Ten-Year Simulations of U.S. Regional Climate Z. Pan, W. J. Gutowski, Jr., R. W. Arritt, E. S. Takle, F. Otieno, C. Anderson, M. Segal Iowa State University J. H. Christensen, O. B. Christensen Danish Meteorological Institute Copenhagen, Denmark START Temperate East Asia Regional Center(February 2000)

Outline Overview Overview Comparison with Observations Comparison with Observations  Precipitation  T min, T max Biases as norms for evaluating climate change Biases as norms for evaluating climate change  Precipitation  T min, T max Conclusions Conclusions START Temperate East Asia Regional Center(February 2000)

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

Simulations

Domain

Purpose  Evaluate RCM performance  Compare RCM and GCM projections  Assess U.S. regional climate change uncertainty

Outline Overview Comparison with Observations Comparison with Observations  Precipitation  T min, T max START Temperate East Asia Regional Center(February 2000)

RegCM2BiasVEMAP JAN JUL [mm/d]

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, W)

Precipitation Regions Upper Miss.

Range: mm

Range: mm

Range: mm

T min /T max Problem: Model elevations different from observing stations O O O O O

T min /T max Problem: Model elevations different from observing stations O O O O “Solution”: Interpolate to common elevation using dT/dz = K/km (common = real 1/2 deg) O

[C] 10 Year Mean Maximum Temperature - RegCM2

[C] 10 Year Mean Maximum Temperature - DMI

[C] 10 Year Mean Minimum Temperature - RegCM2

[C] 10 Year Mean Minimum Temperature - DMI

Outline Overview Comparison with Observations  Precipitation  T min, T max Biases as norms for evaluating climate change Biases as norms for evaluating climate change  Precipitation  T min, T max START Temperate East Asia Regional Center(February 2000)

Reanalysis HadCM Cont/Scen RegCM2 HIRHAM Possible Comparisons? OBS HadCM Cont/Scen Driving Differences

Definition of Biases ReanalysisRegCM2OBS RCM (performance) bias

ReanalysisRegCM2 HIRHAM Inter-model bias Definition of Biases

Reanalysis HadCM RegCM2 Definition of Biases Forcing bias

HadCM RegCM2 HadCM Definition of Biases G-R nesting bias

HadCM control HadCM scenario RegCM2 Climate Change Change

Climate Change P Control Scenario Change

Climate Change P Control Scenario Change Max Bias

Analysis Regions

Seasonal-regional biases P o, P m are observed, model precipitation N is total grids in the region Climate change ratio Definitions

Include here Tmin/max transparencies Degree-days Wind power

Outline Overview Comparison with Observations  Precipitation  T min, T max Biases as norms for evaluating climate change  Precipitation  T min, T max Conclusions Conclusions 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 T min than T max 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 Administration U.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.