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Project to Intercompare Regional Climate Simulations (PIRCS): Lessons and Suggestions for an Asian RMIP. W. J. Gutowski, R. W. Arritt, G. S. Takle, Z. Pan International Institute of Theoretical and Applied Physics Iowa State University (http://www.pircs.iastate.edu).
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Project to Intercompare Regional Climate Simulations(PIRCS):Lessons and Suggestions for an Asian RMIP W. J. Gutowski, R. W. Arritt, G. S. Takle, Z. Pan International Institute of Theoretical and Applied Physics Iowa State University (http://www.pircs.iastate.edu) Asian RMIP Workshop (June 2000)
PIRCS Participating Models • Danish Met. Inst. (HIRHAM4; J.H. Christensen, O.B. Christensen) • Université du Québec à Montréal (D. Caya, S. Biner) • Scripps Institution of Oceanography (RSM; J. Roads, S. Chen) • NCEP (RSM; S.-Y. Hong) • NASA - Marshall (MM5/BATS; W. Lapenta) • CSIRO (DARLAM; J. McGregor, J. Katzfey) • Colorado State University (ClimRAMS; G. Liston) • Iowa State University (RegCM2; Z. Pan) • Iowa State University (MM5/LSM; D. Flory) • Univ. of Maryland / NASA-GSFC (GEOS; M. Fox-Rabinovitz) • SMHI / Rossby Centre (RCA; M. Rummukainen, C. Jones) • NOAA (RUC2; G. Grell) • ETH (D. Luethi) • Universidad Complutense Madrid (PROMES; M.Gaertner) • Université Catholique du Louvain (P. Marbaix) • Argnonne National Lab (MM5 V3; J. Taylor, J. Larson)
PIRCS Mission Evaluate regional climate simulation by mesoscale models, using a common framework Asian RMIP Workshop (June 2000)
Mesoscale Targets are Important! • Mesoscale Convective Systems • Low-Level Jets • Regional Orography Asian RMIP Workshop (June 2000)
Further Motivation • GCIP/G-NEP • Agricultural • Water cycle variability • Data availability • Strong signal Asian RMIP Workshop (June 2000)
Summer 1988 - Drought Jet Stream Cool & Damp Heat Wave Weak & Dry Southerly Flow Adapted from CAC, NWS, NOAA
Summer 1993 - Flood Cool Jet Stream FLood Heat Wave Warm & Moist Southerly Flow Adapted from CAC, NWS, NOAA
500 hPa heights: Root Mean Square Difference from Reanalysis1988
500 hPa heights: Root Mean Square Difference from Reanalysis1993
D500 hPa Heights (1993-1988) ~ Reanalysis ~
D500 hPa Heights (1993-1988) ~ PIRCS Ensemble ~
Precipitation Regions Upper Miss.
Comparison of PIRCS models with gridded precipitation analysis
Comparison of PIRCS models with gridded precipitation analysis
Precip. Bias June 1988 Composite [mm/d] -10 -8 -6 -4 -2 0 +2 +4 +6 +8 +10
Precip. Bias July 1993 Composite [mm/d] -10 -8 -6 -4 -2 0 +2 +4 +6 +8 +10
1993 Contours: qe (D = 6 K) Shaded: Precip > 300 mm
Lessons • Ensembles are important • Reveal common problems • Reveal unique problems • No model is “best” • Distinction between problems of • Lateral forcing/dynamics (common) • Surface processes (unique)
Lessons Lessons • Interannual climate variation • Simulated in large-scale dynamics • Muted in precipitation response
Future Plans • Same grid, multi-year • More truly climate simulation • Reduce initial conditions problem Asian RMIP Workshop (June 2000)
Future Plans • Same grid, multi-year • More truly climate simulation • Reduce initial conditions problem • PIRCS 2: South America - LBA • ENSO • Atmospheric heat source • Moisture inflow from Atlantic Ocean • Low-Level Jet? • Significant observational data bases Asian RMIP Workshop (June 2000)
Suggestions for Asian RMIP (1) Coordinate archive convections with PIRCS-2 (under development) - promote wider access/analysis - sharing of diagnostic tools - sharing of tools to transform output to standard format (2) Use NetCDF (3) Establish common file naming conventions Asian RMIP Workshop (June 2000)
Suggestions for Asian RMIP (4) Other variables? PIRCS 2 includes (among others): • CAPE (3 hr) • ISCCP clouds (3 hr) • OLR (3 hr) • 500 hPa vertical motion (3 hr) • Precipitable water (3 hr) • diabatic heating (monthly) Asian RMIP Workshop (June 2000)
Proposal for Standard Diagnostics and Data Interchange Modules in PIRCS Jay Larson Mathematics and Computer Science Division / Argonne National Laboratory www.mcs.anl.gov/~larson
An Intercomparison Wish List Common utilities for: • Writing and re-reading the agreed-upon output format • Reading / interpolating model input data format • Computation of diagnostic fields • Quality control • Visualization and analysis tools that work with the output format
Schematic for PIRCS Diagnostics and Output Application Program: • We supply application code, complete with time-stepping, filename generation, output module, and library routine calls • User supplies module to read the model’s history files, returning the model fields required by the PIRCS application
Acknowledgments • Primary Funding: Electric Power Research Institute (EPRI) • Guidance/Support: Andrew Staniforth, Eugenia Kalnay, Filippo Giorgi, Roger Pielke, AMIP group • Special Thanks: Participating Modelers Asian RMIP Workshop (June 2000)