Climate Modeling

18
Climate Modeling Climate Modeling Inez Fung Dept of Earth and Planetary Science Dept of Environmental Science, Policy and Management UC Berkeley

description

Climate Modeling. Inez Fung Dept of Earth and Planetary Science Dept of Environmental Science, Policy and Management UC Berkeley. Atmosphere. momentum. mass. energy. water vapor. convective mixing. Ocean. momentum. mass. energy. salinity. Earth’s Energy Balance, with GHG. Sun. - PowerPoint PPT Presentation

Transcript of Climate Modeling

Climate ModelingClimate Modeling

Inez FungDept of Earth and Planetary Science

Dept of Environmental Science, Policy and Management

UC Berkeley

mass

energy

water vapor

momentum

)(

...),,,(

,...),(

)(

),(;

0)(

)(ˆ12

2

qonCondensatiEvapqutq

GHGCOqTfLW

aerosolscloudsfSW

TLHSHLWSWTutT

qTfRTp

ut

uFkgpuuutu

ℑ+−=∇•+∂∂

==

ℑ++++=∇•+∂∂

==

=•∇+∂∂

ℑ+++∇−=×Ω+∇•+∂∂

r

bbr

r

rrrrrr

ρρ

ρρ

ρ

Atmosphere

ℑ convective mixing

Ocean

momentum

mass

energy

salinity )()(

)(

),(;0

0

12

00

03

03

2

00

2222

sPEz

ssu

ts

TQTutT

sTfgzp

zw

u

Fpuuutu

ℑ+−Δ

=∇•+∂∂

ℑ+=∇•+∂∂

=+∂∂

−=

=∂∂

+•∇

++∇−=×Ω+∇•+∂∂

ρ

ρρ

τρ

r

r

r

rrrrrr

Earth’s Energy Balance, with GHG

COCO22, H, H22O, GHGO, GHG

Earth

70

95114

23

7

50 absorbed by sfc

Sun

30

20 absorbed by atm

100

Climate Processes

• Radiative transfer: solar & terrestrial

• phase transition of water

• Convective mixing• cloud microphysics• Evapotranspirat’n• Movement of heat

and water in soils

Climate Feedbacks

Warming

Decrease snow cover;Decrease reflectivity of surfaceIncrease absorption of solar energy

Increase cloud cover;Decrease absorption of solar energy

Evaporation from ocean,Increase water vapor in atmEnhance greenhouse effect

Observed Warming greatest at high

latitudes

Amplification of warming due to decrease of albedo (melting of snow and ice)

Will cloud cover increase or decrease with warming? [models: decrease; warm air can hold more moisture; +ve feedback]

A B + water vapor + longwave abs Warming

A C + water vapor + cloud cover + longwave abs - shortwave abs

275 280 285 290 295 3000

5

10

15

20

25

30

35

40

1 2 3 4 5 6

Temperature (K)

Sat

urat

ion

Vap

or P

ress

ure

(mb)

A

B

Cliquid

vapor

“Externally Forced” climate variability: Milankovitch Cycles (Orbital Variations)

Co-Variations of CO2 and Climate

100

150

200

250

300

0 50 100 150 200 250 300 350 400 450

Thousand Years Before Present

CO2 (ppmv)

-10

-5

0

5

10

Te

mp

era

t ur e

De

pa r

t ur e

(K

)

120,000 yr

Last Glacial Max

e.g.•El-Nino / Southern Oscillation

•Instability of the air-sea system in the equatorial pacific

•Irregular

•2-7 year

“Internal” Variability of the Climate System

1885

1995

Climate Forcing: expressed as a change in radiative heating (W/m2) at surface for a given change in trace gas composition or other change external to the climate system

Hansen PNAS 2001

Cumulative climate forcing since 1800

Ship Tracks:- more cloud condensation nuclei- smaller drops- more drops- more reflective- Δ energy balance

Numerical Weather Prediction ( ~ days)

Initial Conditions

t = 0 hr

Prediction t = 6 hr 12 18 24

1st Numerical Weather Prediction Experiment • Charney, Fjortoft and von Neumann (1950, Tellus) • Barotropic Vorticity Eqn • ENIAC computer (10 word memory) • 1 layer over N America

Now: Operational forecasts (model validation in ~days); require model + initial conditions (obs atm)

Seasonal Climate Prediction ( ~ months) ( El – Nino Southern Oscillation )

{ Initial Conditions}

Atm + Ocn t = 0

{Prediction}

t = 1 mo 2 3

• Coupled atmosphere-ocean instability• Require observations of initial states of both atm & ocean, esp. Equatorial Pacific• Cane & Zebiak ( 1986, 1987)• {Ensemble} of forecasts • Forecast statistics (mean & variance) – probability• Now – experimental forecasts (model testing in ~months)

Climate Models Capture Magnitude and Timing of Recent Warming

Meehl et al. 2006; Hansen et al. 2005

Published by AAAS

G. A. Meehl et al., Science 305, 994 -997 (2004)

Fig. 3. Height anomalies at 500 hPa (gpm) for the 1995 Chicago heat wave (anomalies for 13 to 14 July 1995 from July 1948 to 2003 as base period), from NCEP/NCAR

reanalysis data (A) and the 2003 Paris heat wave (anomalies for 1 to 13 August 2003 from August 1948 to 2003 as base period), from NCEP/NCAR reanalysis data (B)

Published by AAAS

G. A. Meehl et al., Science 305, 994 -997 (2004)

Fig. 4. Height anomalies at 500 hPa (gpm) for events that satisfy the heat wave criteria in the model in future climate (2080 to 2099) for grid points near Chicago (A)

and Paris (B), using the same base period as in Fig

21stC warming depends on CO2 increase

20thC stabilizn:CO2 constant at 380 ppmv for the 21stC

21thC “Business as usual”:CO2 increasing 380 to 680 ppmv

Meehl et al. (Science 2005)