simulating and forecasting regional climates of the future

Simulating and Forecasting Simulating and Forecasting Regional Climates of the FutureRegional Climates of the Future

William J. Gutowski, Jr.William J. Gutowski, Jr.Dept. Geological & Atmospheric SciencesDept. Geological & Atmospheric Sciences

Dept. of AgronomyDept. of AgronomyIowa State UniversityIowa State University

Major contributions fromMajor contributions from::Z. Pan, R. W. Arritt, C. Anderson, F. Otieno, E. S. TakleZ. Pan, R. W. Arritt, C. Anderson, F. Otieno, E. S. Takle

Iowa State UniversityIowa State University

J. H. Christensen, O. B. ChristensenJ. H. Christensen, O. B. ChristensenDanish Meteorological Institute Danish Meteorological Institute

Copenhagen, DenmarkCopenhagen, Denmark

ISU Plant Pathology (March 2001)

• Regional Climate Models (RCMs)Regional Climate Models (RCMs)

– Why?Why?

– Physical BasisPhysical Basis

– Simulation Considerations

• A Norm to Evaluate Projected ChangeA Norm to Evaluate Projected Change

• Conclusions

OutlineOutline



– Why?Why?

– Physical Basis


• A Norm to Evaluate Projected Change

• Conclusions

OutlineOutline


Global Climate Models:

• nearly closed system

• complete representation

Why Regional Climate Models?Why Regional Climate Models?

Global Climate Models:

• nearly closed system

• complete representation


However:

• high computing demands

• limits resolution

• many surface features unresolved (esp. human-scale)

Regional Climate Models:Regional Climate Models:

• sacrifice global coveragesacrifice global coverage

• higher resolutionhigher resolution


Global Global Model Model ResolutionResolution

X = 250 kmX = 250 km

contours every 250 m

TERRAIN HEIGHT


TERRAIN HEIGHT

Regional Regional Model Model ResolutionResolution

X = 50 kmX = 50 km


FutureFuture Model Model Resolution?Resolution?

X = 10 kmX = 10 km

TERRAIN HEIGHT


– Why?Why?

– Physical Basis



• Conclusions

OutlineOutline


1. Conservation of Thermodynamic Energy (First Law of Thermodynamics)

2. Conservation of Momentum (Newton’s Second Law)

3. Conservation of Mass

RCM Foundation: Conservation Laws of Physics

Conservation of “M”

ΔMΔt

=?


ΔMΔt

≠0

Source/sink≠0


ΔMΔt

≠0


Source/sink≠0

ΔMΔt

≠0

1. Conservation of Thermodynamic Energy (First Law of Thermodynamics):

Heat input = internal energy) + (work done)


Transport and accumulation by circulation

“Contact” heat exchange Radiation to/from surface

Heat Source/Sink

Condensation

Radiation to/from space

2. Conservation of Momentum (Newton’s Second Law):

wind)/ time) = forces)


3. Conservation of Mass:

Special constituent - water


Evapotranspiration Precipitation

MoistureIn/Out

Δ Moisture( )Δt

≠0

EP P

Q Q

R

Water CycleWater Cycle

E

E


Heat absorbedHeat absorbed

Heat releasedHeat released

Water is thus a primaryWater is thus a primary form of heat transportform of heat transport

heat absorbed when evaporates heat absorbed when evaporates

released when water condensesreleased when water condenses

largest individual source of energy largest individual source of energy

for the atmospherefor the atmosphere


Radiation absorbed by water & re-emittedRadiation absorbed by water & re-emitted

Water is thus a primaryWater is thus a primary form of heat transportform of heat transport

heat absorbed when evaporates heat absorbed when evaporates

released when water condensesreleased when water condenses

largest individual source of energy largest individual source of energy

for the atmospherefor the atmosphere

andand greenhouse gas greenhouse gas

~ transparent to solar~ transparent to solar

absorbs/emits infraredabsorbs/emits infrared

1. Conservation of Thermodynamic Energy (First Law of Thermodynamics)

2. Conservation of Momentum (Newton’s Second Law)

3. Conservation of Mass

Plus: Ideal Gas Law

RCM Foundation: Fundamental Laws of Physics


– Why?Why?




