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Water Utility Climate Alliance White Paper Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change Table 3.4. Climate downscaling groups at government-supported facilities with longstanding financial and infrastructure support (cont.) RCM/method Institution Web site Contact Climate MM5, Climate WRF Various statistical and stochastic methods Illinois State Water Survey, Center for Atmospheric Science, Climate, Air Quality, and Impact Modeling System NCAR, Research Applications Laboratory, Integrated Science Program http://www.isws.illinois.edu/atmos/ modeling/caqims/ http://www.isp.ucar.edu/ Dr. Xin-Zhong Liang Illinois State Water Survey 2204 Griffith Dr. Champaign, IL 61820-7495 217-244-6864 xliang@illinois.edu Dr. Peter Backlund Director, NCAR/ISP PO Box 3000 Boulder, CO 80307-3000 303-497-1103 backlund@ucar.edu C-FDDA = Climate-Four Dimensional Data Assimilation; MM5 = Penn State-National Center for Atmospheric Research Mesoscale Model version 5; NRCM = Nested Regional Climate Model; WRF = Weather Research and Forecasting. Table 3.5. Institutions that have generated downscaled climate simulations Technique, name Institution Contact RCM: RSM-NCEP NOAA National Centers for Environmental Prediction Hann-Ming Henry Juang Henry.Juang@noaa.gov RCM: RSM-ECPC UC San Diego, Scripps Oceanographic Institute, Experimental Climate Prediction Center Masao Kanamitsu mkanamitsu@ucsd.edu RCM: WRF-ARW, MM5 Pacific Northwest National Laboratory Ruby Leung Ruby.Leung@pnl.gov RCM: WRF-NMM Iowa State University Chris Anderson cjames@iastate.edu RCM: MM5 Iowa State University Ray Arritt rwarritt@bruce.agron.iastate.edu RCM: Climate WRF Illinois State Water Survey Xin-Zhong Liang xliang@illinois.edu RCM: ETA-NCEP NOAA National Centers for Environmental Prediction Rongqian Yang Rongqian.yang@noaa.gov RCM: ETA-SIB UCLA Yongkang Xue yxue@geog.ucla.edu RCM: RAMS Colorado State University Lixin Lu lixin@atmos.colostate.edu RCM: RegCM3 UC Santa Cruz Mark Snyder msnyder@pmc.ucsc.edu Page 3-31
Water Utility Climate Alliance White Paper Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change Table 3.5. Institutions that have generated downscaled climate simulations (cont.) Technique, name Institution Contact RCM: RAMS, WRF University of Arizona Christopher Castro castro@atmo.arizona.edu SD: LLNL-Reclamation-Lawrence Livermore National Laboratory, Bureau Edwin Maurer SCU WCRP CMIP3 of Reclamation, Santa Clara University EMaurer@scu.edu SD: U. Washington University of Washington Many investigators Climate Impacts Group SD: Indiana University Precipitation Climates Indiana University Sara Pryor spryor@indiana.edu ETA = ETA Coordinate Mesoscale Model; MM5 = Penn State-National Center for Atmospheric Research Mesoscale Model version 5; RCM = regional climate model; RAMS = Regional Atmospheric Modeling System; RegCM3 = Regional Climate Model version 3; RSM = Regional Spectral Model; SD = Statistical Downscaling; WRF = Weather Research and Forecast Model. Indeed, the North American Regional Climate Change Assessment Project (NARCCAP, http://narccap.ucar.edu/) represents the most ambitious attempt to quantify uncertainty in regional climate projections. It will contain results from six RCMs that each are provided data from two of four participating GCM institutions that each submitted a single GCM projection from a single emissions scenario. 3.2.5 What framework is applied for analyzing errors in downscaling techniques? A framework that allows for analysis of errors in statistical and dynamical downscaling techniques is described below (it is assumed that all analyses are performed on identical time scales, e.g., daily, monthly, or annual). 1. Baseline climate simulation. The downscaling technique is calibrated on the target region for the target variables by using observations or a proxy for observations from the recent past as input. The accuracy of the calibration is checked by simulation of an independent period. Evaluation of the baseline climate simulation provides a measure of the error introduced by the downscaling technique. 2. Alternative baseline climate simulation. The downscaling technique is applied without recalibration to another region or another period within the same region in which the climate conditions are quite different and may have characteristics expected under climate change within the target region. The differences between this simulation and the baseline climate simulation provide a measure of how robust the downscaling technique is to changing climate conditions. Page 3-32
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