- ability. Dieback of the Amazon rainforest has been predicted (2, 80) to occur under 􏰄3–4°C global warming because of a more persistent El Nin ̃o state that leads to drying over much of the Amazon basin (81). Different vegetation models driven with similar climate projections also show Amazon dieback (82), but other global climate models (83) project smaller reductions (or increases) of precipitation and, therefore, do not produce die- back (84). A regional climate model (85) predicts Amazon dieback due to widespread reductions in precipitation and lengthening of the dry season. Changes in fire frequency prob- ably contribute to bistability and will be amplified by forest fragmentation due to human activity. Indeed land-use change alone could potentially bring forest cover to a critical threshold. Thus, the fate of the Amazon may be determined by a complex interplay between direct land-use change and the response of regional precipitation and ENSO to global forcing.
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    Boreal Forest. The boreal system exhibits a complex interplay between tree physiology, permafrost, and fire. Under climate change, increased water stress, increased peak summer heat stress causing increased mortality, vulnerability to disease and subsequent fire, as well as decreased reproduction rates could lead to large-scale dieback of the boreal forests (77, 86), with transitions to open woodlands or grasslands. In interior boreal regions, temperate tree species will remain excluded from succession due to frost damage in still very cold winters. Continental steppe grasslands will expand at the expense of boreal forest where soil moisture along the arid timberline ecotone declines further (87), amplified through concurrent increases in the frequency of fires. Newly unfrozen soils that regionally drain well, and reductions in the amount of snow, also support drying, more fire and hence less biomass. In contrast, increased thaw depth and increased water-use efficiency under elevated CO2 will tend to increase available soil moisture, decreasing fire frequency and increasing woody biomass. Studies suggest a threshold for boreal forest dieback of 􏰄3°C global warming (77, 86), but limitations in existing models and physi- ological understanding make this highly uncertain.
    Others. We remind the reader that we considered other candidate tipping elements, which are not listed here because they did not meet conditions 2–4 for policy relevance. Some are listed in Table 1 and discussed in SI Appendix 2.
    Ranking the Threat
    Given our identification of policy-relevant tipping elements in the climate system, how do we decide which pose the greatest threat to society and, therefore, need the greatest attention? The first step is to asses the sensitivity of each tipping element to global warming and the associated uncertainties, including the confidence of the community in the argument for tipping element status. Our workshop and systematic review of the literature addressed this. In addition, formal elicitations of expert beliefs have frequently been used to bring current un- derstanding of model studies, empirical evidence, and theoret- ical considerations to bear on policy-relevant variables (88). From a natural science perspective, a general criticism is that expert beliefs carry subjective biases and, moreover, do not add to the body of scientific knowledge unless verified by data or theory. Nonetheless, expert elicitations, based on rigorous pro- tocols from statistics (89–91) and risk analysis (91, 92), have proved to be a very valuable source of information in public policymaking (93). It is increasingly recognized that they can also play a valuable role for informing climate policy decisions (94). In the field of climate change, formal expert elicitations have been conducted, e.g., on climate sensitivity (95), forest ecosys- tems (96), the WAIS (97), radiative forcing of aerosols (98), and the THC (99).
    On the basis of previous experience (99), we used the afore- mentioned workshop to initiate an elicitation of expert opinions on, among other things, six potential tipping elements listed in Table 1: reorganization of the Atlantic THC, melt of the GIS, disintegration of the WAIS, Amazon rainforest dieback, dieback of boreal forests, and shift of the ENSO regime to an El Nin ̃o-like mean state. The elicitation was based on a computer- based interactive questionnaire that was completed individually by participating experts. Following a pilot phase at the workshop, the questionnaire was distributed to 193 international scientists in October and November 2005; 52 experts returned a completed questionnaire (among them 16 workshop participants and 22 contributors to the IPCC Fourth Assessment Report). Although participation inevitably involved a self-selection process, we assembled a heterogeneous group covering a wide range of
    expertise (see SI Appendix 3). The full results will be presented separately (E.K., J.W.H., H.H., R. Dawson, and H.J.S., unpub- lished work). Here we report a subset that reflect the range of scientific perspectives to supplement our own assessment of the tipping elements.
    In the questionnaire, experts were asked for a pairwise comparison of tipping elements in terms of (i) their sensitivity to global mean temperature increase and (ii) the uncertainty about the underlying physical mechanisms. The exact questions posed to participants and the breakdown of their responses are de- scribed in SI Appendix 3. We have identified partial rankings of tipping elements from the collection of expert responses. Be- cause the number of experts commenting on individual pairs of tipping elements varied widely, those rankings could not be established with equal credibility. We highlight the difference in expert consensus by using the symbols 􏰅􏰅 and 􏰅 for strong and weak consensus upon the ordering, respectively, and by providing the number x that agreed with the direction of the or- dering compared with the number y of experts who commented on the pair [given as x(y)]. For sensitivity to global mean warm- ing, we find
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    8(10) to WAIS
    7(7) to THC
    WAIS Amazon rainforest
    > >
    where the more sensitive tipping element is to the left. Owing to the close link between ENSO and the Amazon rainforest, both were judged of similar sensitivity to warming, but experts were divided as to whether ENSO would be more sensitive than the THC. Boreal forests were only compared with the Amazon rainforest, and three out of five experts judged the former to be more sensitive to global mean warming. Concerning the uncer- tainty about the physical mechanisms that may give rise to tipping points, we find
    3(4) to THC WAIS >>
    Amazon rainforest ENSO
    6(9) to GIS
    2(2) to THC 6(8)
    1(1) 3+2(6) 2(2)
    to GIS
    to THC

    to GIS
    THC >> GIS,
    where the more uncertain tipping element is to the left. We display a greater or equal uncertainty about the ENSO com- pared with the THC, because three and two out of six experts believed the ENSO to be more and similarly uncertain, respec- tively. In addition, five out of six experts judged the uncertainty about the response of boreal forests to be larger than for the Amazon rainforest.
    Taking into account our own analysis of the literature (sum- marized in the previous section and Table 1) and the expert elicitation (summarized above), the potential tipping elements in the climate system may be grouped into three clusters: (i) high sensitivity with smallest uncertainty: GIS and Arctic sea-ice; (ii) intermediate sensitivity with largest uncertainty: WAIS, Boreal forest, Amazon rainforest, ENSO, and WAM; (iii) low sensitivity with intermediate uncertainty: THC. ISM is not included in the clustering because its forcing differs, but it clearly has large uncertainty. We conclude that the greatest (and clearest) threat
    is to the Arctic with summer sea-ice loss likely to occur long before (and potentially contribute to) GIS melt. Tipping ele- ments in the tropics, the boreal zone, and West Antarctica are surrounded by large uncertainty and, given their potential sensitivity, constitute candidates for surprising society. The archetypal example of a tipping element, the THC appears to be a less immediate threat, but the long-term fate of the THC under significant warming remains a source of concern (99).
    The Prospects for Early Warning
    Establishing early warning systems for various tipping elements would clearly be desirable, but can 􏰏crit be anticipated before we reach it? In principle, an incipient bifurcation in a dynamical system could be anticipated (100), by looking at the spectral properties of time series data (101), in particular, extracting the longest system-immanent timescale (􏰓) from the response of the system to natural variability (102). Systems theory reveals (Fig. 2A) (i) that those tipping points that represent a bifurcation are universally characterized by 􏰓 3 􏰎 at the threshold, and (ii) that in principle 􏰓 could be reconstructed through methods of time series analysis. Hence a ‘‘degenerate fingerprinting’’ method has been developed for anticipating a threshold in a spatially ex- tended system and applied to the detection of a threshold in the Atlantic THC, by using time series output from a model of intermediate complexity (102) (Fig. 2B).
    These studies reveal that if a system is forced slowly (keeping it in quasi-equilibrium), proximity to a threshold may be inferred in a model-independent way. However, if the system is forced faster (as is probably the case for the THC today), a dynamical model will also be needed. Even if there is no bifurcation, determining 􏰓 is still worthwhile because it determines the system’s linear response characteristics to external forcing, and transitions that are not strictly bifurcations are expected to resemble bifurcation-type behavior to a certain degree. For strongly resource-limited ecosystems that show self-organized patchiness, their observable macrostructure may also provide an indication of their proximity to state changes (103).
    If a forewarning system for approaching thresholds is to become workable, then real-time observation systems need to be improved (e.g., building on the Atlantic THC monitoring at 26.5°N). For slow transition systems, notably ocean and ice sheets, observation records also need to be extended further back in time (e.g., for the Atlantic beyond the 􏰄150-year SST record). Analysis of extended time series data could then be used to improve models (104), e.g., an effort to determine the Atlantic’s 􏰓 and assimilate it into ocean models could reduce the vast intra- and intermodel (44) spread regarding the proximity to a tipping point (102).
    Society may be lulled into a false sense of security by smooth projections of global change. Our synthesis of present knowledge suggests that a variety of tipping elements could reach their critical point within this century under anthropogenic climate change. The greatest threats are tipping the Arctic sea-ice and the Greenland ice sheet, and at least five other elements could surprise us by exhibiting a nearby tipping point. This knowledge should influence climate policy, but a full assessment of policy relevance would require that, for each potential tipping element, we answer the following questions: Mitigation: Can we stay clear of 􏰏crit? Adaptation: Can Fˆ be tolerated?
    The IPCC provides a thorough overview of mitigation (105) and adaptation (106) work upon which such a policy assess- ment of tipping elements could be built. Given the scale of potential impacts from tipping elements, we anticipate that they will shift the balance toward stronger mitigation and demand adaptation concepts beyond incremental approaches (107, 108). Policy analysis and implementation will be ex-
    B 25 20 15 10 5
    00 0.2 0.4 0.6 0.8 1 1
    0 0.2 0.4 0.6 0.8 1
    t (50,000 yrs)
    Fig. 2. Method for estimating the proximity to a tipping point. (A) Schematic approach: The potential wells represent stable attractors, and the ball, the state of the system. Under gradual anthropogenic forcing (progressing from dark to light blue potential), the right potential well becomes shallower and finally vanishes (threshold), causing the ball to abruptly roll to the left. The curvature of the well is inversely proportional to the system’s response time 􏰓 to small perturbations. ‘‘Degenerate fingerprinting’’ (102) extracts 􏰓 from the system’s noisy, multivariate time series and forecasts the vanishing of local curvature. (B) Degenerate fingerprinting ‘‘in action’’: Shown is an example for the Atlantic meridional overturning circulation. (Upper) Overturning strength under a 4-fold linear increase of atmospheric CO2 over 50,000 years in the CLIMBER-2 model with weak, stochastic freshwater forcing. Eventually, the circulation collapses without early warning. (Lower) Overturning replaced by a proxy of the shape of the potential (as in A). Although the signal is noisier in Lower than it is in Upper, it allows forecasting of the location of the threshold (data taken from ref. 102). The solid green line is a linear fit, and the dashed green lines are 95% error bars.
    tremely challenging given the nonconvexities in the human- environment system (109) that will be enhanced by tipping elements, as well as the need to handle intergenerational justice and interpersonal equity over long periods and under conditions of uncertainty (110). A rigorous study of potential tipping elements in human socioeconomic systems would also be welcome, especially to address whether and how a rapid societal transition toward sustainability could be triggered, given that some models suggest there exists a tipping point for the transition to a low-carbon-energy system (111).
    It seems wise to assume that we have not yet identified all potential policy-relevant tipping elements. Hence, a systematic search for further tipping elements should be undertaken, drawing on both paleodata and multimodel ensemble studies. Given the large uncertainty that remains about tipping ele-
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    Proxy for Curvature
    Overturning (Sv)
    ments, there is an urgent need to improve our understanding of the underlying physical mechanisms determining their behavior, so that policy makers are able ‘‘to avoid the unman- ageable, and to manage the unavoidable’’ (112).
    ACKNOWLEDGMENTS. We thank the British Embassy in Berlin for hosting the workshop ‘‘Tipping Points in the Earth System’’ on October 5– 6, 2005, and all of the participants of the workshop and the expert elicitation. M. Wodinski prepared Fig. 1. We thank O. Edenhofer, V. Petoukhov, the editor W. C. Clark,
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    Models are representations. Climate models are representations of the climate system. Here, we’ll take a look at the interplay between observations and models (which can inform each other), and we’ll go through the process of building a simple climate model, examine various assumptions we might make, and think about how our model could be changed to more closely represent what’s really happening. You can build a simple climate model yourself. Or, you could spend a career building complex climate models.
    Learning Goals
    By the end of this section, you will be able to:
    1 Explain how modeling and observations together help us learn about how Earth’s climate system works.
    2 Explain, conceptually, how a simple energy balance model works, and some of the possible variations on an energy balance model.


