Can General Circulation Models be Trusted to Predict Global Warming? Yuk Ling Yung Presentation at...

Can General Circulation Can General Circulation Models be Trusted to Models be Trusted to

Predict Global Warming?Predict Global Warming?

Yuk Ling YungYuk Ling Yung

Presentation at the RCEC Academia SinicaPresentation at the RCEC Academia Sinica

Nov 28 2007Nov 28 2007

Future climate is like Dark Matter?

What is Greenhouse Effect? What is Greenhouse Effect? （（ Review)Review) GCM Prediction of Future (IPCC)GCM Prediction of Future (IPCC) NCAR Simulations (Deser, NCAR)NCAR Simulations (Deser, NCAR) Solar Cycle (Yau, CUHK)Solar Cycle (Yau, CUHK) Cloud Feedback (Li, CIT)Cloud Feedback (Li, CIT) Long Period OscillationsLong Period Oscillations (Heavens, CIT) Conclusions (Poetry)

Today’s OutlineToday’s Outline

What is Greenhouse Effect?What is Greenhouse Effect?

Absorption in Earth’s Atmosphere

O3

H2O

H2O

CO2

What is Greenhouse Effect?What is Greenhouse Effect? GCM Prediction of FutureGCM Prediction of Future NCAR 50 yearsNCAR 50 years Solar CycleSolar Cycle Cloud Feedback Cloud Feedback Long Period OscillationsLong Period Oscillations

Today’s OutlineToday’s Outline

What is Greenhouse Effect?What is Greenhouse Effect? GCM Prediction of FutureGCM Prediction of Future NCAR 50 yearsNCAR 50 years Solar CycleSolar Cycle Cloud Feedback Cloud Feedback Long Period OscillationsLong Period Oscillations

Today’s OutlineToday’s Outline

Atmospheric Radiative ForcingCO2 Increase and Ozone Depletion

Figure 9.1

From IPCC 2007 Report Chapter 9

Simulated Temperature Change 1890-1999

warming

cooling

Cooling due toozone depletion

Alti

tud

e

(hP

a)

°C/century

Alti

tud

e

(km

)

C

90°N 60°N 30°N 0° 30°S 60°S 90°S

Sea Level Pressure Trend 1950-2000OBSERVATIONS MODEL

+1.9- 2.9

+1.6- 4.2

- - - Linear trend significantly different from zero (0.05 P)

0.73

Sea Level Pressure Trend 1950-2000OBSERVATIONS MODEL

+1.9- 2.9

+1.6- 4.2

0.73

0.76

500 hPa Geopotential Height Trend

Oceanic vs. Atmospheric Radiative ForcingSea Level Pressure Trend 500 hPa Height Trend

BOTH

OCEAN

ATMOS

Oceanic vs. Atmospheric Radiative ForcingSea Level Pressure Trend 500 hPa Height Trend

BOTH

OCEAN

ATMOS

What is Greenhouse Effect?What is Greenhouse Effect? GCM Prediction of FutureGCM Prediction of Future NCAR 50 yearsNCAR 50 years Solar CycleSolar Cycle Cloud Feedback Cloud Feedback Long Period OscillationsLong Period Oscillations

Today’s OutlineToday’s Outline

Model G O SD SI BC OC MD SS LU SO VL Members

1 CCSM3 x x x -- x x -- -- -- x x 8

2 FGOALS--g1.0 x -- x ? -- -- -- -- -- -- -- 33 GFDL--CM2.0 x x x -- x x -- -- x x x 34 GFDL--CM2.1 x x x -- x x -- -- x x x 35 GISS--EH x x x x x x x x x x x 56 GISS--ER x x x x x x x x x x x 97 INM--CM3.0 x -- x -- -- -- -- -- -- x -- 18 MIROC3.2(medres) x x x ? x x x x x x x 39 MIROC3.2(hires) x x x ? x x x x x x x 110 MIUB/ECHO--G x -- x x -- -- -- -- -- x x 511 MRI--CGCM2.3.2 x -- x -- -- -- -- -- -- x x 512 PCM x x x -- -- -- -- -- -- x x 4

