The North American Regional Climate Change Assessment Program (NARCCAP) Linda O. Mearns

1. 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

2. Global Climate Models Regional Climate Models

3. 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)

4. 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

5. 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)

6. 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

7. 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

8. NARCCAP - Team Linda O. Mearns, NCAR Ray Arritt, Iowa State; Dave Bader, LLNL and Oakridge National Lab; Melissa Bukovsky, NCAR; Richard Jones, WilfranMoufouma-Okia, UKHadley Centre;SébastienBiner, 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, YunQian, 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

9. NARCCAP Domain

10. 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).

11. 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

16. Regions Analyzed Boreal forest Maritimes Great Lakes Pacific coast Upper Mississippi River Deep South California coast

17. 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

18. Monthly time series of precipitation in coastal California 1997-98 El Nino 1982-83 El Nino multi-year drought small spread, high skill

19. Correlation with Observed Precipitation - Coastal California All models have high correlations with observed monthly time series of precipitation. Ensemble mean has a higher correlation than any model

20. 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.

21. Monthly Time Series - Deep South Ensemble (black curve) Two models (RSM and CRCM) perform much better. These models inform the domain interior about the large scale.

22. Monthly Time Series - Deep South Ensemble (black curve) A “mini ensemble” of RSM and CRCM performs best in this region.

23. NARCCAP PLAN – Phase II A2 Emissions Scenario GFDL CGCM3 HADCM3 CCSM CAM3 Time slice 50km GFDL Time slice 50 km Provide boundary conditions 2041-2070 future 1971-2000 current CRCM Quebec, Ouranos RegCM3 UC Santa Cruz ICTP HADRM3 Hadley Centre MM5 Iowa State/ PNNL RSM Scripps WRF NCAR/ PNNL

24. GCM-RCM Matrix AOGCMS RCMs

25. Phase II (Climate Change) Results

26. Change in Winter TemperatureUK Models

27. Change in Summer TemperatureUK Models

28. Uncertainty across two RCMs nested in same GCM for % Change in Winter Precipitation Regional Model 2 Regional Model 1 Global Model

29. Effect of two different GCMs driving one RCM – % change in winter precipitation GCMs GFDL CGCM3 RCM RegCM3

30. Global Time Slice / RCM Comparison at same resolution (50km) A2 Emissions Scenario GFDL AOGCM NCAR CCSM Six RCMS 50 km GFDL AGCM Time slice 50 km CAM3 Time slice 50km compare compare

32. RegCM3 in GFDL% Change Precip - Winter

33. 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

34. NARCCAP Project Timeline Phase IIa Current Climate1 Future Climate 1 Current and Future 2 Project Start AOGCM Boundaries available Phase 1 12/07 8/09 9/07 1/06 9/08 6/10 Archiving Procedures - Implementation Phase IIb Time slices

35. 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 • , • mcginnis@ucar.edu Over 200 hundred users registered

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