    Dr Sara Harris: Hello, and welcome to this Introduction to Climate Modeling.
    How likely is it that the area where you live
    will be affected by rising sea level within your lifetime?
    Or perhaps affected by extreme weather events, like droughts or floods?
    What's the likely range of possibilities for future global temperatures,
    given the range of possible future pathways we might choose?
    Or how is Earth's climate system as a whole likely to respond
    to future changes in energy flows?
    Climate models can help us understand how Earth's climate system works.
    And they are our only tools for peering into the future
    to help us estimate the likely ranges of possibility down the road.
    We can't actually run more than one experiment on the real planet Earth,
    so climate models allow us to try out all sorts of what if scenarios.
    We can turn things on and off, and we can see what happens.
    If you've ever folded a piece of paper into the shape of an airplane
    and thrown it, you've made a model.
    If you speak, or write, or gesture in some language, you are using a model.
    Language is a representation of your thoughts,
    but can never really quite be what you're thinking, though in our language
    we do aim to get as close as possible to communicating
    what it is that we're thinking.
    We use physical models in architecture to show what something
    might look like if we were to build it.
    We use models in engineering to test designs
    before putting the time, effort, and energy into building the real thing.
    We even model our own features ourselves.
    And our models help us plan ahead, because we
    have expectations of the future.
    We expect, for example, that next winter will
    be colder than the following summer.
    We might not know exactly how cold or how warm the seasons next year will be,
    but we have a pretty good idea what clothes would be useful to have handy,
    and whether it would be useful to buy a snow shovel.
    How is it that we are able to model these things?
    We have experience, and we have observations from the world around us.
    We certainly have varying levels of confidence
    in our experience and our observations, depending on how extensive they are,
    how many times they might have been repeated,
    and whether we're pretty sure we've considered
    most of the things that are relevant, or if we're leaving something out.
    Essentially, our models of the future fit within what we think
    is the likely range of possibility.
    And we revise and refine them all the time as we gain new insights.
    Climate modeling is conceptually similar to the future modeling you and I do
    all the time for ourselves.
    Climate models are based on physical principles of how the world works,
    things like conservation of mass and energy, gravity, laws of motion,
    how chemical reactions work, and what we know about how biology works.
    These models don't exist in a vacuum, nor do they arise out of thin air.
    They are our attempts to represent Earth's climate system with the purpose
    to help us learn more about it, since, again, we
    can't run a global scale real-life experiment here more than once.
    This is a drawing of the major components of Earth's climate system,
    with arrows representing the flows of mass and energy
    among the different parts.
    This essentially represents a static model
    of what Earth's climate system looks like,
    which helps us get started thinking about it.
    The next step is to try to represent how the mass and energy flow
    through the system, turning this into something dynamic that
    can change over time.
    We'd use what we know about physics, chemistry,
    and biology to give the model information about how different
    processes work, and how fast, and under what conditions.
    So we're giving the model information about how
    to deal with stocks and flows.
    Typically, this is done using a bunch of equations,
    which represent stocks, flows, and feedbacks,
    including time scales on which different processes operate.
    And then the equations are solved by a computer.
    Once we've built a model, and it seems to operate with reasonable stability,
    then we could add, for example, some kind of perturbation.
    Then, if our model does a decent job of linking the different parts together,
    we could see how that perturbation ripples through the system
    and affects other parts.
    We could see whether and how fast the system approaches some equilibrium
    again, and what processes were largely responsible.
    We could actually turn different processes on or off
    to try to isolate their influence on the system.
    Again, something we can't do on the real planet.
    We also test our climate model's output against observations of the real world.
    And we might find out that the model aligns well with those observations.
    Or we might find out that we need to revise the model,
    or maybe that we need to go out and make some more real world
    observations to get a better handle on how things really work.
    Here's an example of a real world constraint on climate models
    that has to do with the relative proportions of liquid water and water
    At warmer temperatures, more of the water present will be in vapor form.
    And at colder temperatures, less of the water present
    will be in vapor form, and more will be as liquid water or even solid
    ice, which isn't shown here.
    If a model is trying to represent what happens to water cycling
    through the climate system, it would have
    to take into account how the proportion of vapor to liquid
    changes if the temperature changes.
    If some air warms up in the model, then the model
    should also make some of the water in that air change phase
    from liquid to vapor within some range that makes physical sense.
    If some air cools, as is common and as air rises through the atmosphere,
    then, in the model, some of the water vapor present in the air
    should condense.
    Using a relationship like this, which is based on observations
    in the real world, a modeler can tell the model
    what to do with water as temperature changes.
    This is just one example of how observations help
    inform what goes into climate models.
    There are many more, like the rate at which CO2 exchanges with the ocean,
    or the heat capacity of water, or the average growth of trees each year,
    or the temperature profile of the atmosphere.
    Ideally, climate models align with physical reality.
    So observations inform climate models, but climate models also
    can inform observations.
    For example, we've talked about how some of the excess CO2 emitted
    from human activities gets taken up by plants on land
    and some gets taken up by the oceans.
    With models and observations together, we
    can learn in more detail, more specifically,
    about where that carbon goes.
    Observations of atmospheric carbon dioxide in different parts of the world
    can be incorporated into models of atmospheric circulation, which
    tell us how the air moves around.
    And the output from those air circulation models
    can indicate which parts of the world are
    likely responsible for the uptake of CO2 from the atmosphere.
    Is it tropical forests?
    Is it certain areas of the ocean?
    The model output can actually help people decide in what regions of Earth
    would it be useful to conduct further observational work.
    To illustrate a climate model using information we've encountered earlier,
    we're going to construct a simple energy balance model.
    This model uses essentially one physical relationship, and we've seen it before.
    It's the Stefan-Boltzmann equation, which relates energy output
    to the temperature of an object.
    You'll recall from earlier that warmer objects emit more energy,
    and that energy goes up as a function of the object's temperature
    raised to the fourth power.
    So it goes up exponentially as things heat up.
    We'll use that equation, plus some addition and subtraction
    of energy flows, to make this model.
    First, we'll start with something completely unrealistic.
    Imagine turning off the sun.
    So there is no solar energy coming in.
    We'll let the Earth's surface keep its tiny amount of geothermal energy coming
    from the planet's interior, about 0.06 watts per meter squared.
    With this little energy flow, Earth's surface
    has to emit 0.06 watts per meter squared to be in thermal equilibrium.
    And it can do that at a temperature of about 32 Kelvin,
    or about minus 241 degrees Celsius.
    Now we'll turn on the sun to its current energy
    output, which means Earth gets about 341 watts per meter squared.
    This is an example of an observation that's used in climate models.
    If we want to model the Earth, we need to use a realistic number
    for the incoming solar radiation.
    We'd use a different number if we were modeling Mars, for example.
    We're going to assume, for now, that Earth absorbs
    all the radiation it gets from the sun.
    Nothing is reflected, and there are no greenhouse gases.
    When the sun first turns on, Earth is emitting
    just 0.06 watts per meter squared, but now it's
    getting 341 watts per meter squared.
    So we have an imbalance.
    Over time, Earth warms up until it reaches the right temperature
    to emit the same amount of energy as it absorbs.
    That temperature, according to Stefan-Boltzmann,
    where energy inflow equals energy outflow,
    is about 278 Kelvin, or about 5 degrees Celsius.
    So that's a very simple model.
    And it doesn't quite capture what's really going on.
    So let's add another important process, reflection.
    First, a question for you.
    What's going to happen to the temperature of our modelled Earth
    after we add reflection?
    Will temperature go up, go down, stay the same?
    What's going to happen?


    Dr Sara Harris: Today Earth reflects about 30% of the incoming energy from the sun.
    So let's make our model do that.
    Now Earth's surface only absorbs 70% of what's coming in,
    so it only has to re-emit 239 watts per meter squared.
    And so it cools down to a new equilibrium where
    energy inflow equals energy outflow, now at minus 18 degrees Celsius.
    So that's a little closer to representing the real Earth.
    And minus 18 Celsius is about the temperature of the upper atmosphere.
    And the temperature Earth's surface would
    be if we had 30% reflection and no greenhouse gases.
    Next step, add greenhouse gases.
    For our purpose here, we're going to make a simplifying assumption
    that the greenhouse gases absorb all the radiation coming
    from our surface and they re-emit half of it upward and half of it downward,
    just to make things conceptually more straightforward.
    We know that for the planet to be in energy balance,
    the upward emission from greenhouse gases
    will have to equal the solar inflow minus reflection.
    So that's 239 watts per meter squared.
    We've assumed in this model that the downward emission from greenhouse gases
    equals the upward emission.
    So that's also 239 watts per meter squared.
    So now Earth's surface is absorbing 239 from the sun plus 239
    from greenhouse gases.
    So it has to re-emit two times 239 watts per meter squared back upward
    in order for inflow to equal outflow.
    And so it warms up to 303 Kelvin, or 30 degrees Celsius.
    If we take a look at what happens to our energy balance model over time,
    it looks something like this.
    From the left, we start just when we conceptually turn the sun back
    on, and suddenly inflow far exceeds outflow.
    The red line is way above the green line.
    Temperature is the blue line.
    And you can see that Earth starts out very cold.
    And it takes some time for it to warm up to its new equilibrium
    temperature with its new inflow of energy from the sun.
    When it does warm up enough, so the inflow equals outflow,
    our model Earth's temperature stabilizes at about 5 degrees Celsius.
    But then we add a reflection.
    So 30% of the incoming solar energy gets reflected away immediately.
    And our model Earth cools down to minus 18 Celsius.
    Then we added greenhouse gases to the model.
    And it warmed up again.
    And it stabilized at about 30 degrees Celsius
    once outflow caught up with inflow again.
    So one thing to notice is that there are transition periods in the model.
    When we change something, Earth doesn't respond immediately.
    There's some lag time before it reaches a new equilibrium state.
    OK, so there's an example of an energy balance model with some assumptions
    and some simplifications.
    And this model produces a temperature for Earth's surface
    that we can compare to observations again and see how it does.
    Well, Earth's average surface temperature
    is about 15 degrees Celsius, not 30.
    So how could our model get closer to approximating reality?
    Well, we could divide the atmosphere into layers
    and could more realistically represent the flows
    of energy due to greenhouse gases in the atmosphere,
    which aren't simply half up and half down.
    We could also take into account the fact that some energy emitted from Earth's
    surface proceeds directly to space.
    It doesn't all get absorbed by greenhouse gases.
    Or we could include that some energy leaves
    Earth's surface through latent heat transfer in thermals,
    not only via radiation.
    We could get specific about what's on Earth's surface.
    Is it water?
    Is it rock?
    We could make our energy balance model more closely approximate the real Earth
    by dividing our model planet into different latitude bands,
    not just treat the whole thing as one big average.
    The purpose of going through this model is
    to illustrate how we can use a few equations
    and construct a model that actually does approximate some
    of the processes happening on Earth.
    You could build this model yourself in a spreadsheet.
    With more sophistication, you could include more processes,
    giving them magnitudes based on observations in the real world,
    and bring your model closer to resembling reality.
    To summarize, with climate models, we're attempting
    to represent Earth's climate system.
    So it's important to ground the model in how physics, chemistry,
    and biology work in the real world.
    We use real-world observations to help define what's realistic in a model.
    And sometimes modeling can help us decide
    what new observations would be helpful.
    Ultimately, people build models to help better
    understand Earth's climate system.
    It's an ongoing effort.

    Read through this slide show about how climate models work. It’s a little weird to get to it, but here’s what to do:
    1 Go to
    2 Scroll down a little to the slide show (big mostly blue image).
    3 Click the “Play” button, THEN CLICK ON THE LEFT LABEL “Model Overview”.
    4 Start from Model Overview. Go through “Model Overview” and “Testing Models” (There are a few of places toward the end of “Testing Models”, you’ll notice the text and images don’t go together).
    If you are going to build a climate model, you have to make choices. You cannot represent everything that is happening in the real world. And even if you could, it might not be terribly helpful. Here we will examine some of the fundamental decisions that climate modelers make – decisions about resolution in time and space, decisions about what processes to represent explicitly, and what to approximate using reasonable assumptions and known physical relationships. Modeling choices ultimately depend on the questions you want to address.

    Learning Goals
    By the end of this section, you will be able to:
    1 Describe the tradeoffs among (1) model resolution in time and space, (2) number of processes modeled, (3) time period modeled, and (4) number of model runs.
    2 Define parameterization and give examples of parameterizations in climate models.
    3 Describe basic categories of climate models (EBMs, EMICs, GCMs) and their uses and limitations.


    Dr Sara Harris: Hello and welcome.
    In this lesson, we're going to explore some
    of the choices climate modelers make.
    Climate models vary widely from those that
    include few processes in average over large space and time scales
    to those that explicitly attempt to model many interrelated processes
    and deal with smaller increments in space and time.
    It is impossible to truly capture a representation of the actual Earth.
    So modelers make choices.
    Their choices depend on the question of interest
    and also are ultimately limited by time and computing power.
    Computing power does keep increasing, which increasingly
    makes it possible to add complexity to climate models
    or allows modelers to increase spatial and temporal resolution
    or to model longer time periods or to run the model more times through.
    Here, we're going to talk about some of the choices
    you might face if you become a climate modeler.
    The simplest kind of energy balance models, like we did before,
    basically average over the whole Earth and make some big assumptions.
    But those models are still useful to do things like estimate
    how long it might take for Earth to regain energy balance
    after a perturbation or to estimate what might happen
    to Earth's average temperature if say, overall
    reflectivity changed, for example.
    But we can get more complicated and model smaller scale processes
    if we conceptually divide Earth up into smaller pieces.
    The size of the pieces depends on what processes we're interested in studying.
    For example, if you're learning to identify continents,
    you don't need a particularly detailed world map.
    But if you're trying to find an address in an unfamiliar city,
    you need some small scale detail.
    Here, one might choose to divide up the Earth into latitude bands.
    Just getting more detail by latitude can be informative
    because there are different things going on at the equator compared
    to the poles, particularly regarding energy coming in and leaving.
    The next step might be to also divide the Earth up by longitude
    and create smaller boxes instead of bands.

