The science b ehind climate change
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The Science B ehind Climate Change. Daniel Rothenberg Based on presentations by Dan Chavas , Marty Singh, Tim Cronin, Morgan O’Neill MIT Energy Club: Energy 101 series November 13, 2012. http://rsd.gsfc.nasa.gov/rsd/images/goes8_lg.jpg

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The Science B ehind Climate Change

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The Science Behind Climate Change

Daniel Rothenberg

Based on presentations by Dan Chavas, Marty Singh, Tim Cronin, Morgan O’Neill

MIT Energy Club: Energy 101 series

November 13, 2012

http://rsd.gsfc.nasa.gov/rsd/images/goes8_lg.jpg

http://images.sciencedaily.com/2007/11/071114163448-large.jpg


Goal

  • I hope you take home…

    • The basic scientific logic for why we care about increasing greenhouse gas concentrations

    • Insight into what is well-understood about climate change

    • Answers to your questions


Outline

Why greenhouse gas emissions matter

  • Energy balance models: why GHGs  warming

  • Radiative-convective model: simplest tool to quantify warming (at the surface where we live)

  • General Circulation Model: exploring our future climate


Outline

Why greenhouse gas emissions matter

  • Energy balance models: why GHGs  warming

  • Radiative-convective model: simplest tool to quantify warming at the surface (where we live)

  • General Circulation Model: exploring our future climate


Physics review: Blackbody radiation

1) Stefan-Boltzmann’s Law: Fout =  T4

2) Wien’s Law: λmax~ 1/T

http://upload.wikimedia.org/wikipedia/commons/f/ff/BlackbodySpectrum_loglog_150dpi_en.png


Physics review: Blackbody radiation

1) Stefan-Boltzmann’s Law: Fout =  T4

2) Wien’s Law: λmax~ 1/T

http://upload.wikimedia.org/wikipedia/commons/f/ff/BlackbodySpectrum_loglog_150dpi_en.png


Physics review: Blackbody radiation

1) Stefan-Boltzmann’s Law: Fout =  T4

2) Wien’s Law: λmax~ 1/T

http://upload.wikimedia.org/wikipedia/commons/f/ff/BlackbodySpectrum_loglog_150dpi_en.png


Physics review: Blackbody radiation

1) Stefan-Boltzmann’s Law: Fout =  T4

2) Wien’s Law: λmax~ 1/T

http://upload.wikimedia.org/wikipedia/commons/f/ff/BlackbodySpectrum_loglog_150dpi_en.png


Physics review: Blackbody radiation

1) Stefan-Boltzmann’s Law: Fout =  T4

2) Wien’s Law: λmax~ 1/T

http://upload.wikimedia.org/wikipedia/commons/f/ff/BlackbodySpectrum_loglog_150dpi_en.png


Physics review: Blackbody radiation

1) Stefan-Boltzmann’s Law: Fout =  T4

2) Wien’s Law: λmax~ 1/T

http://upload.wikimedia.org/wikipedia/commons/f/ff/BlackbodySpectrum_loglog_150dpi_en.png


Energy BalanceEquilibrium

Energy in = Energy out

T = constant


Energy BalanceEquilibrium

Energy in = Energy out

T = constant


Energy BalanceEquilibrium

Energy in = Energy out

T = constant


Energy Balance models for climate

  • “Rock-star” model


Energy Balance models for climate

  • “Rock-star” model


Energy Balance: The “rock-star” modelEquilibrium

Energy in = Energy out

T = constant

Archer “Global Warming: Understanding the Forecast”


Energy Balance: The “rock-star” modelEquilibrium

Tsun = 5800 K

Tearth

Fout = T4

Energy in = Energy out

T = constant


Energy Balance: The “rock-star” modelEquilibrium

Tsun = 5800 K

1.5*108 km

Tearth

Rearth =

6*103 km

Fout = T4

Energy in = Energy out

T = constant


Energy Balance: The “rock-star” modelEquilibrium

S0 ≈ 1367 W/m2

Energy in = Energy out

T = constant


Energy Balance: The “rock-star” modelEquilibrium

S0 ≈ 1367 W/m2

Energy in = Energy out

T = constant


Energy Balance: The “rock-star” modelEquilibrium

SA = 4πR2

S0 ≈ 1367 W/m2

A = πR2

Energy in = Energy out

T = constant


Energy Balance: The “rock-star” modelEquilibrium

S0/4

S0 ≈ 1367 W/m2

Stop = S0/4

Energy in = Energy out

T = constant


Energy Balance: The “rock-star” modelAlbedo

Albedo () = fraction of incoming solar radiation reflected

Global mean albedo:  ≈ 0.3

NASA MODIS

Energy in = absorbed solar radiation = (1 -  )S0/4


Energy Balance: The “rock-star” modelEquilibrium

S0/4

S0/4

S0 ≈ 1367 W/m2

Stop = S0/4

Fin = (1 -  )S0/4

Energy in = Energy out

T = constant


Energy Balance: The “rock-star” modelEquilibrium

Fout

S0/4

S0/4

S0 ≈ 1367 W/m2

Stop = S0/4

Fin = (1 -  )S0/4

Fout = Te4

Energy in = Energy out

T = constant


Energy Balance: The “rock-star” modelEquilibrium

Fin (Solar) = Fout(Terrestrial)