1 BCCR--BCM2.0 x -- x -- -- -- -- -- -- -- -- 1

2 CCCma--CGCM3.1(T47) x -- x -- -- -- -- -- -- -- -- 5

3 CCCma--CGCM3.1(T63) x -- x -- -- -- -- -- -- -- -- 1

4 CNRM--CM3 x x x -- x -- -- -- -- -- -- 15 CSIRO--Mk3.0 x -- x -- ? ? ? ? ? x -- 36 ECHAM5/MPI--OM x x x x -- -- -- -- -- -- -- 47 FGOALS--g1.0 x -- x ? -- -- -- -- -- -- -- 38 GISS--AOM x -- x -- -- -- -- x -- -- -- 29 IPSL--CM4 x -- x x -- -- -- -- -- -- -- 210 UKMO--HadGEM1 x x x x x x -- -- x -- x 111 UKMO--HadCM3 x x x x -- -- -- -- -- -- -- 2

G = Well--mixed greenhouse gases O = Tropospheric and stratospheric ozone SD = Sulfate aerosol direct effects SI = Sulfate aerosol indirect effects BC = Black carbon OC = Organic carbon MD = Mineral dust SS = Sea salt LU = Land use change SO = Solar irradiance VL = Volcanic aerosols.

What is Greenhouse Effect?What is Greenhouse Effect? GCM Prediction of FutureGCM Prediction of Future NCAR 50 yearsNCAR 50 years Solar CycleSolar Cycle Cloud FeedbackCloud Feedback Long Period OscillationsLong Period Oscillations

Today’s OutlineToday’s Outline

F(x,t,ν) =Σi fi(x,t)gi(ν)

<fi(x,t)> = Time average of fi(x,t)

Spectral Empirical Orthogonal Spectral Empirical Orthogonal FunctionsFunctions

What is Greenhouse Effect?What is Greenhouse Effect? GCM Prediction of FutureGCM Prediction of Future NCAR 50 yearsNCAR 50 years Solar CycleSolar Cycle Cloud Feedback Cloud Feedback Long Period OscillationsLong Period Oscillations

Today’s OutlineToday’s Outline

Winter Aleutian Low SLP Index

Tropical Indo-Pacific Climate Index

Deser et al., 2004

Tropics & Aleutian Low: Additional Evidence for Natural Variability

What is Greenhouse Effect? What is Greenhouse Effect? （（ Review)Review) GCM Prediction of Future (IPCC)GCM Prediction of Future (IPCC) NCAR Simulations (Deser, NCAR)NCAR Simulations (Deser, NCAR) Solar Cycle (Yau, CUHK)Solar Cycle (Yau, CUHK) Cloud Feedback (Li, CIT)Cloud Feedback (Li, CIT) Long Period OscillationsLong Period Oscillations (Heavens, CIT) Conclusions (Poetry)

Today’s OutlineToday’s Outline

司馬光(1019-1086 )

夫事未有不生於微而成於著，聖人之慮遠，故能謹其微而治之，眾人之識近，故必待其著而後救之；治其微則用力寡而功多，救其著則竭力而不能及也。

﹝資治通鑑‧卷一﹞

It happens then as it does to physicians in the treatment of consumption, which in the commencement is easy to cure and difficult to understand; but when it has neither been discovered in due time nor treated upon a proper principle, it becomes easy to understand and difficult to cure. The same happens in state affairs; by foreseeing them at a distance … the evils which might arise from them are soon cured; but when, from want of foresight, they are suffered to increase to such a height that they are perceptible to everyone, there is no longer any remedy. [The Prince]

Niccolo Machiavelli(1469-1527)

從軍行從軍行﹝﹝其四其四 ﹞ ﹞ 王昌齡王昌齡

青海長雲暗雪山 孤城遙望玉門關青海長雲暗雪山 孤城遙望玉門關黃沙百戰穿金甲 不破樓蘭終不還黃沙百戰穿金甲 不破樓蘭終不還

ConclusionsConclusions Short term prediction reasonably goodShort term prediction reasonably good

(not covered)(not covered)

Stratosphere coolingStratosphere cooling

Volcanic eruptionsVolcanic eruptions

Low frequency variability (associated with oceans) poorLow frequency variability (associated with oceans) poor Non--linear effects may be underestimatedNon--linear effects may be underestimated

ThanksThanks

Yung’s Group at CaltechYung’s Group at Caltech Clara Deser (NCAR)Clara Deser (NCAR) David Camp (CalPoly SLOB)David Camp (CalPoly SLOB) K. K. Tung (UW)K. K. Tung (UW) Duane Waliser (JPL)Duane Waliser (JPL)