    You can imagine this grid over the surface of the Earth,
    and the model is keeping track of what happens in each grid zone.
    The cells are connected to one another and they exchange matter and energy
    with one another.
    The boxes, or grid cells, can extend into three spatial dimensions.
    But shown here, is how one could divide up the atmosphere vertically
    too so the cells stack on top of one another.
    Not shown here but done in climate models that include ocean dynamics,
    are cells extending downward into the oceans as well.
    One detail to note on this image, is that in the model,
    the chosen layers of the atmosphere are thinner near Earth's surface
    where there are more molecules, and then the layers get thicker-
    so have less detailed resolution-- as you go up away from the surface.
    The same pattern is typically chosen in the ocean where a lot of the action
    is closer to the surface layer.
    So it's useful to have higher spatial resolution there.
    Then they average bigger pieces deeper down in the ocean.
    The cells don't all need to be the same size.
    Also not shown here, is surface topography
    like mountain ranges, which stick up into the atmosphere
    and sometimes need to be taken into account depending on what
    questions you're trying to answer.
    When should you stop dividing the earth into smaller pieces in your model?
    If you model only be average Earth, you can address questions
    about the average Earth.
    If you want to answer questions about say, temperature and precipitation
    patterns that happen on spatial skills scales of continents,
    you have to divide the Earth into enough cells
    that you can resolve the variations at the scale of interest.
    If you wanted to include hurricanes in your climate model,
    you need to have small enough cells to resolve hurricanes,
    and typically that would mean having at least four cells in the space
    covered by one hurricane.
    If you're not answering questions where you
    need to know what the hurricanes are doing though,
    you don't need to have cell sizes that small.
    Typical grid cell sizes for a general circulation model, or GCM,
    would be about 100 to 200 kilometers on a side like the coarsest resolution
    image shown here in the upper left and would
    have maybe 20 vertical layers in the atmosphere and 20 more in the oceans.
    But cell sizes continue to get smaller as computers get faster.
    In designing a climate model, you'll need
    to decide how often your model takes a snapshot of the system.
    It turns out that spatial scales and temporal scales
    are closely linked together.
    Imagine for example, you're trying to model a soccer game.
    You've set up your equations so that your virtual players
    have rules to follow.
    You divide the field into squares, and you're
    going to keep track of the number of players in each square over time
    and the location of the ball.
    How often should you collect data in order to be able to follow the action?
    You want the snapshots to make sense in time.
    So if, for example, you only look at the field every five minutes,
    each successive snapshot would be disconnected from the last.
    You'd probably need to choose a timescale that
    was fast enough that your model could follow the ball traveling from one
    square to the next to the next.
    If you choose tiny squares, you'd have to choose a very short time step too
    because the ball can travel across a small square faster than it
    can travel across a bigger square.
    So the smaller the square, the smaller the time step required.
    For a typical general circulation model that's
    trying to capture the action in the atmosphere
    at spatial scales of 1 to 200 kilometers,
    a typical time step is 20 minutes to an hour.
    If you're trying to model the growth and decay of massive ice sheets
    on time scales of thousands of years, you
    don't need to have your model look every virtual 20 minutes.
    In a soccer game, there aren't that many things to keep track of.
    In a climate model, for variables in the atmosphere,
    it would be pretty normal to keep track of temperature and humidity,
    how much water was in what phase-- that is solid ice, liquid droplets, or water
    vapor-- and the mass of the atmosphere.
    The model would also be tracking energy flows from the surface,
    into the atmospheric cells right next to the surface,
    and from those to the cells around them.
    It would also be tracking motions from one cell
    to another, both horizontally and vertically,
    like the soccer players running around.
    Models can get more complex and can add more variables.
    People might add aerosols or dust or carbon to their models
    and track how those move around and influence other parts of the system.
    They might link there atmospheric model to model
    of the oceans which would track other variables in each ocean
    cell-- like temperature and salinity or sea ice at the surface.
    Each variable would be determined for each cell
    in the model at each time step.
    So each cell would just have one value for each
    of those variables for each time step.
    We wouldn't see any of the variation that
    might be happening at smaller scales.
    It would be highly unusual for a single model
    to include all the items shown in this cartoon of the climate system.
    And in fact, greater complexity is not necessarily helpful.
    There's way more going on in the climate system
    than any model can explicitly track.
    And there are important things happening at smaller spatial
    scales than the typical grid cell size of models.
    Processes that turn out to matter on the larger spatial scale model.
    For example, photosynthesis is happening on really small scales--
    like the scale of the leaf, or if you want, even smaller than a leaf.
    Each leaf might not really matter for the climate system,
    but the aggregate effects of photosynthesis on the scale of a forest
    might be relevant.
    So there are choices to be made regarding
    at what level you explicitly model some of the processes in the climate system.
    Do you model each leaf?
    Or do you make some reasonable assumptions and approximations
    and come out with an estimate of how the whole forest is interacting
    with the rest of the climate system?
    When modelers choose to approximate some process using
    reasonable assumptions and related variables, what they're doing
    is called parametrization.
    They're approximating aggregate effects and using
    those aggregate approximations in the model.
    Probably the most common example of parameterizations in climate models
    is how people represent clouds.
    Clouds are tricky because they're typically smaller than a grid cell
    size, and cloud formation depends on lots
    of processes like evaporation and condensation
    that are happening at really tiny scales.
    We simply can't-- realistically-- model the formation of each raindrop
    everywhere on Earth.
    So modelers use other variables like temperature and relative humidity,
    which are related to cloud formation, to approximate how much cloud cover
    there would likely be in a particular grid celll--
    and to estimate the range of droplet sizes, which matters for things
    like reflectivity of the clouds.
    So parameterizations are reasonable and useful approximations.
    Some models are specifically designed to simulate short time
    periods on the order of decades.
    These are usually the most complex models with the highest resolution
    and the most things to keep track of.
    Other models are typically run out a century or so,
    which is common for questions of interest to humans alive today
    since it's a time frame we can get our heads around.
    We can imagine one fairly long human lifetime.
    Some models, however, are designed to simulate thousands of years.
    These models are often tested against geological observations
    and are run thousands of years into the future
    to address questions like, what's the long term fate of our atmospheric CO2
    Or maybe, how long might it take to melt most of the ice on Greenland, given
    some future emissions trajectory?
    So you'll need to choose how much virtual time to cover.
    All of these choices have trade-offs.
    One of the trade-offs involves computing time.
    The time it's going to take to run your model
    is how long it takes the computer to do one math operation-- like
    add two numbers together-- times the number of math operations per equation
    times the number of equations that have to be solved for every grid
    cell times the number of grid cells in your model times
    the total number of times steps.
    And this is just for one run of your model.
    If you want to say, change one of the starting values
    to something slightly different, to see whether that
    changes the model's output, you'd repeat all these computational costs.
    So we also have to multiply by the number of model runs.
    These can really add up for high resolution complex models.
    So we have constraints on climate models imposed
    by computer power and the speed at which we can solve the millions of equations.
    This constraint becomes less important over time with increasing computer
    power, and as computers get faster, we can explicitly
    incorporate more processes into models.
    And we can increase the resolution and sophistication.
    Some global models now are aiming for grid cells
    just a few kilometers on a side with associated quite short time steps.
    This will allow the models to capture processes
    at small scale that previously couldn't be models,
    but also limits the time span that can be modeled to just a couple of decades.

    But there's also a fundamental issue with model complexity.
    It's tempting to try to model everything,
    to include all possible processes at all possible scales in a climate model.
    It seems like including more processes more
    explicitly would naturally get us closer to truly representing the climate
    system, and certainly modeling specific parts of the system
    can help us better understand those parts.
    But thing can get a little off.
    Every number in a climate model has the potential
    to be a little different from the true value in the real world.
    And if enough little things get a little bit off in a complex model,
    it can translate into a larger range of possibilities for the big predictions
    that come out of the model.
    Naomi Oreskes has called this the complexity paradox.
    In her words, a complex model may be more realistic.
    Yet ironically, as we add more factors to model,
    the certainty of its predictions may decrease even as our intuitive
    faith in the model increases.
    This is a good reminder that models are not
    exact replicas of the climate system.
    Instead, they are useful tools for learning--
    tools which require continual checks against what we know about physics,
    chemistry, and biology-- checks against real world observations,
    and checks against one another.
    So modelers make choices.
    You can design a fairly simple model with large spatial scales and time
    scales, or detailed model with small grid cells, short time
    steps, and many variables.
    You could choose to explicitly model more processes,
    or you could choose to approximate using parameterizations.
    You'll be able to run your simple model faster,
    and it will be able to model longer time spans, and run your model more times
    than you can do with your complex model.
    But ultimately, your choices will depend on what questions
    you want to address through modeling.

    Read about different types of climate models
    There’s a wide range of types of models, from “Energy Balance Models”, to “Earth Models of Intermediate Complexity”, to “General Circulation Models”, and others. The choice of what kind of model to use depends on the questions the modeler is trying to address. Here’s a place to start reading about the types of climate models:

    3.1.2 Types of models
    Simplifications are unavoidable when designing a climate model as the processes that should be taken into account range from the scale of centimetres (for instance for atmospheric turbulence) to that of the Earth itself. The involved time scales also vary widely from the order of seconds for some waves, to billions of years when analysing the evolution of the climate since the formation of Earth. It is thus an important skill for a modeller to be able to select the processes that must be explicitly included compared to those that can be neglected or represented in a simplified way. This choice is of course based on the scientific goal of the study. However, it also depends on technical issues since the most sophisticated models require a lot of computational power: even on the largest computer presently available, the models cannot be routinely used for periods longer than a few centuries to millennia. On longer time scales, or when quite a large number of experiments are needed, it is thus necessary to user simpler and faster models. Furthermore, it is often very illuminating to deliberately design a model that includes only the most important properties, so as to understand in depth the nature of a feedback or the complex interaction between the various components of the system. This is also the reason why simple models are often used to analyse the results of more complex models in which the fundamental characteristics of the system could be hidden by the number of processes represented and the details provided.
    Modellers have first to decide the variables or processes to be taken into account and those that will be taken as constants. This provides a method of classifying the models as a function of the components that are represented interactively. In the majority of climate studies, at least the physical behaviour of the atmosphere, ocean and sea ice must be represented. In addition, the terrestrial and marine carbon cycles, the dynamic vegetation and the ice sheet components are more and more regularly included, leading to what are called Earth-system models.

    Figure 3.2: Types of climate model.

    A second way of differentiating between models is related to the complexity of the processes that are included (Fig. 3.2). At one end of the spectrum, General Circulation Models (GCMs) try to account for all the important properties of the system at the highest affordable resolution. The term GCM was introduced because one of the first goals of these models is to simulate the three dimensional structure of winds and currents realistically. They have classically been divided into Atmospheric General Circulation Models (AGCMs) and Ocean General Circulation Models (OGCMs). For climate studies using interactive atmospheric and oceanic components, the acronyms AOGCM (Atmosphere Ocean General Circulation Model) and the broader CGCM (Coupled General Circulation Model) are generally chosen.
    At the other end of the spectrum, simple climate models (such as the Energy Balance Models, or EBMs, see section 3.2.1) propose a highly simplified version of the dynamic of the climate system. The variables are averaged over large regions, sometimes over the whole Earth, and many processes are not represented or accounted for by the parameterizations. EBMs thus include a relatively small number of degree of freedom.
    EMICs (Earth Models of Intermediate Complexity) are located between those two extremes. They are based on a more complex representation of the system than EBMs but include simplifications and parameterisations for some processes that are explicitly accounted for in GCMs. Actually, the EMICs form the broader category of models. Some of them are relatively close to simple models, while others could be considered as slightly degraded GCMs.
    When employed correctly, all the model types can produce useful information on the behaviour of the climate system. There is no perfect model, suitable for all purposes. This is why a wide range of climate models exists, forming what is called the spectrum or the hierarchy of models that will be described in section 3.2. Depending on the objective or the question, one type of models could be selected. The best type of model to use depends on the objective or the question. On the other hand, combining the results from various types of models is often the best way to gain a deep understanding of the dominant processes in action.

    Some processes are not explicitly included in models because of simplifications, lack of knowledge of the mechanisms, or because the spatial resolution of the model is not high enough to include them. To take the first order effects of these processes into account, they are represented by parameterisations in models. See sections 3.1.1, 3.1.2, 3.2.2 and 3.3.1.

    Furthermore, many processes are still not sufficiently well-known to include their detailed behaviour in models. As a consequence, parameterisations have to be designed, based on empirical evidence and/or on theoretical arguments, to account for the large-scale influence of those processes not included explicitly. Because these parameterizations reproduce only the first order effects and are usually not valid for all possible conditions, they are often a large source of considerable uncertainty in models.

    Feel free to browse forward and backward from this page on this site, as much as interests you.

    Questions to consider:
    If you were interested in modeling El Nino, what type of model might you choose?
    If you were interested in modeling the glacial-interglacial climate cycles of the last million years, what type of model might you choose?
    If you were interested in modeling the average surface temperature of Mars, what type of model might you choose?
    If you were interested in modeling deep ocean circulation (the “thermohaline circulation” or “meridional overturning circulation”), what type of model might you choose?

    Unless you are a climate modeler already, most of the information you will encounter related to climate models is the distilled output from those models. The output you see might be, say, an xy plot showing the value of some variable (e.g. temperature, sea level, sea ice, precipitation…) over time. Or the output might be a map (or a series of maps) showing variations in space (and time). Or, if you get into reading modeling papers, the output might be a range of estimates for some particular parameter or variable of interest. Here we will look at some examples of climate model output, and compare that information to observations. You will use two relatively simple interactive climate models to generate future scenarios.
    Learning Goals
    By the end of this section, you will be able to:
    1 Compare model output to observations.
    2 Describe future temperature forecasts from climate models.
    3 Use a relatively simple climate model to answer questions about stock and flow of carbon to and from the atmosphere.
    4 Use a relatively simple model to generate “What if…” scenarios for the future, that keep global surface temperatures below 2°C above preindustrial values.


    Dr Sara Harris: Welcome to this lesson, where we're going
    to take a look at some output from climate models.
    So what do we get out of climate models?
    And how might that information be useful?
    Well, if we're using climate models to look into the future,
    we get estimates of different climate variables, like temperature or sea
    level, at times in the future.
    And those estimates represent a range of possibilities,
    with some values tagged as more likely than others.
    The future isn't entirely unpredictable.
    Some outcomes really are more likely than others.
    First, we'll look at how well climate models do.
    Here's one example of checking model output against observations.
    This is a compilation from the Intergovernmental Panel
    on Climate Change in their 2007 report.
    The vertical axis is temperature anomalies, which just means difference
    from a baseline.
    Which, in this case, is the average of 1901 to 1950 temperatures.
    The black line is temperature anomaly observations since 1900.
    So this is based on measured temperatures.
    Then in the yellow, we have output from climate models.
    There are actually 58 different yellow lines.
    And these are model runs from 14 different models, each of which
    was constructed somewhat differently, with different assumptions
    in the models and different choices for parametrizations.
    The red line shows the average of all those yellow model runs.
    One thing to note is that the red line from the models
    tracks the black line-- which is from the observations-- pretty well.
    They don't agree every year, but the trends over this time period do agree.
    And there are actually good reasons that they don't agree every year.
    There's natural year-to-year variability in the climate system,
    so the temperatures do go up and down around the longer-term average.
    The climate models do actually reproduce the nature
    of that year-to-year variability, just not the exact timing.
    However, if there's a particular known event that influences the climate,
    and if that event is included in the climate model,
    they do a good job reproducing the timing.
    The example shown here are the four vertical lines,
    which represent the times of four different large volcanic eruptions
    in the 20th century.
    Volcanic eruptions emit sulfates into the atmosphere, which are reflective,
    and therefore cause temporary cooling, which
    is seen both in the observations and the model output--
    cooling after each of these eruptions.
    Another important point to make, here, is that a single run of a single model
    is less compelling than multiple slightly different runs
    of multiple models with different approaches to modeling.
    Modeling projects now incorporate multiple models and multiple runs
    with different combinations of values for different variables
    in order to capture the probable range, rather than choosing just one.
    This approach helps increase our confidence in the model output.
    If the models can reproduce historical observations,
    then climate modeling can help with sorting out
    attribution for climate change.
    One clear hypothesis to test is whether or not the observed changes in climate
    can be accounted for solely by natural factors.
    The two main natural factors are solar variability from sunspot cycles, which
    change the amount of incoming solar energy by a little bit,
    and volcanic eruptions, which if they're big, cause short-term cooling.
    So here we have on the top, the figure we already saw.
    This shows temperature observations in black and average model
    temperatures in red.
    These models were run using inputs that included solar variability, volcanoes,
    and also, human activities.
    The bottom plot, though, shows the model output
    when the models only included solar variability and volcanoes.
    The story here is that if global temperature
    changes over the last several decades were
    driven by natural variability of the sun and volcanoes,
    we would have seen a small cooling-- that's the blue line--
    rather than the warming that's actually observed.
    When human activities are included in the climate models,
    like in the top panel, the models consistently
    reproduce the observed warming.
    Keeping on the temperature theme, back in 1988,
    James Hansen produced some projections of what future climate might look like.
    And now, time has passed.
    More real world observations have been collected.
    And the fact that there's a model projection done back in 1988,
    allows us to have a look at how well those projections ended up
    matching reality.
    So imagine yourself in 1988 thinking about the range of possibilities
    for the future.
    Or imagine yourself now creating projections for the future.
    What range of possibilities would you generate?
    So back then, Hansen gave three future scenarios.
    The scenarios represent different human CO2 emission pathways.
    In scenario A, the model was told to assume exponential growth in emissions.
    In scenario B, the model was told that the growth rate in emissions
    would slow down and the rate of increase would stabilize,
    but emissions would still increase.
    For scenario C, the model was told that greenhouse gas emissions would
    decrease starting around the year 2000.
    So how did the model do?
    It turned out that as time passed, our actual greenhouse
    gas emissions came closest to following scenario
    B. So have a look at scenario B. The temperature projections for scenario
    B are a bit higher than the actual observations turned out to be.
    OK, so why is that?
    Remember that climate models are constructed by people.
    And they are continually revised based on new information.
    Hansen's 1988 model used a fairly high value for the climate sensitivity,
    which you'll recall is the temperature change that
    happens in response to a change in energy
    after the system has reached equilibrium again.
    The typical central value for climate sensitivity--
    which we're using in this course-- is about 3/4
    of a degree Celsius for every additional watt per meter squared.
    Hansen's 1988 model used a higher climate
    sensitivity of about a full degree per watt per meter squared.
    So the model did produce higher future temperature estimates.
    One way we can interpret this comparison is that perhaps earth's climate
    sensitivity really is closer to that central value of 3/4
    of a degree per watt per meter squared.
    Keep in mind, however, that it hasn't been
    a tremendously long time since 1988.
    And it will be worth reexamining this comparison again in the future.
    Here's another example of a comparison between observations and models.
    This time looking at sea ice extent in the Arctic in September.
    We saw the observational data here before.
    That's the red line, and we've added two more data points
    for the record-breaking years of 2007 and 2012.
    The model output is in blue, with the light blue band
    showing the range of 18 model projections for Arctic sea ice,
    with the average of the models indicated by the darker dashed line.
    This comparison shows that although the models agreed with the data
    in the early part of the record-- the 1950s, '60s, and early '70s--
    the models don't do a very good job projecting
    the real observed rate of sea ice lost in the past few decades.
    The models do show a decline, but they're
    conservative in that they don't show nearly as steep a decline
    as actually occurred.
    So faced with this kind of mismatch, modelers
    need to go back and ask what processes were not as well represented
    in the model as they could be.
    And here's an example we've looked at before-- the IPCC
    projections of sea level made back in 1990
    and how those projections have fared.
    Back in 1990, the IPCC essentially didn't incorporate some components
    of ice melts on land, and thus the projections
    made turned out to be conservative and underestimated the sea level
    rise as time passed.
    And we so something like this in an earlier lesson--
    data from just the past four decades.
    They were maps of average surface temperatures,
    which showed that each successive decade was warmer than the last.
    Have a look at this animation which comes from NASA.
    In about 36 seconds, it shows a global map of temperature changes from 1880
    through the present, then modeled on out into the future up to the year 2100.
    The orange and red colors are warmer than the baseline and the blue colors
    are cooler than the baseline.
    In particular, see if you can pick out patterns.
    What part of the globe is warming most rapidly?
    Compare the land to the ocean.
    What we see in general is a continuation of the observed faster warming
    at northern high latitudes and more warming over land than ocean.
    The frames in this animation that are in the future
    are data against which we can check the model once the future's here.
    To summarize, if model output compares well
    with observations in the real world, that
    helps increase our confidence that the model
    does a reasonable job representing the processes going on
    in the climate system.
    For example, a climate model that can reproduce the global temperature
    record of the past century, is more likely to reasonably forecast
    the future then a model that can't reproduce known observations.
    No model will end up uncannily predicting exactly what will happen,
    but they can provide ranges of possibility.
    And that information can be useful for human communities
    to plan and implement mitigation and adaptation strategies.

