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 50 km grid spacing North America at typical global climate model resolution Hadley Centre AOGCM (HadCM3), 2.5˚ (lat) x 3.75˚ (lon), ~ 280 km

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) 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 Initiated in 2006, it is an international program that will serve the climate scenario needs of the United States, Canada, and northern Mexico.

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 ( ) 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 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 California coast Deep South Great Lakes Maritimes Upper Mississippi River

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

El Nino El Nino multi-year drought Monthly time series of precipitation in coastal California small spread, high skill

Correlation with Observed Precipitation - Coastal California Model Correlation HadRM RegCM MM RSM0.945 CRCM0.946 WRF0.918 Ensemble Ensemble mean has a higher correlation than any model All models have high correlations with observed monthly time series of precipitation.

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 Model Correlation HadRM RegCM MM RSM0.649 CRCM0.649 WRF0.513 Ensemble0.640 Two models (RSM and CRCM) perform much better. These models inform the domain interior about the large scale. Ensemble (black curve)

Monthly Time Series - Deep South Model Correlation HadRM RegCM MM RSM0.649 CRCM0.649 WRF0.513 Ensemble0.640 RSM+CRCM0.727 A mini ensemble of RSM and CRCM performs best in this region. Ensemble (black curve)

A2 Emissions Scenario GFDLCCSMHADCM3CGCM current future Provide boundary conditions MM5 Iowa State/ PNNL RegCM3 UC Santa Cruz ICTP CRCM Quebec, Ouranos HADRM3 Hadley Centre RSM Scripps WRF NCAR/ PNNL NARCCAP PLAN – Phase II CAM3 Time slice 50km GFDL Time slice 50 km

GCM-RCM Matrix GFDLCGCM3HADCM3CCSM MM5 XX1 RegCM X1**X** CRCM X1** X HADRM XX1** RSM X1 X WRF XX1 *CAM3 X *GFDL X** 1 = chosen first GCM *= time slice experiments Red = run completed ** = data loaded AOGCMS RCMs

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 Global ModelRegional Model 1 Regional Model 2

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

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

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

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 To sign up as user, go to web site – contact Seth McGinnis, Over 200 hundred users registered

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