PIRCS Project to Intercompare Regional Climate Simulations: Contributions to Transferability Ninth Session GEWEX Hydrometeorology Panel Lüneburg, Germany September Gene Takle Bill Gutowski, Ray Arritt

Outline What is PIRCS Lessons learned relating to hydrological cycle PIRCS 1c and beyond Contributions to transferability and GHP objectives

To provide a common framework for evaluating strengths and weaknesses of regional climate models and their component procedures through systematic, comparative simulations PIRCS Mission

Domain PIRCS Experiments 1a and 1b GCM grid: red pointsRCM grid: green, blue points

Domain PIRCS Experiments 1a and 1b GCM grid: red pointsRCM grid: green, blue points Upper Miss.

PIRCS Experiment 1 Experiment 1a 1988 drought Experiment 1b 1993 flood Heat Wave Jet Stream Cool Warm & Moist Southerly Flow Flood Jet Stream Cool & Damp Weak & Dry Southerly Flow Heat Wave

 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 Participating Groups

 500 hPa Heights ( ) <== Reanalysis Mean of 7 models ==>

500 hPa Heights: Root Mean Square Difference from Reanalysis PIRCS Expt 1a (1988)

Daily Precipitation History PIRCS Expt 1a (1988 Drought)

Lessons Learned - 1a Models generally capture the large-scale fields for extreme events Models generally capture the timing and spatial location of precipitation events far from boundaries and long after initialization for synoptically driven precipitation Models show wide differences(but realistic behavior) during periods of strong mesoscale forcing From these experiences, we assert that simulated climate is a sequence of actual climate events

500 hPa Heights: Root Mean Square Difference from Reanalysis PIRCS Expt1b (1993)

Ensemble of Cumulative Precipitation for PIRCS 1b Precipitation (mm) Upper Mississippi River Basin

Daily Cycle of Water Vapor in Upper Mississippi River Basin Nocturnal water vapor flux convergence (not in NNR) Nocturnal precipitation maximum (not in NNR) Temporal separation of evap max and precip max Nocturnal precipitation max created by mesoscale convective systems Region lacks major orographic forcing (e.g., no mountains, no coasts, no major lakes) to spatially constrain precip events

Daily Cycle of Water Vapor in Upper Mississippi River Basin Nocturnal water vapor flux convergence (not in NNR) Nocturnal precipitation maximum (not in NNR) Temporal separation of evap max and precip max Nocturnal precipitation max created by mesoscale convective systems Region lacks major orographic forcing (e.g., no mountains, no coasts, no major lakes) to spatially constrain precip events We are a boring place to visit…

Daily Cycle of Water Vapor in Upper Mississippi River Basin Nocturnal water vapor flux convergence (not in NNR) Nocturnal precipitation maximum (not in NNR) Temporal separation of evap max and precip max Nocturnal precipitation max created by mesoscale convective systems Region lacks major orographic forcing (e.g., no mountains, no coasts, no major lakes) to spatially constrain precip events We are a boring place to visit unless you bring your RCM!

Lessons Learned - 1b As much difference among models using NNR bc as between models using NNR and ER bc. But this may not be the case where bc are in data- sparse regions. Extended period of saturated soils allowed examination of evaporation schemes (independent of soil moisture values). Diurnal separation of C and P from E. Lack of precip south of frontal boundary shows failure to simulate MCCs

Lessons Learned - 2 All models get P-E > 0, as observed, even though this is not the normal climatological occurrence for this region. Convective (vs. stable precip): %. Three models using K-F scheme differ widely in conv. fraction. Conv fraction not correlated with total precip. E (models) = 3.9 mm/d; E (clim) ~ 4 mm/d; 3 models markedly different: model deficiencies exposed. Water recycling ratio similar in 10 of 13 and within the expected range. Importance of vertical and horizontal resolution of and time evolution of the LLJ Common model faults and relation to parentage

PIRCS 1c and Beyond present Domain same as 1a and 1b with expansion to south and west Participants sought See PIRCS homepage: Revisit PIRCS 1b? PIRCS 2, South America??

What have been the benefits of transferability? Application to different regions severely tests different model components Convection, interaction of convection with PBL and turbulence representation of the LLJ Linkage of convective activity to convective cloudiness to test surface energy budget Colin Jones, Rossby Center

u, v, w Constraining boundary T,  w Regional models, with boundaries constrained by observations, allow for more realistic parameterizations of model physics for use in global models Concept suggested by Colin Jones, sketch by EST RCM is a bridge between 1-D and GCMs for parameterizations

PIRCS Publications PIRCS 1a Takle, E. S., W. J. Gutowski, R. A. Arritt, Z. Pan, C. J. Anderson, R. R. da Silva, D. Caya, S.-C. Chen, J. H. Christensen, S.-Y. Hong, H.-M. H. Juang, J. Katzfey, W. M. Lapenta, R. Laprise, P. Lopez, J. McGregor and J. O. Roads, 1999: Project to Intercompare Regional Climate Simulations (PIRCS): Description and initial results. J. Geophys. Res., 104, 19,443-19,461. PIRCS 1b Anderson, C. J., R. W. Arritt, E. S. Takle, Z. Pan, W. J. Gutowski, Jr., R. da Silva, D. Caya, J. H. Christiansen, D. Luthi, M. A. Gaertner, C. Gallardo, F. Giorgi, S.-Y. Hong, Colin Jones, H.-M. J. Juang, Jack J. Katzfey, W. M. Lapenta, R. Laprise, J. W. Larson, G. E. Liston, J. L. McGregor, R. A. Pielke, Sr., J. O. Roads, and J. A. Taylor, 2002: Hydrologic processes in regional climate model simulations of the central United States flood of June-July J. Hydrometeor., 4,

15 Conference Presentations American Meteorological Society meetings International Association of Meteorological and Atmospheric Sciences European Geophysical Society American Geophysical Union

Invited Presentations Working Group on Numerical Experimentation, WCRP Workshop on Climate Modeling Clivar Meeting Regional Climate Model Intercomparsion Project for China Arctic Model Intercomparison Project Workshop on Regional Climate Prediction and Downscaling Techniques for South America

Contributions of RCM Intercomparisons to GHP Objectives Offer opportunities for better understanding of how the water and energy cycles contribute to climate feedbacks (up-scaling issues) Suggest specific areas and strategies for improving parameterizations PIRCS represented in the IPCC TAR and offers opportunity to interact with the broader WCRP community on predictability

PIRCS Program Office Project Leaders: Ray Arritt Bill Gutowski Gene Takle Project Scientists: Chris Anderson Dave Flory Computations and Communications Consultant: Daryl Herzmann Scientific Consultant: Zaitao Pan