    Explore “The Very, Very Simple Climate Model” from UCAR
    Go to this link to access the model:
    (You need a Flash plugin to use this interactive model)

    What to do:
    1 Explore all the features of this model. Click all the buttons. Play around for a while.
    2 Set up for a model run out to the year 2110 in which you keep the Carbon Dioxide Emissions constant at the default value of 9.35 Gton C per year.
    1 With constant carbon emissions, what do you expect to happen to CO2 concentration and to temperature over time?
    2 Run the model and see if your expectations match what happens.
    3 If not, why not?
    3 Using the model, try to estimate a Carbon Dioxide Emissions value (in Gton C per year) for which inflow of carbon to the atmosphere equals outflow from the atmosphere (according to this model)? How will you be able to tell?
    4 What happens to CO2 concentration and Temperature if you change the “Ocean Absorption Rate” (under “Change Settings”)? Make a prediction before you run the model. Then run it and see.
    5 Compare possible values for the climate sensitivity. According to this model, how does the temperature difference between 1990 and 2110 vary across the range of climate sensitivities estimated by the IPCC in 2013 (about 1.5-4.5°C per CO2 doubling, with 3°C as the best estimate given by the IPCC in 2007 (the 2013 Summary for Policymakers gave the same likely range of sensitivity but no best estimate)? You’ll have to make choices about the other settings.

    Explore “The Very, Very Simple Climate Model” from UCAR
    Go to this link to access the model:
    (You need a Flash plugin to use this interactive model)

    What to do:
    1 Explore all the features of this model. Click all the buttons. Play around for a while.
    2 Set up for a model run out to the year 2110 in which you keep the Carbon Dioxide Emissions constant at the default value of 9.35 Gton C per year.
    1 With constant carbon emissions, what do you expect to happen to CO2 concentration and to temperature over time?
    2 Run the model and see if your expectations match what happens.
    3 If not, why not?
    3 Using the model, try to estimate a Carbon Dioxide Emissions value (in Gton C per year) for which inflow of carbon to the atmosphere equals outflow from the atmosphere (according to this model)? How will you be able to tell?
    4 What happens to CO2 concentration and Temperature if you change the “Ocean Absorption Rate” (under “Change Settings”)? Make a prediction before you run the model. Then run it and see.
    5 Compare possible values for the climate sensitivity. According to this model, how does the temperature difference between 1990 and 2110 vary across the range of climate sensitivities estimated by the IPCC in 2013 (about 1.5-4.5°C per CO2 doubling, with 3°C as the best estimate given by the IPCC in 2007 (the 2013 Summary for Policymakers gave the same likely range of sensitivity but no best estimate)? You’ll have to make choices about the other settings.

    In this section, we’ll look at two main approaches to generating future scenarios: those from the Special Report on Emissions Scenarios, and the newer Representative Concentration Pathways approach. Both are attempts to define a range of possible scenarios for the future, which are then used in climate models, and the output from the climate models yields information that helps us think about our future choices.
    Learning Goals:
    By the end of this section, you will be able to:
    1 Explain how emissions scenarios are created and used to drive climate models.
    2 Describe the families of scenarios defined by the Special Report on Emissions Scenarios.
    3 Explain what Representative Concentration Pathways represent.


    Dr Sara Harris: Welcome to this next lesson.
    We're going to take a look at some future scenarios now.
    One of the sticky challenges in looking forward into the future
    and projecting the range of possible outcomes for climate
    is that we don't really know what we're going
    to do in terms of our emissions of greenhouse gases to the atmosphere.
    So people have made efforts to describe a range of likely possibilities.
    It's not that any particular one of the possibilities
    is going to become the future, nor is one possibility necessarily
    more likely than the others.
    But defining a range allows us to think about what that future world might
    look like and which of the future possibilities
    comes closest to how we imagine we'd like the future to look.
    So we're going to talk about emissions scenarios.
    Emissions scenarios essentially define some pathway
    for human emissions of greenhouse gases over time.
    Then that information is fed into climate models, which
    then can calculate things like future global temperatures or future sea level
    or precipitation patterns at different times in the future,
    based on those hypothetical future emissions.
    We're going to talk about two approaches to emissions scenarios here.
    One approach is from the Special Report on Emission Scenarios from 2000,
    and the other is called Representative Concentration
    Pathways, which are a newer approach.
    Here's the approach used by the Special Report on Emissions
    Scenarios, which were utilized in the IPCC's third and fourth assessment
    Essentially, groups of people sat down and defined some future storylines.
    The storylines were based on possible socioeconomic change in the future.
    Like whether the world's economies would become more integrated over time.
    Or whether regions would become more economically isolated.
    They included factors like demographics, and possible changes
    in human populations, in resource use, in the mix of energy types
    that we might use in the future.
    Possible policy change has a huge range of human factors.
    Then taking these storylines, people estimated
    what the implications would be for future greenhouse gas emissions
    for each story.
    And in this way, they defined emissions scenarios
    that were linked to the storylines.
    These estimates of emissions then were fed into the climate models.
    This is a simplified schematic of the SRES families.
    The two on the top, A1 and A2, thematically
    tend toward more economic growth in their story lines.
    And the two on the bottom, B1 and B1, tend more
    toward environmental protection.
    The two on the left, A1 and B1, describe worlds
    that are more globally interconnected.
    And the two on the right describe futures
    where regional connections are more important.
    Within the A1 family, there are three scenarios
    that differ in how we use energy in the future.
    One of them represents a balance between fossil and non-fossil energy.
    Then there is A1 F1, which describes the future
    with intensive use of fossil fuels.
    This one is typically nicknamed the business-as-usual scenario.
    And there's T, in which we transition to non-fossil energy sources.
    There are no probabilities nor preferences
    attached to any of the scenarios.
    The attempt is to capture a range of possibilities
    and use them to learn about what the future might hold.
    Here's an example of some output from climate models using
    a selection of the SRES scenarios from the IPCC 2007 report.
    The vertical axis is warming relative to the global average from 1980 to 1999.
    And in the time period between 2000 and 2100,
    you can see that the various scenarios might take us
    on different temperature paths.
    There's quite a lot of information on this plot.
    The red, green, and blue are three different scenarios.
    And the lighter shaded colors around each line
    are a range of outcomes for each scenario from a bunch
    of different climate models.
    The yellow is actually a hypothetical story
    in which greenhouse gas concentrations are held constant at the values
    they had in the year 2000.
    On the right are the outcomes in the year 2100 for the three series
    shown on the plot plus 3 more scenarios, including the business-as-usual one,
    which is on the far right.
    It's the one of these six that ends up at the highest temperatures.
    Again, scenarios like these help us think about
    and imagine the future possibilities.
    And again, none of the scenarios are officially more likely than any others.
    Though as time goes on, we'll be able to assess which turns out
    to be closer to our true path.
    Here's another newer approach to defining emissions scenarios.
    In this approach, what people have done is
    they've defined a condition for Earth in the year 2100.
    And that condition is defined by how much extra energy might
    be added to the climate system by 2100, compared to pre-industrial values.
    And then after picking four endpoints, people
    chose what are called Representative Concentration Pathways to get there.
    The concentration part relates to the concentrations of greenhouse gases
    in the atmosphere along the way.
    There are, in fact, many possible pathways,
    many possible arrangements of social and economic and political futures
    that might carry us to those conditions defined for 2100.
    So this approach is somewhat reversed from the SRES approach.
    Rather than defining the stories first, then the implications for greenhouse
    gases, this approach defines the greenhouse gas trajectories,
    then people talk about what variety of human scenarios
    might correspond to those trajectories.
    There's an ongoing exchange of information
    about Concentration Pathways and what human choices might correspond to them.
    So to get an idea about these are CPs.
    They are four trajectories into the future.
    The trajectories include radiative forcing
    from a bunch of different sources, including predicted solar output,
    every one of the different gases in the atmosphere involved
    in energy flows, aerosols, land use change, black carbon on snow,
    a lot of different factors.
    What's plotted here is the radiative forcing from greenhouse gas emissions
    in watts per meter squared.
    The black line is the historical data since 1900.
    And then each of the colored lines goes along a representative concentration
    The top one is named RCP 8.5, because if you follow that pathway, by 2100,
    we end up with radiative forcing 8.5 watts per meter squared higher than we
    had prior to the Industrial Revolution.
    The second one down, the orange one, RCP 6,
    a pathway by which we'd end up with six watts per meter
    squared more than pre-industrial.
    Then there's RCP 4.5, and at the bottom, there's
    RCP 3PD, which is the only one that peaks before 2100 and then declines.
    That's the PD, for peak and decline.
    So what kinds of emissions each year would carry us along those pathways?
    Here are the representative annual emissions
    for each of the four pathways in units of gigatons.
    That's billions of tons of carbon per year.
    We're somewhere in near 10 billion tons per year now.
    RCP 8.5 takes us up close to 30 billion tons of carbon each year.
    The other three pathways show declines in emission rates,
    starting prior to 2100, with RCP 3PD starting to decline quite soon,
    with emissions going negative by 2100.
    Again, these are simply illustrative possible choices of action
    that we might take.
    And next, how do those emissions translate
    into atmospheric CO2 concentrations?
    We not only have to take into account our inflow by emissions,
    but we also need to incorporate things like how much carbon land
    plants and the oceans will continue to take out of the atmosphere each year.
    For RCP 3PD, atmospheric concentrations of carbon dioxide
    actually declined by 2100.
    And for RCP 4.5, they stabilized at about 540 parts per million,
    shortly after 2100.
    540 is just a tad shy of doubling CO2 since pre-industrial times.
    Going up, RCP 6 takes us past 700 parts per million.
    And RCP 8.5 keeps rising for the next couple of hundred years.
    But keep in mind as we look at the next plot,
    that stabilizing CO2 doesn't translate into stabilizing temperature.
    Because for temperature to stabilize, we need
    to balance inflows and outflows of energy.
    So the RCPs get defined and the pathways get fed into a climate model
    to see what happens.
    For example, what happens to global surface warming?
    This particular example uses the climate sensitivity
    of three degrees Celsius per doubling of CO2,
    which is the same as what we've been using, just expressed differently.
    In just one of the scenarios, that's RCP 3PD, temperature stabilizes by 2100.
    And other research shows that beyond that, into the future,
    temperatures decline along that pathway.
    RCP 3PD is also the only one of these Representative Concentration Pathways
    in which global temperatures don't exceed two degrees Celsius warmer
    than pre-industrial values, which is an often discussed boundary that's
    likely undesirable to cross.
    In the other three scenarios, temperatures
    continue to rise for longer.
    To summarize, we have a desire to peer into the future.
    Climate models can help us do that, but they need information
    about possible pathways for future emissions.
    We've described two approaches to defining those scenarios.
    The SRES families of scenarios start by telling
    a story about future human activities and what our societies might look like.
    From those stories, people estimate what the scenarios would likely
    mean for greenhouse gas emissions.
    And those numbers are used in climate models.
    The Representative Concentration Pathway approach is different.
    First, it defines endpoints in terms of the radiative forcing
    above pre-industrial times that might be happening in 2100.
    Then it works backward to define representative pathways that
    lead there.
    Again, those pieces of information go into climate models
    in order to estimate the response of the climate system to our actions.
    How does this help?
    What these scenarios do is give us glimpses and "what if" scenarios.
    What can we expect if we approximately follow one pathway or another?
    They can also help us think about what we imagine
    we'd like to see in our future world

    Explore the RCP database
    You can read about the Representative Concentration Pathways Database here:
    And you can explore the data yourself here:
    Here’s an example from that page, comparing the four RCPs in terms of Total CO2 emissions. Note: Units Pg C/yr = petagrams carbon per year. These are equivalent to Gton C/yr, which you’ve seen elsewhere in this course.

