Ten-Year Simulations Ten-Year Simulations of of

U.S. Regional ClimateU.S. Regional Climate Z. Pan, Z. Pan, W. J. Gutowski, Jr.,W. J. Gutowski, Jr., R. W. Arritt, R. W. Arritt,

E. S. Takle, F. Otieno, C. Anderson, M. SegalE. S. Takle, F. Otieno, C. Anderson, M. SegalIowa State UniversityIowa State University

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

Copenhagen, DenmarkCopenhagen, Denmark

START Temperate East Asia Regional Center (February 2000)

OutlineOutline

OverviewOverview Comparison with ObservationsComparison with Observations

PrecipitationPrecipitation TTminmin, T, Tmaxmax

Biases as norms for evaluating climate changeBiases as norms for evaluating climate change PrecipitationPrecipitation TTminmin, T, Tmaxmax

ConclusionsConclusions

START Temperate East Asia Regional Center (February 2000)

OutlineOutline

OverviewOverview

START Temperate East Asia Regional Center (February 2000)

Simulations

Model Observed GCM-control GCM-Scenario

RegCM2 NCEPReanalysis(1979-1988)

HadleyCentre(~1990’s)

HadleyCentre(2040-2050)

HIRHAM(DMI)

“ “ “

Domain

Purpose

Evaluate RCM performanceCompare RCM and GCM projectionsAssess U.S. regional climate change

uncertainty

OutlineOutline

Overview Comparison with ObservationsComparison with Observations

PrecipitationPrecipitation TTminmin, T, Tmaxmax

START Temperate East Asia Regional Center (February 2000)

RegCM2 Bias VEMAP

JAN

JUL

0-2 +2 [mm/d]+4 +6- 4

Self-Organizing Maps

Set of maps• Trained to distribution of data• Give 2-D projection of higher order map space

• Show characteristic data structures

• Are approximately continuous

“Robert Johnson” box: (31-35 N, 85-90 W)

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 88Year

WinterSpringSummerAutumn

Range: 650 - 850 mm

HIRHAM

0

200

400

600

800

1000

79 80 81 82 83 84 85 86 87 88

Year

WinterSpringSummerAutumn

Range: 590 - 870 mm

Tmin/Tmax Problem: Model elevations different from observing stations

O OO O

O

Tmin/Tmax Problem: Model elevations different from observing stations

O OO O

“Solution”: Interpolate to common elevation using dT/dz = - 6.5 K/km

(common = real world @ 1/2 deg)

O

+2.5-2.5 +12.5-12.5 +22.5

[C]

10 Year Mean Maximum Temperature - RegCM2

+2.5-2.5 +12.5-12.5 +22.5

[C]

10 Year Mean Maximum Temperature - DMI

+2.5-2.5 +12.5-12.5 +22.5

[C]

10 Year Mean Minimum Temperature - RegCM2

+2.5-2.5 +12.5-12.5 +22.5

[C]

10 Year Mean Minimum Temperature - DMI

OutlineOutline

Overview Comparison with Observations

Precipitation Tmin, Tmax

Biases as norms for evaluating climate changeBiases as norms for evaluating climate change PrecipitationPrecipitation TTminmin, T, Tmaxmax

START Temperate East Asia Regional Center (February 2000)

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

Definition of Biases

Reanalysis

HadCM

RegCM2

RegCM2

Definition of Biases

Forcingbias

HadCM

RegCM2

HadCM

Definition of Biases

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 PPPMaxP

RΔΔΔ

Δ=

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

Southeast U.S.

-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 PPPMaxP

RΔΔΔ

Δ=

HIRHAM

0

1

2

3

4

5

6

7

PNW CA MW NE SE

Region

Rchng

winterspringsummerautumn

Include hereTmin/max transparenciesDegree-daysWind power

OutlineOutline

Overview Comparison with Observations

Precipitation Tmin, Tmax

Biases as norms for evaluating climate change Precipitation Tmin, Tmax

ConclusionsConclusions

START Temperate East Asia Regional Center (February 2000)

Conclusions

RegCM2 simulates broad-scale regional features fairly well.

Interannual variability in RegCM2 (and HIRHAM) is less than observed.

Specific regions and seasons pose special challenge to RegCM2, e.g., south-central US Timing of events good Magnitude poor Moisture transport problem?

START Temperate East Asia Regional Center (February 2000)

Climate change is 1-3 times larger than biases in most seasons and regions summer ratios are always less than 1

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

START Temperate East Asia Regional Center (February 2000)

Conclusions

Regional warming signal is less robust than precipitation change

Future warming projection has large inter-model differences

Warming greater for Tmin than Tmax

Warming greater for winter than summer

START Temperate East Asia Regional Center (February 2000)

Conclusions

Acknowledgments

Primary Funding: Electric Power Research Institute (EPRI)

Additional Support: U.S. National Oceanic and Atmospheric AdministrationU.S. National Science Foundation

START Temperate East Asia Regional Center (February 2000)

EXTRA SLIDES

Definition of Biases

RCM (performance) bias - difference between reanalysis-driven RCM simulation and observations

forcing bias - difference between runs driven by GCM control climate and driven by reanalysis

inter-model bias - difference between runs from different RCMs (HIRHAM minus RegCM2), both driven by reanalysis

G-R nesting bias – difference between GCM run and RCM run driven by GCM output, both for current climate.