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The North American Regional Climate Change Assessment Program (NARCCAP) Linda O. Mearns National Center for Atmospheric Research SAMSI Climate Change Workshop Research Triangle Park, NC February 18, 2010 Global Climate Models Regional Climate Models What high resolution is really good for • In certain specific contexts, provides insights on realistic climate response to high resolution forcing (e.g. mountains, complex coast lines) • For coupling climate models to other models that require high resolution (e.g. air quality models – for air pollution studies) Advantages of higher resolution North America at typical global climate model resolution Hadley Centre AOGCM (HadCM3), 2.5˚ (lat) x 3.75˚ (lon), ~ 280 km North America at 50 km grid spacing Putting Spatial Resolution in the Context of Other Uncertainties • Must consider the other major uncertainties regarding future climate in addition to the issue of spatial scale – what is the relative importance of uncertainty due to spatial scale? • These include: – Specifying alternative future emissions of ghgs and aerosols – Modeling the global climate response to the forcings (i.e., differences among AOGCMs) Regional Modeling Strategy Nested regional modeling technique • Global model provides: – initial conditions – soil moisture, sea surface temperatures, sea ice – lateral meteorological conditions (temperature, pressure, humidity) every 6-8 hours. – Large scale response to forcing (100s kms) • Regional model provides finer scale (10s km) response The North American Regional Climate Change Assessment Program (NARCCAP) Initiated in 2006, it is an international program that will serve the climate scenario needs of the United States, Canada, and northern Mexico. •Exploration of multiple uncertainties in regional model and global climate model regional projections •Development of multiple high resolution regional climate scenarios for use in impacts assessments. •Further evaluation of regional model performance over North America •Exploration of some remaining uncertainties in regional climate modeling (e.g., importance of compatibility of physics in nesting and nested models) •Program has been funded by NOAA-OGP, NSF, DOE, USEPA-ORD – 4-year program www.narccap.ucar.edu NARCCAP - Team Linda O. Mearns, NCAR Ray Arritt, Iowa State; Dave Bader, LLNL and Oakridge National Lab; Melissa Bukovsky, NCAR; Richard Jones, Wilfran Moufouma-Okia, UK Hadley Centre; Sébastien Biner, Daniel Caya, Ouranos (Quebec); Phil Duffy, Climate Central; Dave Flory, Iowa State; William Gutowski, Iowa State; Isaac Held, GFDL; Bill Kuo, NCAR; René Laprise, UQAM; Ruby Leung, Yun Qian, PNNL; Larry McDaniel, Seth McGinnis, Don Middleton, NCAR; Ana Nunes, Scripps; Doug Nychka, NCAR, John Roads*, Scripps; Steve Sain, NCAR; Lisa Sloan, Mark Snyder, UC Santa Cruz, Gene Takle, Iowa State * Deceased June 2008 NARCCAP Domain Organization of Program • Phase I: 25-year RCM simulations using NCEP-Reanalysis boundary conditions (1979—2004) • Phase II: Climate Change Simulations – Phase IIa: RCM runs (50 km res.) nested in AOGCMs current and future – Phase IIb: Time-slice experiments at 50 km res. (GFDL and NCAR CAM3). For comparison with RCM runs. • Quantification of uncertainty at regional scales – probabilistic approaches • Scenario formation and provision to impacts community led by NCAR. • Opportunity for double nesting (over specific regions) to include participation of other RCM groups (e.g., for NOAA OGP RISAs, CEC, New York Climate and Health Project, U. Nebraska). Phase I • All 6 RCMs have completed the reanalysis-driven runs (RegCM3, WRF, CRCM, ECPC RSM, MM5, HadRM3) • Results are shown here for 1980-2004 from six RCMs • Configuration: – common North America domain (some differences due to horizontal coordinates) – horizontal grid spacing 50 km – boundary data from NCEP/DOE Reanalysis 2 – boundaries, SST and sea ice updated every 6 hours Regions Analyzed Boreal forest Pacific coast Maritimes Great Lakes Upper Mississippi River California coast Deep South Coastal California • Mediterranean climate: wet winters and very dry summers (Koeppen types Csa, Csb). – More Mediterranean