    Some possibilities:
    1 Compare the four RCPs in terms of the radiative forcing from different greenhouse gases.
    2 Compare the four RCPs in terms of emissions of different climate-related stuff (different types of gases, aerosols, particulates).
    3 What do you want to know more about?

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    Representative Concentration Pathways Database
    A database with scenarios from the integrated assessment community to expedite climate change assessments

    ©2011 iStockphoto LP

    In May 2007 the Intergovernmental Panel on Climate Change (IPCC) ask the international scientific community to develop a new set of climate scenarios  for the IPCC Fifth Assessment Report (AR5), expected to be published in 2013/2014.
    The new scenarios are called the Representative Concentration Pathways (RCPs).

    The RCP database, hosted at IIASA, represents several years of collaboration between internationally renowned scientific teams coordinated by the Integrated Assessment Modeling Consortium (IAMC).
    In its first three months online, the RCP database was viewed by over 16,000 people.
    The different scenarios (RCPs) underpinning the climate simulations of the AR5 can be viewed and compared online at the level of five world regions, 13 sectors, and with 0.5º × 0.5º resolution spatial maps.

    Four RCPs based on different radiative forcing levels were chosen from the literature. One of these  was developed at IIASA using the MESSAGE model.
    The RCP database, which documents the emissions, concentrations, and land-cover change projections based on these four RCPs, is intended to provide input to climate models.
    They will also facilitate and expedite future climate change assessments across the integrated assessment community.
    About the RCP database
    The RCPs, which replace and extend the scenarios used in earlier IPCC assessments, are compatible with the full range of stabilization, mitigation, and baseline emission scenarios available in the current scientific literature. The RCP levels chosen, a brief description, a reference to the underlying publication, and the modeling tool used are shown in Table 1 below.

    How the RCP database works

    The database, which was first released in May 2009, includes harmonized and consolidated data for the four RCPs, comprising emissions pathways starting from an identical base year (2000) to 2100. The database covers emissions of well-mixed greenhouse gases (GHGs) such as carbon dioxide, nitrous oxide and fluorinated gases at the level of five world regions and short-lived GHGs as well as radiatively and chemically active gases (black and organic carbon, methane, sulfur, nitrogen oxides, volatile organic compounds, carbon monoxide and ammonia) in addition to spatial patterns.

    Radiative forcing and concentrations of GHGs are given for the RCPs up to the year 2100, and are extended for climate modeling experiments to 2300. Wherever available, historical information is provided back to the year 1850. The data, verified for quality and consistency, can be downloaded in various formats, including Microsoft Excel, scalable vector graphics, and netCDF format, free of charge at the IIASA Web site, subject to provision of an e-mail address. The RCP database was developed by the Energy Program and Transitions to New Technologies Program at IIASA.


    "Radiative forcing is a measure of the influence a factor has in altering the balance of incoming and outgoing energy in the Earth-Atmosphere system and is an index of the importance of this factor as a potential climate change mechanism," according to the IPCC. It is expressed in watts per square meter (W/m2).

    Variations in the sun's output, polar ice, and natural events like volcanic eruptions influence the Earth’s radiative balance, as do human activities that result in, for example, greenhouse gas emissions, pollution, and deforestation. Changes in the resulting radiative forcing level are measured at the top of the atmosphere and calculated by subtracting the energy radiating out from Earth from the energy flowing in and comparing the result against the IPCC base year of 1750 before the onset of the industrialization, where radiative forcing is assumed to be zero. If the level of radiative forcing varies from zero, then some warming or cooling is occurring. Scientists can directly measure the amount by which the Earth’s energy budget is out of balance and calculate the effects that this could have for a range of human and environmental indicators. The four different RCPs were developed to represent the world at different forcing levels in the future. Radiative forcing leading to 8.5 W/m2 in 2100, as studied by IIASA using the MESSAGE model, is the high end of the radiative forcing range being used.

    Table 1. The RCP Database provides excellent data visualization capabilities.

    RCP level
    Reference/Modeling tool
    Rising radiative forcing pathway leading to 8.5 W/m2 in 2100.
    Riahi et al. (2007) – MESSAGE
    Stabilization without overshoot pathway to 6 W/m2 at stabilization after 2100
    Fujino et al. (2006) and Hijioka et al. (2008) – AIM
    Stabilization without overshoot pathway to 4.5 W/m2 at stabilization after 2100
    Clarke et al. (2007) – MiniCAM
    Peak in radiative forcing at ~3 W/m2 before 2100 and decline
    van Vuuren et al. (2006, 2007) – IMAGE

    The main challenge in the RCP modeling process is to expedite the research process for AR5 and beyond. For the IPCC Special Report on Emission Scenarios (SRES), published back in the year 2000, four alternative scenario families were developed, characterized by socioeconomic storylines that assumed different directions of future development. The resulting climate scenarios were then applied to impacts, adaptation, and vulnerability (IAV) research. This sequential approach—from socioeconomic factors and emissions, to climate projections, and finally to impact assessment—became time-consuming. Now the RCPs are identified "up-front," and the climate modeling community is able to proceed with new climate change projections at the same time as new work is being carried out within the Integrated Assessment Modeling (IAM) and Impact, Adaptation, and Vulnerability (IAV) communities.

    If you want to delve into the nitty-gritty of SRES…

    Here’s a link to the IPCC, 2000 Special Report on Emissions Scenarios:
    Or you can read the much shorter Wikipedia summary:

    Special Report on Emissions Scenarios
    From Wikipedia, the free encyclopedia

    Jump to: navigation, search
    This article is about the Special Report on Emissions Scenarios (SRES). For other uses of this acronym, see SRES (disambiguation).
    See also: Global warming
    The Special Report on Emissions Scenarios (SRES) is a report by the Intergovernmental Panel on Climate Change (IPCC) that was published in 2000. The greenhouse gas emissions scenarios described in the Report have been used to make projections of possible future climate change. The SRES scenarios, as they are often called, were used in the IPCC Third Assessment Report (TAR), published in 2001, and in the IPCC Fourth Assessment Report (AR4), published in 2007.
    The SRES scenarios were designed to improve upon some aspects of the IS92 scenarios, which had been used in the earlier IPCC Second Assessment Report of 1995.[1] The SRES scenarios are "baseline" (or "reference") scenarios, which means that they do not take into account any current or future measures to limit greenhouse gas (GHG) emissions (e.g., the Kyoto Protocol to the United Nations Framework Convention on Climate Change).[2]
    Emissions projections of the SRES scenarios are broadly comparable in range to the baseline emissions scenarios that have been developed by the scientific community.[3] The SRES scenarios, however, do not encompass the full range of possible futures: emissions may change less than the scenarios imply, or they could change more.[4]
    SRES was superseded by Representative Concentration Pathways (RCPs) in 2014.

    Contents  [hide]
    Scenario families
    SRES scenarios and climate change initiatives
    Atmospheric GHG concentrations
    Observed emissions rates
    Views and analysis
    MER and PPP
    Availability of fossil fuels
    Select Committee report
    Comparison with a “no policy” scenario
    Post-SRES projections
    See also
    External links
    The four SRES scenario families[5][6][7] of the Fourth Assessment Report vs. projected global average surface warming until 2100
    (Summary; PDF)

    More economic focus

    More environmental focus
    (homogeneous world)
    rapid economic growth
    (groups: A1T; A1B; A1Fl)
    1.4 - 6.4 °C
    global environmental sustainability
    1.1 - 2.9 °C
    (heterogeneous world)
    regionally oriented
    economic development
    2.0 - 5.4 °C
    local environmental sustainability
    1.4 - 3.8 °C
    Because projections of climate change depend heavily upon future human activity, climate models are run against scenarios. There are 40 different scenarios, each making different assumptions for future greenhouse gas pollution, land-use and other driving forces. Assumptions about future technological development as well as the future economic development are thus made for each scenario. Most include an increase in the consumption of fossil fuels; some versions of B1 have lower levels of consumption by 2100 than in 1990 [1]. Overall global GDP will grow by a factor of between 5-25 in the emissions scenarios.
    These emissions scenarios are organized into families, which contain scenarios that are similar to each other in some respects. IPCC assessment report projections for the future are often made in the context of a specific scenario family.
    According to the IPCC, all SRES scenarios are considered "neutral".[8] None of the SRES scenarios project future disasters or catastrophes, e.g., wars and conflicts, and/or environmental collapse.[8]
    The scenarios are not described by the IPCC as representing good or bad pathways of future social and economic development.[9]
    Scenario families[edit]
    Scenario families contain individual scenarios with common themes. The six families of scenarios discussed in the IPCC's Third Assessment Report (TAR) and Fourth Assessment Report (AR4) are A1FI, A1B, A1T, A2, B1, and B2.
    The IPCC did not state that any of the SRES scenarios were more likely to occur than others, therefore none of the SRES scenarios represent a "best guess" of future emissions.[10]
    Scenario descriptions are based on those in AR4, which are identical to those in TAR.[11]
    The A1 scenarios are of a more integrated world. The A1 family of scenarios is characterized by:
    Rapid economic growth.
    A global population that reaches 9 billion in 2050 and then gradually declines.
    The quick spread of new and efficient technologies.
    A convergent world - income and way of life converge between regions. Extensive social and cultural interactions worldwide.
    There are subsets to the A1 family based on their technological emphasis:
    A1FI - An emphasis on fossil-fuels (Fossil Intensive).
    A1B - A balanced emphasis on all energy sources.
    A1T - Emphasis on non-fossil energy sources.
    The A2 scenarios are of a more divided world. The A2 family of scenarios is characterized by:
    A world of independently operating, self-reliant nations.
    Continuously increasing population.
    Regionally oriented economic development.
    The B1 scenarios are of a world more integrated, and more ecologically friendly. The B1 scenarios are characterized by:
    Rapid economic growth as in A1, but with rapid changes towards a service and information economy.
    Population rising to 9 billion in 2050 and then declining as in A1.
    Reductions in material intensity and the introduction of clean and resource efficient technologies.
    An emphasis on global solutions to economic, social and environmental stability.
    The B2 scenarios are of a world more divided, but more ecologically friendly. The B2 scenarios are characterized by:
    Continuously increasing population, but at a slower rate than in A2.
    Emphasis on local rather than global solutions to economic, social and environmental stability.
    Intermediate levels of economic development.
    Less rapid and more fragmented technological change than in A1 and B1.
    SRES scenarios and climate change initiatives[edit]
    While some scenarios assume a more environmentally friendly world than others, none include any climate-specific initiatives, such as the Kyoto Protocol.[citation needed]
    Atmospheric GHG concentrations[edit]

