Hydrology and Earth System Sciences www.hydrol-earth-syst-sci.net 1027-5606 1607-7938 12 2 2008 10.5194/hess-12-551-2008 http://www.hydrol-earth-syst-sci.net/12/551/2008/ http://www.hydrol-earth-syst-sci.net/12/551/2008/hess-12-551-2008.html http://www.hydrol-earth-syst-sci.net/12/551/2008/hess-12-551-2008.pdf 551 563 2008-03-13 Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods E. P. Maurer emaurer@engr.scu.edu H. G. Hidalgo Civil Engineering Department, Santa Clara University, Santa Clara, CA, USA Scripps Institution of Oceanography, Div. of Climate Atmospheric Sciences & Physical Oceanography, La Jolla, CA, USA Downscaling of climate model data is essential to local and regional impact analysis. We compare two methods of statistical downscaling to produce continuous, gridded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km² per grid cell) resolution over the western U.S. We use NCEP/NCAR Reanalysis data from 1950–1999 as a surrogate General Circulation Model (GCM). The two methods included are constructed analogues (CA) and a bias correction and spatial downscaling (BCSD), both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA downscales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to generate daily values. The methods produce generally comparable skill in producing downscaled, gridded fields of precipitation and temperatures at a monthly and seasonal level. 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