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Outline Overview Overview START Temperate East Asia Regional Center(February 2000)
Citation preview
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.