    Projected changes over the 21st century in the atmospheric concentrations of three greenhouse gases: carbon dioxide (chemical formula: CO2), methane (CH4), and nitrous oxide (N2O). These projections by the United States Environmental Protection Agency are based on emissions scenarios contained in the SRES.[12]
    The SRES scenarios have been used to project future atmospheric GHG concentrations. Under the six illustrative SRES scenarios, the IPCC Third Assessment Report (2001)[13] projects the atmospheric concentration of carbon dioxide (CO
    2) in the year 2100 as between 540 and 970 parts per million (ppm). In this estimate, there are uncertainties over the future removal of carbon from the atmosphere by carbon sinks. There are also uncertainties regarding future changes in the Earth's biosphere and feedbacks in the climate system. The estimated effect of these uncertainties mean that the total projected concentration ranges from 490 to 1,260 ppm.[13] This compares to a pre-industrial (taken as the year 1750) concentration of about 280 ppm, and a concentration of about 368 ppm in the year 2000.
    The United States Environmental Protection Agency has also produced projections of future atmospheric GHG concentrations using the SRES scenarios.[12] These projections are shown opposite, and are subject to the uncertainty described earlier regarding the future role of carbon sinks and changes to the Earth's biosphere.
    Observed emissions rates[edit]
    See also: Greenhouse gas § Regional and national attribution of emissions and economics of global warming § Trends and projections
    Between the 1990s and 2000s, the growth rate in CO2 emissions from fossil fuel burning and industrial processes increased (McMullen and Jabbour, 2009, p. 8).[14] The growth rate from 1990-1999 averaged 1.1% per year.
    Between the years 2000-2009, growth in CO
    2 emissions from fossil fuel burning was, on average, 3% per year, which exceeds the growth estimated by 35 of the 40 SRES scenarios (34 if the trend is computed with end points instead of a linear fit).[15] Human-caused greenhouse gas emissions set a record in 2010,[16] a 6% jump on 2009 emissions, exceeding even the "worst case" scenario cited in the IPCC Fourth Assessment Report.
    Views and analysis[edit]
    MER and PPP[edit]
    The SRES scenarios were criticised by Ian Castles, and David Henderson.[17][18][19] The core of their critique was the use of market exchange rates (MER) for international comparison, in lieu of the theoretically favoured PPP exchange rate which corrects for differences in purchasing power.[20] The IPCC rebutted this criticism[21][22][23]
    The positions in the debate can be summarised as follows. Using MER, the SRES scenarios overstate income differences in past and present, and overestimate future economic growth in developing countries. This, Castles and Henderson argue, leads to an overestimate of future greenhouse gas emissions. The IPCC would have made climate change more dramatic than it is.
    However, the difference in economic growth is offset by a difference in energy intensity. Some say these two opposite effects fully cancel,[24] some say this is only partial.[25] Overall, the effect of a switch from MER to PPP is likely to have a minimal effect on carbon dioxide concentrations in the atmosphere.[26]
    But even if global climate change is not affected, it has been argued[27] that the regional distribution of emissions and incomes is very different between an MER and a PPP scenario. This would influence the political debate: In a PPP scenario, China and India have a much smaller share of global emissions. It would also affect vulnerability to climate change: in a PPP scenario, poor countries grow slower and would face greater impacts.
    Availability of fossil fuels[edit]
    As part of the SRES, IPCC authors assessed the potential future availability of fossil fuels for energy use.[28] The issue of whether or not the future availability of fossil fuels would limit future carbon emissions was considered in the Third Assessment Report;[29] it concluded that limits on fossil fuel resources would not limit carbon emissions in the 21st century.[29] Their estimate for conventional coal reserves was around 1,000 gigatonnes of carbon (GtC), with an upper estimate of between 3,500 and 4,000 GtC.[30] This compares with cumulative carbon emissions up to the year 2100 of about 1,000 GtC for the SRES B1 scenario, and about 2,000 GtC for the SRES A1FI scenario.
    The carbon in proven conventional oil and gas reserves was estimated to be much less than the cumulative carbon emissions associated with atmospheric stabilization of CO2 concentrations at levels of 450 ppmv or higher.[29] The Third Assessment Report suggested[29] that the future makeup of the world's energy mix would determine whether or not greenhouse gas concentrations were stabilized in the 21st century. The future energy mix might be based more on the exploitation of unconventional oil and gas (e.g., oil sands, shale oil, tight oil, shale gas), or more on the use of non-fossil energy sources, like renewable energy.[29]
    Hook et al. (2009, abstract) criticized the SRES scenarios for being biased towards “exaggerated resource availability” and making “unrealistic expectations on future production outputs from fossil fuels.”[31] Patzek and Croft (2010, p. 3113) made a prediction of future coal production and carbon emissions.[32] In their assessment, all but the lowest emission SRES scenarios projected far too high levels of future coal production and carbon emissions (Patzek and Croft, 2010, pp. 3113–3114). In a discussion paper, Aleklett (2007, p. 17) viewed SRES projections between the years 2020 and 2100 as “absolutely unrealistic”.[33] In Aleklett's analysis, emissions from oil and gas were lower than all of the SRES projections, with emissions from coal much lower than the majority of SRES projections (Aleklett, 2007, p. 2).
    Select Committee report[edit]
    In 2005, the UK Parliament's House of Lords Economics Affairs Select Committee produced a report on the economics of climate change.[34] As part of their inquiry, they took evidence on criticisms of the SRES. Among those who gave evidence to the Committee were Dr Ian Castles, a critic of the SRES scenarios,[35] and Prof Nebojsa Nakicenovic, who co-edited the SRES.[36] IPCC author Dr Chris Hope commented on the SRES A2 scenario, which is one of the higher emissions scenarios of the SRES.[37] Hope assessed and compared the marginal damages of climate change using two versions of the A2 scenario. In one version of the A2 scenario, emissions were as the IPCC projected. In the other version of A2, Hope reduced the IPCC's projected emissions by a half (i.e., 50% of the original A2 scenario). In his integrated assessment model, both of these versions of the A2 scenario lead to almost identical estimates of marginal climate damages (the present-day value of emitting one tonne of CO2 into the atmosphere). Based on this finding, Hope argued that present day climate policy was insensitive to whether or not you accepted the validity of the higher emission SRES scenarios.
    IPCC author Prof Richard Tol commented on the strengths and weaknesses of the SRES scenarios.[38] In his view, the A2 SRES marker scenario was, by far, the most realistic. UK Government departments Defra and HM Treasury argued that case for action on climate change was not undermined by the Castles and Henderson critique of the SRES scenarios.[39] They also commented that unless effective action was taken to curb emissions growth, other bodies, like the International Energy Agency, expected greenhouse gas emissions to continue to rise into the future.
    Comparison with a “no policy” scenario[edit]
    In a report published by the MIT Joint Program on the Science and Policy of Global Change, Webster et al. (2008) compared the SRES scenarios with their own “no policy” scenario.[40] Their no-policy scenario assumes that in the future, the world does nothing to limit greenhouse gas emissions. They found that most of the SRES scenarios were outside of the 90% probability range of their no-policy scenario (Webster et al., 2008, p. 1). Most of the SRES scenarios were consistent with efforts to stabilize greenhouse gas concentrations in the atmosphere. Webster et al. (2008, p. 54) noted that the SRES scenarios were designed to cover most of the range of future emission levels in the published scientific literature. Many such scenarios in the literature presumably assumed that future efforts would be made to stabilize greenhouse gas concentrations.
    Post-SRES projections[edit]
    Further information: climate change scenario § Quantitative emissions projections
    As part of the IPCC Fourth Assessment Report, the literature on emissions scenarios was assessed. Baseline emissions scenarios published since the SRES were found to be comparable in range to those in the SRES.[41] IPCC (2007)[41] noted that post-SRES scenarios had used lower values for some drivers for emissions, notably population projections. However, of the assessed studies that had incorporated new population projections, changes in other drivers, such as economic growth, resulted in little change in overall emission levels.

    In this section, we are going to do some back-of-the-envelope estimations ("back-of-the-envelope" means a rough estimate using some justifiable assumptions). We are going to estimate a carbon emissions budget for the future, then apply that budget to each of the RCP scenarios to see how long it lasts. Are any of these exactly what will happen? No. But this exercise allows us to use some fairly simple metrics to make comparisons among future pathways, even though the climate system itself is very complex. We’ll also have a look at the possibilities for the longer term, out tens of thousands of years into the future.
    Learning Goals:
    By the end of this section, you will be able to:
    1 Use a relationship between cumulative carbon emissions and temperature to estimate a remaining carbon emissions budget for humanity.
    2 Compare the carbon budget to the representative concentration pathways for emissions.
    3 Describe the role of human choices in determining what will happen in the upcoming century.
    4 Compare possibilities for future climate over the upcoming tens of thousands of years, depending on the eventual cumulative human carbon emissions.


    DR. SARA HARRIS: Welcome to this next lesson about the nearest future.
    We've had a look at various emissions scenarios.
    Both the SRES scenarios and the Representative Concentration Pathways.
    And we've seen a little bit about what the different trajectories might
    mean for earth's climate in the coming century.
    Here we're going to do a little exploration of data and modeling
    We're going to use a relationship between carbon emissions
    and temperature to conduct a few what-if scenarios along each
    of the Representative Concentration Pathways.
    We've seen some projections for temperature in the upcoming century,
    like these ones.
    Of these four possible pathways only one of them
    appears to keep earth's average temperature below two degrees Celsius
    warmer than pre-industrial values.
    The two-degrees-boundary is a useful one to talk about simply
    because there's been international agreement that if temperatures
    go higher than that we'll be entering the realm of quote,
    dangerous climate change.
    Based on projections of sea level rise, and extreme weather events,
    and other likely outcomes in a warming world.
    There are also those who argue that two degrees is itself too high.
    But here for convenience, we're going to work with that two-degrees-boundary.
    Just as a reminder that's two degrees warmer than average global temperatures
    were at the start of the Industrial Revolution.
    We're part of the way there already.
    How do we get from CO2 emissions to global temperature change?
    We're going to do a little bit of climate modeling ourselves
    using graphs.
    The goal here is to use relationships between CO2 emissions and temperature,
    with this idea of a two degree warming boundary,
    and see what we come up with for a carbon budget for humanity.
    This is going to be a back-of-the-envelope approach.
    It turns out that there's a linear relationship between total carbon
    emitted over time, the cumulative amount of carbon emitted,
    and the final temperature change we get at equilibrium once earth
    is adjusted after the perturbation.
    Two handy things are going on here that help
    yield this nice linear relationship.
    One has to do with how good a greenhouse gas CO2 is as its concentration
    increases more and more.
    If you already have lots of CO2 in the atmosphere, adding more
    makes less and less difference to warming.
    We're kind of losing power as we crank up the CO2.
    It's sort of like if you have three outfielders at a baseball game
    and you add one more.
    Your team is going to catch quite a few more fly balls.
    But if you already have 50 outfielders and you add one more
    it doesn't make as much difference.
    So if you don't have much CO2 to start with, adding some
    makes a bigger difference than if you're starting out with a lot.
    So that kind of complicates things.
    But there's another factor going on which
    counters those diminishing returns.
    This has to do with that issue of how much stays in the atmosphere each year
    and how much the plants and oceans take out.
    At higher and higher CO2 concentrations it looks like less gets taken up.
    So more stays in the atmosphere.
    Making up for the fact that each extra molecule doesn't
    make as much difference as before.
    Anyway, those two things essentially cancel each other out,
    leaving us with a nice linear relationship to play around with.
    This comes from Matthews and others from a paper in 2012.
    They concluded that for every 1,000 gigatons of carbon emitted
    to the atmosphere-- that's cumulative emissions over time-- for every 1,000
    gigatons we get about 1.8 degrees Celsius final temperature rise.
    For 4,000 gigatons we'd get 4 times that temperature rise,
    to 7.2 degrees Celsius.
    So here's a question for you.
    According to this plot about how much total carbon can
    we emit and not exceed the two degrees Celsius threshold?
    Choose the closest answer.

    MY ANSWER : 1,100 G


    SARA HARRIS: If we start on the vertical axis with two degrees,
    go over to the right to the blue line, and then down to the horizontal axis,
    we get the result that cumulative carbon emissions
    of about 1,100 gigatons of carbon corresponds to a two-degree temperature
    So, about 1,100 gigatons of total overall carbon emissions
    yields this two degrees temperature rise.
    Here's data from a previous lesson.
    It's the record of our carbon emissions since 1850,
    with the result that since then, we've emitted about 540 gigatons of carbon.
    So another question.
    How many gigatons of carbon do we have left
    if we're going to stay below two degrees Celsius, according to these data?


    SARA HARRIS: If we've already used 540 gigatons of the budget,
    we have about 560 left.
    We're about halfway there.
    So let's take a look at what the future might hold for our emissions
    and how long that budget might last us.
    Here the annual emissions data for the four representative concentration
    pathways we looked at earlier.
    The black line is the past, and we've emitted a cumulative total
    of 540 gigatons of carbon.
    If in the future we end up following something like the RCP3 peak
    and decline pathway, then we'll end up emitting a cumulative total
    less than 560 gigatons.
    That's the darker green area under the green curve.
    Along that pathway, we won't break the bank.
    We won't run through our entire budget.
    Let's look at the other pathways.
    For RCP 4.5, we use up our budget of 560 gigatons by 2064.
    That's the blue shape.
    For RCP 6, we use up our budget by 2062; that's the orange shape.
    And last, for RCP 8.5 we use up our budget by 2048; that's the red.
    Notice for the last three pathways it would be quite a precipitous change
    to suddenly go from emitting say, 15 gigatons of carbon to the atmosphere
    one year to emitting zero the next.
    That's not going to happen.
    There's inertia in our human systems and we
    don't change things like our energy sources overnight.
    Following the red pathway, for example, would make it very difficult
    to stay below the two degree boundary.
    So this example is just another way of looking at the future.
    We saw previously that the only one of these four pathways that
    keeps the earth's surface temperature less than two degrees Celsius
    above pre-industrial values is the RCP 3 peak and decline pathway.
    And now we've taken a look from the carbon side, which agrees.
    In summary, a handy relationship exists between cumulative carbon emissions
    and the global temperature change that arises from them.
    For every 1,000 gigatons of carbon emitted,
    we get about 1.8 degrees Celsius temperature rise.
    If we consider aiming for a temperature rise
    less than two degrees Celsius above pre-industrial values,
    we have about 568 gigatons of carbon left to emit.
    At the rates defined by the representative concentration pathways,
    we'll finish that off within 50 years unless we end up
    on the RCP 3 peak and decline path.
    At this time, the greatest source of uncertainty regarding our future path
    is uncertainty about our own future actions
    and what choices we'll make today and in the future.

    By Curt Stager, 2012, Nature Education Knowledge 3(10):7
    Here’s the link:
    1 This reading compares two scenarios: (1) cumulative human carbon emissions end up about 1000 Gton C, and (2) cumulative human carbon emissions end up about 5000 GtonC. What are the differences between these two scenarios, over time, for:
    1 Atmospheric CO2 concentration?
    2 Temperature?
    3 Sea level?
    2 Explain what’s going on in Figures 2 and 3 to someone unfamiliar with the topic.
    3 The article briefly mentions what people of the future might think about climate change, and perceived benefits and drawbacks for future humans. What do you think of the long-term tradeoffs mentioned in this article?

    |  Lead Editor:

    What Happens AFTER Global Warming?
    By: Curt Stager © 2012 Nature Education

    Citation: Stager, C. (2012) What Happens AFTER Global Warming? Nature Education Knowledge 3(10):7

    What happens to our heat-trapping fossil fuel emissions after we release them, how long will they persist, and what might life be like in a warming - and then cooling - world?
    Aa Aa Aa

    Until recently, most discussions of modern global warming have looked only as far ahead as 2100 AD. Now, new investigations by pioneering climate modelers are beginning to tell another story, one in which the legacy of our heat-trapping carbon emissions lasts not just decades or centuries but long enough to interfere with future ice ages. As science-journalist Mason Inman (2005) puts it, with only slight exaggeration, "carbon is forever."
    Specialists are now investigating the long-term future of our greenhouse gas pollution with the help of a new generation of sophisticated climate models with names like CLIMBER, GENIE, and LOVECLIM. But the basics of that future boil down to one simple principle: what goes up must come down.

    Climate Whiplash

    Greenhouse gas concentrations and global temperatures will not increase indefinitely — today's carbon dioxide buildup and warming trend must eventually top out and then reverse as the atmosphere gradually recovers. The first stage of this process will occur when the rate at which we burn coal, oil, and natural gas levels off and then declines, either because we switch to alternative energy sources soon, or because we run out of affordable fossil fuels later. As a result, CO2 concentrations in the atmosphere will also eventually peak and then decline. This, in turn, will cause a series of linked environmental responses in which other currently rising trends reverse one by one in a "climate whiplash" phase that follows the lead of our carbon emissions. For example, as CO2 dissolves into the oceans, it combines with water to form carbonic acid, which alters the chemistry of seawater and makes limestone, chalk, and other carbonate-rich substances more likely to dissolve. Ocean acidification will peak shortly after atmospheric CO2 concentrations do, threatening marine species that have acid-soluble carbonate shells or skeletons, including corals, shellfish, and crustaceans (Figure 1).

    Figure 1: Staghorn coral near Key West, Florida.
    Ocean acidification threatens these and other marine organisms that depend on acid-soluble carbonate supporting structures and shells.
    © 2012 Public Domain Courtesy of Reef Relief. Some rights reserved.

    After a delay due to slow response times in the atmosphere and oceans (Wigley 2005), global average temperatures will pivot into cooling mode as CO2 concentrations continue to fall. However, global mean sea level will still rise long after the thermal peak passes, because even though temperatures will be falling, they will still be warmer than today. Therefore, land-based glacial ice will continue to melt and the oceans will continue to expand even though Earth's atmosphere has begun to recover. Sea level will only return to today's position when it finally becomes cool enough for large, land-based ice sheets to build up again on Antarctica and in the Arctic.

    Where Does the Carbon Go?