• Conclusions

OutlineOutline


EvapotranspirationEvapotranspiration


E ~ - CW{eair-esat(Ts)}

CW = CW(atmos.)

but also

CW = CW(physiology)

soil moisture

CW leaf temp.

sunlight

CO2 level


E ~ - CW{eair-esat(Ts)}

RCM Horizontal Grid

I

J(1,1)

(IMAX,JMAX)

How does a “flat” grid ...

RCM Horizontal Grid

How does a “flat” grid ...

...represent part of the spherical earth?

?

RCM Horizontal Grid

By projection to a flat plane

RCM Horizontal Grid

PolarStereographic

True at 90o

RCM Horizontal Grid

Lambert Conformal

True at, e.g.,30o and 60o

RCM Horizontal Grid

Mercator

True at 0o

RCM Horizontal Grid

Forcing Frame:for lateral

boundary conditions“free” interior

RCM Horizontal Grid

E

P

Q

R

Earth Climate SystemEarth Climate System

E

GlobalRegional Regional Regional Regional

Microscale Microscale Microscale Microscale Microscale Microscale Microscale Microscale Microscale

Pla

nt A

Crop BCrop A

Inse

ct A

Soi

l Pat

hoge

n B

Air-TransportedPathogen A

Field Field Field Field Field Field Field Field Field Field

Regional Regional Regional Regional

Continental

Hydrology, Soil Microbiology, Soil Biochemistry

Soil AH2O, temperature,

nutrients, microbes, soil carbon, trace chemicals

Soil AH2O, temperature,


Soil BH2O, temperature,


Soil BH2O, temperature,


Soil CH2O, temperature,


Scales of Climate

Scales of Landforms

Soi

l Pat

hoge

n D

Pla

nt B

Inse

ct B

Air-TransportedPathogen B

Human Influences

Management Management

Che

mic

als

Ero

sion

Che

mic

als

Surf

ace

s lop

e, I

R R

adi a

t ion

, Eva

pora

t ion

, Bio

geoc

hem

i cal

s

Detritus

Particulate D

eposition, Precipitation, S

olar Radiation, IR

Microclimate A

Sol

ar, I

R, w

ind,

CO

2, C

O, N

Ox,S

O2,

H2O

, tem

pera

ture

,

trac

e ga

ses,

shad

ing,

pa

rtic

ulat

e m

atte

r

Sol

ar, I

R, w

ind,

CO

2, C

O, N

Ox,S

O2,

H2O

, tem

pera

ture

,

trac

e ga

ses,

shad

ing,

pa

rtic

ulat

e m

atte

r

Sol

ar, I

R, w

ind,

CO

2, C

O, N

Ox,S

O2,

H2O

, tem

pera

ture

,

trac

e ga

ses,

shad

ing,

pa

rtic

ulat

e m

atte

r

Microclimate CMicroclimate B

ChemicalsChem

icals


– Why?Why?




• Conclusions

OutlineOutline


Simulate decades/centuries into futureSimulate decades/centuries into future

How are projections verified?How are projections verified?

Projections of Future Climate


How are projections verified?How are projections verified?• Accuracy of present climate simulation?Accuracy of present climate simulation?



How are projections verified?How are projections verified?• Accuracy of present climate simulation?Accuracy of present climate simulation?• Accuracy of paleoclimate simulation?Accuracy of paleoclimate simulation?



How are projections verified?How are projections verified?• Accuracy of present climate simulation?Accuracy of present climate simulation?• Accuracy of paleoclimate simulation?Accuracy of paleoclimate simulation?• Alternative …Alternative …



How are projections verified?How are projections verified?• Accuracy of present climate simulation?Accuracy of present climate simulation?• Accuracy of paleoclimate simulation?Accuracy of paleoclimate simulation?• Alternative … Alternative …


Cross-Compare Multiple SimulationsCross-Compare Multiple Simulations

Model Observed GCM-control GCM-Scenario

RegCM2 NCEPReanalysis(1979-1988)

HadleyCentre(~1990’s)

HadleyCentre(2040-2050)

HIRHAM(DMI)

“ “ “

Simulation DomainSimulation Domain

Reanalysis

HadCMCont/Scen

RegCM2

HIRHAM

Possible Comparisons?