(1 -  )S0/4 = Te4

Te= 255 K = 0 F


Energy Balance: The “rock-star” modelEquilibrium

Fin (Solar) = Fout(Terrestrial)

(1 -  )S0/4 = Te4

Te= 255 K = 0 F

Actual Global

Surface Temperature

Tsurface = 288 K  60°F

We need an atmosphere!


Energy Balance models for climate

  • “Rock-star”: too cold

  • 1-layer Total Greenhouse


Energy Balance: The 1-layer “total greenhouse” modelEquilibrium

Fout

S0/4

Assume a single layer atmosphere that absorbs all the terrestrial rays, and none of the solar rays.

S0/4

Tatmos

Tsurface


Energy Balance: The 1-layer “total greenhouse” modelEquilibrium

Fout

S0/4

Assume a single layer atmosphere that absorbs all the terrestrial rays, and none of the solar rays.

S0/4

Tatmos

Energy out has decreased because of the absorbing gases.

Now more energy is coming in than going out and so the system will warm up!

Tsurface


Energy Balance: The 1-layer “total greenhouse” modelEquilibrium

Fout

S0/4

Assume a single layer atmosphere that absorbs all the terrestrial rays, and none of the solar rays.

S0/4

Tatmos

Tsurface

Tsurface= 303 K = 85 F

But this is way too hot…


Energy Balance models for climate

  • “Rock-star”: too cold

  • 1-layer Total Greenhouse: too hot

  • 1-layer Leaky Greenhouse


The greenhouse is “leaky”…

  • N2and O2, which comprise 99% of the atmosphere are diatomic and thus do not interact with outgoing terrestrial radiation

  • However, some trace gases do absorb outgoing radiationover certain wavelength bands within the terrestrial spectrum

  • Greenhouse gases in order of importance:

    • Water vapor (H2O)

    • Carbon dioxide (CO2)

    • Ozone (O3)

    • Methane (CH4)

    • Nitrous Oxide (N2O)

NASA


Energy Balance: The 1-layer “leaky greenhouse” modelEquilibrium

The atmosphere now absorbs a fractionof the terrestrial radiation emitted from the surface.

Fout

S0/4

Simple conceptual understanding of the Earth’s greenhouse effect

S0/4

Tatmos

  • But:

  • The real atmosphere is not a single ‘layer’

  • The real atmosphere absorbs differently at different wavelengths

Tsurface


Energy Balance models for climate

  • “Rock-star”: too cold

  • 1-layer Total Greenhouse: too hot

  • 1-layer Leaky Greenhouse: good, but not realistic

  • Multi-layer radiative


Energy Balance: The multi-layer radiative modelEquilibrium

Manabe & Strickler (1964)

  • Many atmospheric layers

  • More realistic radiative transfer

Tsurface = 332 K = 138 F

Ouch

but warm air tends to rise…


Convection (vertical)

  • Surface is much hotter than the air just above it: cannot be maintained

    • Heat transfer from surface to air above it via conduction

    • Air that is warmer than its surroundings will rise

    • Atmosphere will efficiently transfer heat upwards from surface via convection


Energy Balance models for climate

  • “Rock-star”: too cold

  • 1-layer Total Greenhouse: too hot

  • 1-layer Leaky Greenhouse: good, but not realistic

  • Multi-layer radiative: realistic but not dynamically stable

  • Multi-layer radiative-convective


Outline

Why greenhouse gas emissions matter

  • Energy balance models: why GHGs  warming

  • Radiative-convective model: simplest tool to quantify warming at the surface (where we live)

  • General Circulation Model: exploring our future climate


Multi-layer radiative-convective modelEquilibrium

Manabe & Strickler (1964)

  • Many atmospheric layers

  • More realistic radiativetransfer

  • Convective upward heat transport

Tsurface = 300 K = 80F

YAY


Multi-layer radiative-convective modelEquilibrium

Manabe & Strickler (1964)

  • Many atmospheric layers

  • More realistic radiativetransfer

  • Convective upward heat transport

  • Now have a model where we can change –

    • Chemistry of the atmosphere

    • Incoming solar radiation

  • - and measure how it changes the surface temperature

Tsurface = 300 K = 80F

YAY

This is the simplest model of the mean global atmosphere that is dynamically and thermodynamically stable.