    In order to work out the timing of these processes in more detail, one must consider where CO2 goes after it leaves our smokestacks and exhaust pipes. Some of it will be taken up by soils and organisms but most of it will dissolve into the oceans, with between two thirds and half of our emissions perhaps going into solution during the next millennium or so (Inman 2008, Eby et al. 2009). In many computer simulations, maximum ocean acidification lasts 2000 years or more, depending on the amount of CO2 we emit in the near future. Marine species living in the polar regions and deep sea basins and trenches will be the most rapidly and severely impacted because the solubility of such gases is greatest in cold waters. But after the seas have absorbed as much CO2 as they can, roughly a fifth of our fossil carbon emissions will still be left adrift in the air (Tyrell et al. 2007, Inman 2008).
    The next stage of the cleanup will proceed more slowly. As atmospheric CO2 dissolves into raindrops, the carbonic acid that it produces will react with calcite and other carbonate minerals in rocks and sediments. Over thousands of years, those geochemical weathering processes will transfer many of the formerly airborne carbon atoms into groundwater and runoff, finally delivering them to the oceans in the form of dissolved bicarbonate and carbonate ions. Meanwhile, carbonate-rich deposits on the sea floor will experience similar reactions with overlying seawater as the oceans become more acidified. This slow addition of acid-buffering substances to marine ecosystems will act much like an antacid pill that allows the seas to consume more CO2 from the overlying atmosphere. These processes are generally expected to dominate the long-term recovery for 5,000 years or so.
    But even this second, lengthier phase won't remove the very last fraction of our carbon pollution. Only tens of thousands of years later, or possibly even hundreds of thousands if we burn most of our enormous coal reserves, the last remnants of our CO2 will finally be scrubbed away by even slower reactions with resistant silicate minerals, such as the feldspars found in granite and basalt. This is what University of Chicago oceanographer David Archer calls "the long tail of the carbon curve" (Archer 2005), and it will be dominated by gradual global cooling, albeit at higher temperatures than those of today.

    Choices Before Us

    The intensity and duration of the warming peak and recovery will depend upon choices we make during this century. If we switch to carbon-free energy sources during the next several decades, then approximately 1000 gigatons of fossil carbon will have been released into the atmosphere since the start of the Industrial Revolution (1 gigaton = 1 billion tons). Atmospheric CO2 concentrations will peak close to 550–600 parts per million (ppm) by 2200 AD or so, and then begin to fall (Figure 2; Archer 2005, Archer & Brovkin 2008).

    Figure 2: Airborne carbon dioxide concentrations in a moderate emissions scenario.
    Note the steep initial rise, rapid climate whiplash turnaround, and slow long-term recovery over the next 100,000 years.
    © 2012 Nature Education Reprinted with permission: Archer 2005; Archer and Brovkin 2008. All rights reserved.

    In the climate whiplash phase that follows this relatively moderate scenario, global mean temperatures are likely to climb 2–3°C higher than today by 2200–2300 AD, then enter a cooling recovery phase lasting as much as 100,000 years. Much of Greenland and western Antarctica's ice will melt into the oceans over millennia, lifting sea levels several meters higher than today before slowly receding.
    On the other hand, if we burn through all remaining coal reserves before switching to alternative energy sources, then a far more extreme scenario will result. In one computer simulation of what could follow a 5000 gigaton emission (Figure 3; Schmittner et al. 2008), airborne CO2 concentrations reach 1900–2000 ppm, roughly five times greater than today, by 2300 AD. Global mean temperature jumps 6–9 °C above today's average and remains artificially high for much longer than it does in the more moderate scenario, with the warmest part of the broad maximum lasting from 3000 AD to 4000 AD. Atmospheric CO2 concentrations and temperatures then fall relatively steeply for several thousand years after the peak and whiplash phase, but they don't return to today's levels for at least 400,000 years. All land-based ice eventually melts, raising sea levels by as much as 70 meters until the world cools enough for large polar ice sheets to form again, roughly half a million years from now.

    Figure 3
    Detail of the first 2000 years of an extreme emissions scenario, showing lagged responses of atmospheric CO2 concentrations, temperatures, and sea level.
    © 2012 Nature Education Reprinted with permission: Schmittner et al. 2008. All rights reserved.

    Life in a Hothouse

    What might life on Earth be like under such conditions? Although no examples from the past perfectly illustrate the warmest phases of these two scenarios, several of them are nonetheless informative.

    Immediately before the last ice age-between 130,000 and 117,000 years ago-a natural warming episode known in Europe as the Eemian Interglacial produced global average temperatures 2–3°C higher than those of today, much like what would be expected in our more moderate scenario. The surface area of the Greenland ice sheet shrank by at least a third, the Arctic Ocean lost some summer ice-cover but retained enough for ringed seals and polar bears to survive, elephants and water buffalo migrated northward into Britain and Europe, and trees that are now more typical of the southeastern United States, such as black gums and hickories, thrived in the Adirondack Mountains of upstate New York (Stager 2011). Although it was caused by cyclic changes in the orientation of the Earth relative to the sun rather than greenhouse gases, the Eemian example nonetheless shows that even a relatively moderate warming can melt enough land-based ice to raise sea levels by 6–9 meters if it persists long enough, which in this case was 13,000 years (Figure 4).

    Figure 4: Fossil oysters resting several meters above the surf zone near Durban, South Africa.
    Their elevation shows how high sea level once stood during the warm Eemian Interglacial, 130,000–117,000 years ago.
    © 2012 Nature Education All rights reserved.

    The more extreme of the two emissions scenarios is better illustrated by a super-hothouse that occurred 55 million years ago-roughly 10 million years after the demise of the dinosaurs. Geo-historical evidence shows that the Paleocene-Eocene Thermal Maximum (PETM) was triggered by greenhouse gas buildups, most likely from the release of icy methane hydrates or other carbon compounds buried in marine deposits (Katz et al. 1999). Global mean temperatures rose 5–6°C within several thousand years and did not fully recover for 100,000–200,000 years (Zachos et al. 2003, Rohl et al. 2007, Jaramillo et al. 2010). Both polar regions were completely ice-free, the Arctic Ocean was a warm, brackish pond rimmed by deciduous redwood forests, Antarctica was covered by beech trees, and carbonic acid burned a discolored, carbonate-free band into ocean sediments worldwide (Zachos et al. 2005). Some species became extinct during the PETM, especially in the most heavily acid-impacted portions of the oceans (Gibbs et al. 2006), but many others thrived, sometimes spreading so rapidly between latitudes and continents that they seemed to appear simultaneously in fossil records all over the world (Smith et al. 2006, Jaramillo et al. 2010).
    In both of these cases, free migration seems to have been an important key to the survival of animals and plants of the time, and the lack of human-made barriers in the distant past made it easier for species to adjust to large climatic shifts. Unfortunately, our settlements, roads, and farms can make such migrations more difficult today, and will probably do so in the future as well.

    Climate Ethics

    Such long-term perspectives are not only scientifically interesting and important, they also raise new ethical questions, simply because human beings are now in the picture. Our carbon emissions will influence countless generations, as well as many species other than our own, in future versions of the world that will differ markedly from the one we know now. This realization may force us to weigh the needs of some generations against those of others.
    For instance, having the Arctic Ocean become ice-free in summer may seem outlandish to us, but it may instead seem normal to people who will be born into a warmer world thousands of years from now. When the global cooling recovery sets in, the open-water ecosystems and human cultures that will by then have become dependent upon warmer climates could be threatened as the polar ocean begins to re-freeze. Will global warming seem preferable to cooling then?
    Another potentially confusing situation arises when we consider that atmospheric CO2 concentrations will still be high enough in 50,000 AD to prevent the next ice age, which natural cyclic processes would normally be expected to trigger then (Figure 5; Berger & Loutre 2002, Archer & Ganopolski 2005). The next major cyclic cool period is due in 130,000 AD, by which time a moderate carbon emission will have dissipated. This suggests that preventing an extreme 5000 Gton hothouse scenario now could leave Canada and northern Europe vulnerable to being bulldozed by gigantic ice sheets in the deep future. How do we weigh the winners and losers in such a far-sighted view?

    Figure 5
    Predicted summer insolation (sunlight intensity) values in the Arctic, showing an anticipated cooling period around 50,000 AD that would normally produce an ice age. Lingering remnants of our fossil fuel emissions may still warm the atmosphere enough then to prevent the ice age from occurring.
    © 2012 Nature Education Reprinted with permission: M. F. Loutre. All rights reserved.

    Fortunately, long-term perspectives may also suggest possible win-win situations, as well. For instance, leaving most remaining coal untouched rather than using it all up now would reduce the severity of climate change in the near-term, and would also leave large stores of burnable carbon in the ground that later generations could use as a source of greenhouse gases for the prevention of future ice ages, should they so desire.
    Whichever emissions scenario we choose-be it moderate or extreme-one thing is now clear. Our influence on the climatic future of the world is geological in scope. Little wonder, then, that many scientists are now referring to our chapter of Earth history with a term coined by ecologist Eugene Stoermer-the "Anthropocene Epoch" or the "Age of Humans" (Crutzen & Stoermer 2000, Stager 2011).

    Figure 6
    The rubble-strewn snout of a glacier in southern Iceland, with people in the background for scale.
    © 2012 Nature Education All rights reserved.

    References and Recommended Reading

    Archer, D. The fate of fossil fuel CO2 in geologic time. Journal of Geophysical Research 110, C09805 (2005). doi:10.1029/2004/C002625
    Archer, D. & Ganopolski, A. A movable trigger: Fossil fuel CO and the onset of the next glaciation. Geochemistry, Geophysics, Geosystems 6, Q05003 (2005). doi:1029/2004GC000891
    Archer, D. & Brovkin, V. The millennial lifetime of anthropogenic CO2. Climatic Change 90, 283–297 (2008).
    Berger, A. & Loutre, M. F. An exceptionally long interglacial ahead? Science 297, 1287–1288 (2002).
    Crutzen, P. J. & Stoermer, E. F. "The 'Anthropocene'". Global Change Newsletter 41, 17–18 (2000).
    Eby, M. et al. Lifetime of anthropogenic climate change: Millennial time scales of potential CO2 and surface temperature perturbations. Journal of Climate 22, 2501–2511 (2009).
    Gibbs, S. J. et al. Nannoplankton extinction and origination across the Paleocene-Eocene Thermal Maximum. Science 314, 1770–1773 (2006).
    Inman, M. Carbon is forever. Nature Reports Climate Change (2008). doi:10.1038/climate.2008.122
    Jaramillo, C. et al. Effects of rapid global warming at the Paleocene-Eocene boundary on neotropical vegetation. Science 330, 957–961 (2010).
    Katz, M. E. et al. The source and fate of massive carbon input during the Latest Paleocene Thermal Maximum. Science 286, 1531–1533 (1999).
    Montenegro, A. et al. Long-term fate of anthropogenic carbon. Geophysical Research Letters 34, L19707 (2007). doi:1029/2007GL030905
    Röhl, U. et al. On the duration of the Paleocene-Eocene thermal maximum (PETM). Geochemistry Geophysics Geosystems 8, Q12002 (2007). doi:10.1029/2007GC001784
    Schmittner, A. et al. Future changes in climate, ocean circulation, ecosystems, and biogeochemical cycling simulated for a business-as-usual CO2 emission scenario until year 4000 AD. Global Biogeochemical Cycles 22, GB1013 (2008). doi:10.1029/2007GB002953
    Smith, T. K., Rose, D. & Gingerich, P. D. Rapid Asia-Europe-North America dispersal of the earliest Eocene primate Teilhardina. Proceedings of the National Academy of Sciences of the United States of America 103, 11223–11227 (2009).
    Solomon, S. et al. Irreversible climate change due to carbon dioxide emissions. Proceedings of the National Academy of Sciences of the United States of America 106, 1704-1709 (2009).
    Stager, C. Deep Future: The Next 100,000 Years of Life on Earth. New York, NY: Thomas Dunne Books, 2011. (link)
    Tyrrell, T., Shepherd, J. G. & Castle, S. The long-term legacy of fossil fuels. Tellus, Series B: Chemical and Physical Meteorology 59B, 664–672 (2007).
    Wigley, T. M. L. The climate change commitment. Science 307, 1766–1769 (2005).
    Zachos, J. C. et al. A transient rise in tropical sea surface temperature during the Paleocene-Eocene Thermal Maximum. Science 302, 1551–1554 (2003).
    Zachos, J. C. et al. Rapid acidification of the ocean during the Paleocene-Eocene thermal maximum. Science 308, 1611–1615 (2005).

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    Global Change: An Overview

    Conservation of Biodiversity
    Introduction to the Basic Drivers of Climate

    Deep Atlantic Circulation During the Last Glacial Maximum and Deglaciation

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    We have reached the end of the instructional modules of this course. This is a good time to think over your own experience since the start of the course. What questions have you answered? What new questions do you have? How are you going to address your new questions?
    Lesson Goals:
    By the end of this section, you will be able to:
    1 Compare your own mental model of the climate system today to your mental model of the climate system a few weeks ago (no, there won’t be a quiz question on this one).
    2 Describe possible future climate changes, involving some particular aspect of the climate system, of interest to you (if there are any quiz questions on this one they would be from the Arctic reading).

    Revisit your own mental model
    In Module 2, you might (or might not) have drawn a diagram representing your mental model of Earth’s climate system. Regardless of whether you did it then:
    1 Take 15 minutes, a blank sheet of paper and a pencil (or an electronic file if you prefer), and generate a representation of your own mental model of Earth’s climate system, as you think about it right now. What are important parts? What are important interactions? How are the parts connected?
    2 If you did create one earlier, get it out now, and compare your old and new ones.
    1 Are there things on your old one that aren’t on your new one?
    2 Are there things on your new one that aren’t on your old one?
    3 Are there parts that you want to fill in more completely in the future, but you don’t feel prepared to do yet?
    3 This exercise is primarily for your own reflection. It takes a lot of deliberate work and practice to change one’s mental models.  And, as you know, Earth's climate system is complex, so you may find it's difficult to generate what you'd consider a "complete" picture.

    Explore some aspect of Earth’s climate future
    1 To get started with an example, skim this article about future climate in the Arctic.  Look at the figures. Don't get too bogged down in the details unless you want to:
    What are the estimates for Arctic temperatures in the future if we follow different RCPs (e.g. RCP 8.5 versus RCP 4.5)?
    What components of Earth’s climate system are linked to changes in the Arctic?
    2 Pick some other aspect of Earth’s climate system and see what you can find regarding future projections for that part of the system. It could be local, regional, or global. How far into the future do the projections go? What other components of the climate system are linked to the one you chose?