than the Mediterranean Sea region. • ENSO can have strong effects on interannual variability of precipitation. R. Arritt Monthly time series of precipitation in coastal California 15 mm/day 12 9 6 1982-83 El Nino RCM3 ECPC WRFP Observed (GPCC) Observed (CRUT) 1997-98 MM5I CRCM El Nino HRM3 Observed (UDEL) Ensemble multi-year drought 3 0 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 small spread, high skill Correlation with Observed Precipitation - Coastal California Model Correlation HadRM3 0.857 RegCM3 0.916 MM5 0.925 RSM 0.945 CRCM 0.946 WRF 0.918 Ensemble 0.947 All models have high correlations with observed monthly time series of precipitation. Ensemble mean has a higher correlation than any model Deep South • Humid mid-latitude climate with substantial precipitation year around (Koeppen type Cfa). • Past studies have found problems with RCM simulations of cool-season precipitation in this region. Monthly Time Series - Deep South 15 mm/day 12 RCM3 CRCM Observed (GPCC) Ensemble MM5I WRFP Observed (UDEL) ECPC HRM3 Observed (CRUT) mm/day 9 Correlation 9 HadRM3 0.489 6 RegCM3 0.231 3 MM5 0.343 0 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 RSM 0.649 CRCM 0.649 WRF 0.513 Ensemble 0.640 Monthly mean precipitation for Deep South 12 Model Ensemble (black curve) Observed (GPCC) Observed (UDEL) Observed (CRUT) Ensemble 6 3 0 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Two models (RSM and CRCM) perform much better. These models inform the domain interior about the large scale. Monthly Time Series - Deep South 15 mm/day 12 RCM3 CRCM Observed (GPCC) Ensemble MM5I WRFP Observed (UDEL) ECPC HRM3 Observed (CRUT) mm/day 9 Correlation 9 HadRM3 0.489 6 RegCM3 0.231 3 MM5 0.343 0 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 RSM 0.649 CRCM 0.649 WRF 0.513 Ensemble 0.640 RSM+CRCM 0.727 Monthly mean precipitation for Deep South 12 Model Ensemble (black curve) Observed (GPCC) Observed (UDEL) Observed (CRUT) Ensemble 6 3 0 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 A “mini ensemble” of RSM and CRCM performs best in this region. NARCCAP PLAN – Phase II A2 Emissions Scenario GFDL Time slice 50 km GFDL 1971-2000 current CGCM3 HADCM3 Provide boundary conditions CCSM CAM3 Time slice 50km 2041-2070 future MM5 RegCM3 CRCM HADRM3 RSM WRF Iowa State/ PNNL UC Santa Cruz ICTP Quebec, Ouranos Hadley Centre Scripps NCAR/ PNNL GCM-RCM Matrix AOGCMS GFDL RCMs MM5 RegCM CRCM HADRM RSM WRF *CAM3 *GFDL X1** CGCM3 HADCM3 CCSM X X1 X** X1** X X X1** X1 X X X1 X X** 1 = chosen first GCM *= time slice experiments Red = run completed ** = data loaded Phase II (Climate Change) Results Change in Winter Temperature UK Models Change in Summer Temperature UK Models Uncertainty across two RCMs nested in same GCM for % Change in Winter Precipitation Regional Model 1 Global Model Regional Model 2 Effect of two different GCMs driving one RCM – % change in winter precipitation GCMs CGCM3 RCM RegCM3 GFDL Global Time Slice / RCM Comparison at same resolution (50km) A2 Emissions Scenario GFDL NCAR CCSM AOGCM Six RCMS 50 km GFDL AGCM Time slice 50 km compare compare CAM3 Time slice 50km RegCM3 in GFDL % Change Precip - Winter Quantification of Uncertainty • The four GCM simulations already ‘situated’ probabilistically based on earlier work (Tebaldi et al., 2004, 2005) • RCM results nested in particular GCM would be represented by a probabilistic model (derived assuming probabilistic context of GCM simulation) • Use of performance metrics to differentially weight the various model results – will use different metrics – including process level expert judgment - determine sensitivity of final pdfs to various methods NARCCAP Project Timeline Phase IIa Current Climate1 Future Current and Climate 1 Future 2 Project Start Phase 1 1/06 9/07 AOGCM Boundaries available 12/07 9/08 Archiving Procedures - Implementation Phase IIb Time slices 8/09 6/10 The NARCCAP User Community Three user groups: • Further dynamical or statistical downscaling • Regional analysis of NARCCAP results • Use results as scenarios for impacts and adaptation studies www.narccap.ucar.edu To sign up as user, go to web site – contact Seth McGinnis Over 200 hundred users registered End