OBS

HadCMCont/Scen

Driving Differences

Definition of Biases

Reanalysis RegCM2 OBS

RCM (performance) bias

Reanalysis RegCM2

HIRHAM

Inter-modelbias


Reanalysis

HadCM

RegCM2

RegCM2


Forcingbias

HadCM

RegCM2

HadCM


G-R nestingbias

HadCM control

HadCMscenario

RegCM2

RegCM2

Climate Change

Change

Climate Change

P

Control Scenario

Change

Climate Change

P

Control Scenario

ChangeMax Bias

Analysis Regions

California

-3

-2

-1

0

1

2

3

win spr sum aut anu

season

RCM biasforcing biasintermodel biasG-R nesting biasclimate change

RegCM2

0

1

2

3

4

5

6

7

PNW CA MW NE NS

Region

winter

spring

summer

autumn

SE

HIRHAM

0

1

2

3

4

5

6

7

PNW CA MW NE SE

Region

winterspringsummerautumn

0

100

200

300

400

500

AUG OCT DEC FEB APR JUN

ReGCM2 Sierra

NCEPHCONTHSCEN

Month

0

100

200

300

400

500

AUG OCT DEC FEB APR JUN

HIRHAM Sierra

NCEPHCONTHSCEN

Month

Annual Snow Cycle


– Why?Why?




• Conclusions

OutlineOutline



FIELD POSSIBLECHANGE

CONFIDENCE **

Precipitation + 3-5 mm/d(North)

+ 0-1 mm/d(South)

good

fair

Tmin, Tmax + 2 – 3 oC fair

Snow - 0-50% poor

** = Subject to quality of driving GCM!


• Ratio of climate change to biases is especially Ratio of climate change to biases is especially large in the California regionlarge in the California region

• Differences between RCM and GCM imply Differences between RCM and GCM imply room for RCMs to add value to GCM room for RCMs to add value to GCM simulationssimulations

• Regional warming signal is less robust than Regional warming signal is less robust than precipitation changeprecipitation change

• Future warming projection has large inter-Future warming projection has large inter-model differencesmodel differences

Conclusions

Acknowledgments

Primary Funding: Electric Power Research Institute (EPRI)

Additional Support: U.S. National Oceanic and Atmospheric

AdministrationU.S. National Science Foundation


EXTRA SLIDES

Southeast U.S.

-3

-2

-1

0

1

2

3

4

win spr sum aut anu

season

RCM bias forcing biasintermodel bias G-R nesting biasclimate change

Pre

cip

[m

m/d

ay]

2 3

45

1

Analysis Points

0

5

10

15

20

OBS-1 NC-1 HCont-1 HScen-1

October - March (RegCM2)

0

5

10

15

20



[mm/d]

0

5

10

15

20



[mm/d]

0

5

10

15

20



[mm/d]

0

5

10

15

20



[mm/d]

0

5

10

15

20



[mm/d]

0

2

4

6

8


April-September (RegCM2)

0

2

4

6

8



[mm/d]

0

2

4

6

8



[mm/d]

0

2

4

6

8



[mm/d]

0

2

4

6

8



[mm/d]

0

2

4

6

8



[mm/d]

Precipitation RegionsPrecipitation Regions

UpperMiss.

observation

0

200

400

600

800

1000

79 80 81 82 83 84 85 86 87 88

Year

WinterSpringSummerAutumn

Range: 600 - 970 mm

RegCM2

0

200

400

600

800

1000

79 80 81 82 83 84 85 86 87 88

Year


Range: 650 - 850 mm

HIRHAM

0

200

400

600

800

1000

79 80 81 82 83 84 85 86 87 88

Year


Range: 590 - 870 mm

Energy Balance for EarthEnergy Balance for Earth


Planetary Planetary Albedo Albedo

Conservation of MomentumConservation of Momentum~ Newton’s Second Law ~~ Newton’s Second Law ~

Forces/mass:Forces/mass: gravitygravity pressure gradientpressure gradient frictionfriction


Rotating Frame

r Ω

r R

X

dr V 3dt

= (Forces/ mass)∑

−2r Ω ×

r V 3 +

r Ω

2 r R


Rotating Frame

dudt

−uvtanφ

a+

uwa

=−1ρ

∂p∂x

+2Ωvsinφ−2Ωwcosφ+Frx


Sphere, Rotating Frame

dvdt

−u2 tanφ

a+

vwa

=−1ρ

∂p∂y

−2Ωusinφ +Fry

dwdt

−u2 +v2

a=−

1ρ

∂p∂z

+2Ωucosφ −g+Frz

rotation of direction

simulating and forecasting regional climates of the future

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global climate models

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conservation laws of

mconservation of mconservation

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