    Future Arctic climate changes: Adaptation and mitigation time scales
    James E. Overland1, Muyin Wang2, John E. Walsh3, and Julienne C. Stroeve4
    1NOAA/Pacific Marine Environmental Laboratory, Seattle, Washington, USA, 2University of Washington/JISAO, Seattle, Washington, USA, 3International Arctic Research Center, University of Alaska, Fairbanks, Alaska, USA, 4National Snow and Ice Data Center, CIRES, University of Colorado Boulder, Boulder, Colorado, USA
    Abstract The climate in the Arctic is changing faster than in midlatitudes. This is shown by increased temperatures, loss of summer sea ice, earlier snow melt, impacts on ecosystems, and increased economic access. Arctic sea ice volume has decreased by 75% since the 1980s. Long-lasting global anthropogenic forcing from carbon dioxide has increased over the previous decades and is anticipated to increase
    over the next decades. Temperature increases in response to greenhouse gases are amplified in the Arctic through feedback processes associated with shifts in albedo, ocean and land heat storage, and near-surface longwave radiation fluxes. Thus, for the next few decades out to 2040, continuing envi- ronmental changes in the Arctic are very likely, and the appropriate response is to plan for adaptation
    to these changes. For example, it is very likely that the Arctic Ocean will become seasonally nearly sea
    ice free before 2050 and possibly within a decade or two, which in turn will further increase Arctic tem- peratures, economic access, and ecological shifts. Mitigation becomes an important option to reduce potential Arctic impacts in the second half of the 21st century. Using the most recent set of climate model projections (CMIP5), multimodel mean temperature projections show an Arctic-wide end of century increase of +13∘C in late fall and +5∘C in late spring for a business-as-usual emission scenario (RCP8.5) in contrast to +7∘C in late fall and +3∘C in late spring if civilization follows a mitigation scenario (RCP4.5). Such temperature increases demonstrate the heightened sensitivity of the Arctic to greenhouse gas forcing.
    1. Introduction
    Duarte et al. [2012] and Jeffries et al. [2013] note a large number of recent abrupt climate changes in the Arctic, and Post et al. [2013] show emerging ecological consequences of sea ice decline. Among these
    are a 75% loss of sea ice volume since the 1980s [Schweiger et al., 2011; Overland and Wang, 2013] and earlier loss of late spring snow cover extent during 2008–2012 on high-latitude land areas [Derksen and Brown, 2012]. Both snow and ice losses represent a shift in surface albedo that results in increased ocean and land heat retention. Global warming has produced a larger effect in the Arctic than it has in mid- latitudes (Figure 1), a pattern known as Arctic amplification [Serreze et al., 2009] that was predicted in model simulations beginning in 1980 [Manabe and Stouffer, 1980; Holland and Bitz, 2003; Bracegirdle and Stephenson, 2013]. Arctic air temperatures increased in all seasons during the period 2001–2012 com- pared to 1971–2000, with the greatest warming in autumn and winter. Mean annual temperature in
    the Arctic is now more than 1.5∘C higher than the 1971–2000 average, more than double the warming
    at lower latitudes during the same period. Figure 2a shows that the record of minimum sea ice extent (white area) in September 2012 was reduced by nearly 50% in area compared to its climatological extent (pink line). Figure 2b shows the reduction in September sea ice volume between 1979 and 2012, calcu- lated from a sea ice data assimilation model (the Pan-Arctic Ice-Ocean Modeling and Assimilation System, PIOMAS), which is occurring at a relatively faster rate than sea ice extent owing to the influence of thinning sea ice.
    Arctic amplification is a response to sea ice-temperature positive feedbacks [Mahlstein and Knutti, 2012]. Such interactions include the loss of sea ice with direct albedo reduction and additional heat storage in sea ice-free areas [Serreze et al., 2009; Screen and Simmonds, 2010]. Secondary, large relative contribu- tions to Arctic warming are from additional downwelling longwave radiation reaching the surface that
    This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distri- bution in any medium, provided the original work is properly cited, the use is non-commercial and no modifica- tions or adaptations are made.
    © 2013 The Authors. 1
    Earth’s Future 10.1002/2013EF000162
    has its origin from the additional heat and water vapor given to the lower atmosphere over newly sea ice- free areas [Bintanja and van der Linden, 2013; Ghatak and Miller, 2013]. The combined effects of multiple feedbacks explain much of the enhanced recent and suggested future Arctic warming, including its sea- sonality. We begin by investigating the next 30 years that are dominated by further sea ice loss in summer, which we refer to as the adaptation time scale. The choice of path followed for additional greenhouse gas emissions is the primary determinant of potential air temperature increases near the end of the 21st century, which we refer to as the mitigation time scale.
    2. The Near-Term (<2040 adaptation="" p="" scale="" time="">The previous decade saw an increase of 27% of global emissions of carbon dioxide (CO2), with concen- tration values passing 400 ppm at several observation sites during 2013 [Monastersky, 2013]. Given the current rate of population and urbanization increase and the current status of global political activity on global warming, it is reasonable to project a continuing CO2 rise over the next two decades. Mod- est external forcing from global warming combines with Arctic amplification—the emergence of strong sea ice-temperature positive feedbacks—to increase the likelihood of future Arctic warming and sea ice decline [Serreze and Barry, 2011].
    Figure 1. The difference in recent annual averaged Arctic temperatures (2001–2012) from a baseline period of 1971–2000. Data are from NCEP/NCAR reanalyis.
    Global climate models (GCMs) are major tools available to provide cli- mate projections based on physical laws. Recently, results from more than 30 models have been made available to the wider scientific community through the archive at the Program for Climate Model Diagnosis and Inter- comparison (PCMDI). This constitutes the fifth phase of the Coupled Model Intercomparison Project (CMIP5) that followed an earlier CMIP3. All models show loss of sea ice as greenhouse gas concentrations increase and a faster rate of temperature increase in the Arctic than at lower latitudes. How- ever, there are major difficulties in using the results from these models for quantitative projections in sea ice loss relative to the real-world changes as shown in Figure 2. The first difficulty is the wide spread of different model hindcast and forecast results; they vary
    by model, location, variable, internal chaotic variability, and evaluation metric. The second difficulty is that 80% of 56 CMIP5 ensemble member trends for 1979–2011 are smaller than observed. The observed trend lies outside the 2 standard deviation bound of the models’ trends [Stroeve et al., 2012 and
    their Figure 3]. Overland and Wang [2013] conclude that recent data and expert opinion should be considered over CMIP5 GCM results to advance the very likely timing for a future with nearly sea ice-free conditions to the first half of the 21st century, with a possibility of a nearly complete loss within a decade or two.
    The lack of confidence in CMIP5 projections of the timing for Arctic sea ice loss relative to recent data also brings into question near-term CMIP5 projections for Arctic air temperatures (<2040 a="" adaptation="" amplification="" and="" anthro-="" arctic="" are="" as="" atmosphere="" because="" by="" changes.="" changes="" climate="" co2="" combination="" conclusion="" consider="" continued="" continuing="" contribu-="" decades="" external="" feedbacks.="" for="" forcing="" gases="" greenhouse="" human="" ice-temperature="" in="" into="" locked="" major="" next="" of="" one="" over="" p="" pogenic="" positive="" priority="" residence="" response="" sea="" should="" strong="" support="" system="" that="" the="" time="" tions="" to="">OVERLAND ET AL.
    © 2013 The Authors. 2
    Earth’s Future 10.1002/2013EF000162 3. Surface Temperatures at the Mitigation Time Scale (2080–2100)
    CMIP5 projections are subject to three main types of uncertainty: model differences, internal variability,
    and choice of emission scenario [Overland et al., 2011; Hodson et al., 2012]. Model variations are due to
    different formulations and parameterization of physical processes; internal variability arises from the
    chaotic nature of the earth’s climate system and leads to different results for similar initial conditions of
    the models. Near-term projections are dominated by these two types of uncertainties. Longer-term pro-
    jections are dominated by the choice of the future emission pathway. Coincident with the development
    of CMIP5, four representative con- centration pathways (RCPs) were developed to span a range of poten- tial radiative forcing values for the year 2100, ranging from 2.6 to 8.5 W/m2 (Figure 3) [van Vuuren et al., 2011]. RCPs and emission scenarios are plausible descriptions of how the future may evolve based on the sci- entific literature on socioeconomic change, technological change, energy and land use, and emissions of green- house gases and air pollutants. RCP8.5 represents a rising radiative forcing pathway leading to 8.5 W/m2 (∼1370 ppm CO2 equivalent) by 2100. RCP4.5 represents stabilization near 2060 to 4.5 W/m2 (∼650 ppm CO2 equiva- lent). The RCP2.6 scenario requires a 70% reduction of emissions relative
    to present levels by 2050, a scenario that is highly unlikely in view of the current trajectory of emissions and the absence of progress toward mitigation measures. We refer to the RCP8.5 and RCP4.5 future scenarios as business-as- usual and mitigation.
    Figure 4 [updated from Stroeve et al., 2012] shows that the Arctic continues to lose summer sea ice in GCMs based on all scenarios except the implausible RCP2.6. The business-as-usual (RCP8.5) scenario leads to the most rapid rate of ice loss. However, as noted ear-
    lier, the observed rate of sea ice loss over the past few decades lies outside the range of model simulations of the same period. Strategies for adjusting the model projections include bias correction and/or the selection of sub- sets of models that are more success- ful in capturing the sea coverage of the past few decades [Massonnet et al.,
    Figure 2. (a) Arctic sea ice extent for September 2012 (white region). Climatological sea ice extent for September is shown by pink outline (From NSIDC). (b) Trend in loss of Arctic sea ice volume calculated from a sea ice data assimilation model (From Overland and Wang [2013] based on values from the PIOMAS project at the University of Washington). Dark and light shading indicate 1 and 2 standard deviations.
    2012; Wang and Overland, 2012; Liu et al., 2013]. However, it is unclear whether comparing the fastest sea ice loss rates from a set of model ensemble members with extrapolation from observed conditions is valid, given the potential slow mean responses of the models.
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    Figure 3. Four future climate scenarios based on amount of global radiative forcing at the end of the century [after van Vuuren et al., 2011].
    Figure 5 shows a comparison of the linear trend in annual surface temper- ature observations versus the set of
    36 CMIP5 models during 1966–2005. Averaging over all models and months should highlight the climate sensitivity (temperature change per CO2 increase), as it averages out the across-model differences and much of the internal variability. Indeed, we find a reasonable consistency between the two fields, especially in Arctic amplification of the warming and the tendency for greater warming over land than ocean in mid- dle latitudes. Because the observed pattern represents only one realiza- tion in contrast to the 36 realizations averaged into the model composite, the observed pattern is more spatially complex.
    As noted in the previous section, we have concern about CMIP5 air temper- ature projections near 2040 because
    of the uncertainty in sea ice extents. However, by 2080, most CMIP5 projection results have caught up with the real world in transitioning to a sea ice-free summer. Thus, beyond 2080, we consider that we are primarily comparing the effects of different emission/radiative forcing on a seasonally sea ice-free Arctic.
    Figure 4. Model simulations of Arctic sea ice extent for September, 1900–2100, based on observed concentrations of heat-trapping gases and particles (through 2005) and four emissions scenarios. Colored lines for RCP scenarios are model averages (CMIP5) and lighter shades of the line colors denote ranges among models for each scenario. Dotted gray line and gray shading denote average and range of the historical simulations through 2005. The thick black line shows observed data for 1953–2012. The simulated September ice losses under all scenarios lag behind the observed loss of the past decade (Figure source: adapted from Stroeve et al. [2012]).
    Because we are investigating one of the two planetary regions with the largest range of seasonal radiative forcing and sea ice, it is important to detail the results for each month indi- vidually [Deser et al., 2010; Bintanja and van der Linden, 2013]. Figure 6 shows the mean model projections of surface temperatures for the North- ern Hemisphere during 1950–2100 by month for business-as-usual (RCP8.5) in red and the mitigation scenario (RCP4.5) in blue. At the end of the century the mitigation scenario tops out at approximately +3.0∘C increase for September through January rela- tive to a 1981–2005 baseline period and a slightly lower value for the remainder of the year. The warming
    in the business-as-usual (RCP8.5) sce- nario reaches approximately +6.0∘C in November through January, with values closer to 5∘C in the other
    The seasonality in the Arctic (60∘N–90∘N) is larger than the Northern Hemisphere (Figure 7 versus Figure 6). For spring and early summer (April through July) the mitigation scenario is in the range of a +2 –3∘C temperature increase over the 1981–2005 baseline; this increases in the fall owing to the lack of sea ice to a +7∘C change in November and December. For the business-as-usual, temperatures continue to rise through the second half of the 21st century. The May-June-July temperature increases are near +5∘C,
    © 2013 The Authors. 4
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    Figure 5. Linear trend of annual mean surface air temperature for 1966–2005 period based on NCEP/NCAR reanalysis (left) and ensemble mean of 36 CMIP5 models (one member each). Units are oC/decade.
    Figure 6. Northern Hemisphere monthly temperature anomalies averaged over 36 ensemble members from 36 models. The red line is the ensemble mean under RCP8.5, and the blue line is for RCP4.5. The shaded area outlines 1 standard deviation from the ensemble mean. The temperature anomalies are calculated relative to 1981–2005 period mean.
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    Figure 7. Similar to Figure 6, but averaged over the Arctic domain (60oN–90oN).
    and the November-December-January temperatures top out at a +13∘C increase relative to the
    1981–2005 baseline, a further indication of the Arctic’s heightened sensitivity to greenhouse gas forcing.
    In comparison to previous studies, Bitz et al. [2012] show that two models, CCSM3 and HADGEM1, had greater temperature increases for 2040–2059 minus 1980–1999 compared to the mean of the set of mod- els from the previous CMIP3 results; they attribute this difference to improved sea ice physics in these two models. Because their dates are around the variable timing of sea ice loss in different models, their dif- ference in temperature increases supports our contention that it is difficult to obtain stable temperature projection results at mid-century. On the other hand, two recent studies that look at temperatures from single models at the end of the century find results similar to our CMIP5 composite temperature increases [Koenigk et al., 2012; Vavrus et al., 2012].
    4. Conclusions
    On the basis of two radiative forcing scenarios (mitigation and business-as-usual) in the CMIP5 collection of GCMs we note a large difference in surface air temperatures in the Arctic at the end of the 21st century, which makes a strong case to begin mitigation activities for greenhouse gases. The RCP4.5 scenario, which stabilizes CO2 concentrations by mid-century [Thomson et al., 2011], is a plausible target if decisive actions are begun. We consider that our estimates of future Arctic temperature increases are realistic as we are highlighting the radiative components of the model projections by averaging spatially and over a large number of models.
    For the decadal scale out to 2040, we have low confidence in quantitative projections of the collection of CMIP5 models on the timing of Arctic-wide sea ice loss. There are a number of reasons for this, primarily the spread in the results, which in turn may depend not only on natural variability but also on the mod- els’ different formulations of sea ice physics, treatment of clouds, radiation, and atmospheric and ocean dynamics [Karlsson and Svensson, 2013; Overland and Wang, 2013]. There is a wide gap in projected timing
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    The work is supported by NOAA Arctic Research Project of the Climate Pro- gram Office and by the Office of Naval Research, Code 322. This publication is partially funded by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooper- ative Agreement NA10OAR4320148, contribution 2156, PMEL contribution 4052. JW is supported by NSF grant ARC-1023131.
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