Thus, we can use it as tool to analyze the impact of increasing GHGs on surface temperatures


Multi-layer radiative-convective modelEquilibrium

Manabe & Strickler (1964)

  • Many atmospheric layers

  • More realistic radiativetransfer

  • Convective upward heat transport

Doubling CO2

(keeping everything else constant)

+ 2.3°F

Tsurface = 300 K = 80F

YAY

This is the simplest model of the mean global atmosphere that is dynamically and thermodynamically stable.

Thus, we can use it as tool to analyze the impact of increasing GHGs on surface temperatures


Climate Feedbacks

Clouds

Water vapor

Ice-albedo

NASA Earth Observatory


Water vapor feedback

Positive feedback: Clausius-Clapeyron relation atmospheric water vapor increases exponentially with temperature.


Water vapor feedback

Positive feedback: Clausius-Clapeyron relation atmospheric water vapor increases exponentially with temperature.

Doubling CO2

+ water vapor

+ 4.1°F


The 2xCO2 Baseline: + 4 oF

  • This result is based on straightforward physics – it is the baseline warming caused by 2xCO2

  • The real climate system has many other internal processeswithin that may amplify/suppress this warming

  • However these other processes are less well understood and more complicated to account for

    Other processes:

  • Horizontal variations in climate

  • Movement of atmosphere, including clouds and aerosols

  • Ocean

  • Land interactions: melting of ice, vegetation

  • Biogeochemical cycles (e.g. carbon cycle)


Outline

Why greenhouse gas emissions matter

  • Energy balance models: why GHGs  warming

  • Radiative-convective model: simplest tool to quantify warming at the surface (where we live)

  • General Circulation Model: exploring our future climate


General Circulation Model

  • Must integrate the governing (Navier-Stokes) equations forward in time, keeping track of:

  • Heat

  • Moisture

  • Momentum

  • Other tracers

NOAA GFDL


Putting all the components together


Sub-grid-scale processes

Many processes occur at much smaller scales than the grid-box size (e.g. clouds, rainfall, vegetation, etc.)

Must represent small-scale processes with parameterization:

NOAA


Clouds: why are they important?

  • Clouds can:

  • Warm by absorbing long-wave radiation (greenhouse effect)

  • Cool by reflecting sunlight (change the albedo)

  • Which effect dominates depends on thickness, type, altitude

  • Clouds are difficult to model… not only because of their scale but because the microphysics are not well understood.


Clouds: How do we model them?

Arakawa & Schubert, 1974

  • A gridbox will have an ‘ensemble’ of clouds within it

  • The model only predicts the average temperature, humidity etc. across the grid-box

  • Need to ‘parameterize’ the statistical distribution of clouds within the grid-box using the large-scale atmospheric state


Global Circulation ModelsFuture projections

For 2xCO2…

19 GCMs: + 5.8 F (3.8-7.9)

Baseline: + 4 F

Moderate warming above baseline

  • By 2100…

  • Depends on actual GHG emissions in future

  • Takes a while to reach equilibrium

IPCC4th Assessment Report (2007)


Future changes with warming

Higher confidence

Low confidence

Anything regional/local

Ice sheets

Extreme weather (besides heavy rain)

  • Higher total precipitation

  • Wet get wetter, dry get drier

  • Sea level rise due to thermal expansion

  • Significant arctic ice melt


Things to take home

  • Scientific logic of global warming:

    • GHGs reduce energy lost to space

    • Less energy going out than coming in  climate system warms

    • Basic physics: Baseline 2x CO2 warming = + 4 F

  • Many other processes within real climate system will modulate this baseline, but not sure exactly how

  • Use Global Circulation Models to explore possible future climates

    • Suggest 2x CO2 will yield closer to +6 F warming


Thanks! Questions?

References

  • Book: Archer, David, “Global Warming: Understanding the Forecast”

  • Manabe, S., and R. F. Strickler (1964), Thermal equilibrium of the Atmosphere with a convective adjustment, J. Atmos. Sci., 21(4),361–385.


There’s more!

Discussion Series – “The Science Behind

Climate Change”

November 19, Noon-1pm

66-148

Thanks!


Did Global warming cause Hurricane Sandy?

Wrong question – but might be able to quantify things like:

Was Sandy’s surge more destructive due to climate change? (link through sea level rise)

Are storms like Sandy going to be more frequent in a warmer climate? (talk about ocean warming trends, changes in mid-latitude storm tracks due to sea ice loss, etc)


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