What RCM Data Are Available for California Impacts Modeling? (How Good Is It?)

What RCM Data Are Available for What RCM Data Are Available for California Impacts Modeling?California Impacts Modeling?

(How Good Is It?)(How Good Is It?)

W. J. Gutowski, Jr., Z. Pan, C. Anderson, W. J. Gutowski, Jr., Z. Pan, C. Anderson,

R. W. Arritt, F. Otieno, E. S. TakleR. W. Arritt, F. Otieno, E. S. Takle

Iowa State UniversityIowa State University

J. H. Christensen, O. B. ChristensenJ. H. Christensen, O. B. Christensen

Danish Meteorological Institute Danish Meteorological Institute

Copenhagen, DenmarkCopenhagen, Denmark

California Energy Commission (June 2000)

OutlineOutline

Overview - Regional Climate SimulationOverview - Regional Climate Simulation

Biases as norms for evaluating climate changeBiases as norms for evaluating climate change PrecipitationPrecipitation

TTminmin, T, Tmaxmax

Climate change for selected locations in CAClimate change for selected locations in CA

Conclusions: Ranges for scenariosConclusions: Ranges for scenarios


OutlineOutline

Overview - Regional Climate SimulationOverview - Regional Climate Simulation


What is an RCM? Much like a GCM but ...

Sample RCM Output

X = 250 km

contours every 250 m

X = 50 km


X = 10 km


US Simulations Longer Than 1 Year

Authors Driver Res.[km]

Duration[YR]

Giorgi et al. (1993) Analysis 60 2

Giorgi et al. (1994) GCMpresent

60 3.5

GCMscenario

60 3.5

Giorgi et al. (1998) GCMpresent

50 5

GCMscenario

50 5

Giorgi & Shields (1999) Analysis 60 3

Liston & Pielke (1999) Analysis 50 1

Miller et al. (2000) Analysis 36 8

Pan et al. (2000) Analysis 55 10

[2 models] GCMpresent

55 10

GCMscenario

55 10

Simulations

Model Observed GCM-control GCM-Scenario

RegCM2 NCEPReanalysis(1979-1988)

HadleyCentre(~1990’s)

HadleyCentre(2040-2050)

HIRHAM(DMI)

“ “ “

Domain

Purpose

Evaluate RCM performance

Compare RCM and GCM projections

Assess U.S. regional climate change uncertainty

OutlineOutline

Overview - Regional Climate Simulation

Biases as norms for evaluating climate changeBiases as norms for evaluating climate change PrecipitationPrecipitation

TTminmin, T, Tmaxmax


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

Seasonal-regional biases

Po, Pm are observed, model precipitation

N is total grids in the region

),,( itmdforcRCM

chng

chng PPPMax

PR

=

Climate change ratio

ΔPRCM =1N

Pim−Pi

o( )

i=1

N

∑

Definitions

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

Rchng

winterspringsummerautumn

),,( itmdforcRCM

chng

chng PPPMax

PR

=

HIRHAM

0

1

2

3

4

5

6

7

PNW CA MW NE SE

Region

Rchng

winter

spring

summer

autumn

Tmin, Tmax biases

OutlineOutline


Biases as norms for evaluating climate change Precipitation

Tmin, Tmax

Climate change for selected locations in CAClimate change for selected locations in CA


2 3

45

1

Analysis Points

0

5

10

15

20

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

October - March (RegCM2)

Distribution:Monthly Precipitation

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]

0

50

100

150

200

250

300

2 4 6 8 10 12

RegCM2 - POINT 3

NCEP-3HCont-3HScen-3

Month

CA Temp Biases:

Tmax - small, mixed Tmax - slightly cool

Tmin - warm (few oC) Tmin - small, mixed

0

100

200

300

400

500

2 4 6 8 10 12

HIRHAM - POINT 3

NCEPHContHScen

Month

PIRCSOBS

[mm]

(1993) (1993)

Other Models?

PIRCS

[mm]

(1993)

OutlineOutline


Biases as norms for evaluating climate change Precipitation

Tmin, Tmax

Climate change for selected locations in CA

Conclusions: Ranges for scenariosConclusions: Ranges for scenarios



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%decrease

poor

** = Subject to quality of driving GCM!

Conclusions

Interannual variability in RegCM2 and HIRHAM is less than observed.

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

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

Regional warming signal is less robust than precipitation change

Future warming projection has large inter-model differences


Acknowledgments

Primary Funding: Electric Power Research Institute (EPRI)

Additional Support: U.S. National Oceanic and Atmospheric Administration

U.S. National Science Foundation


What RCM Data Are Available for California Impacts Modeling? (How Good Is It?)

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