TJ7.3 CWRF Application for U.S. Drought Forecasts

Monday, 7 January 2013: 4:30 PM
Ballroom F (Austin Convention Center)
Xin-Zhong Liang, University of Maryland, College Park, MD; and L. Chen and S. Su

The CWRF is a Climate extension of the Weather Research and Forecasting model with enhanced physics representations, including interactions among land–atmosphere–ocean, convection–microphysics-precipitation and cloud–aerosol–radiation. In particular, it incorporates a comprehensive Conjunctive Surface-Subsurface Process (CSSP) module to predict mesoscale terrestrial hydrology variations. Standalone simulations as driven by observational data reveal clear advantage of CSSP over some other existing land surface models (LSMs) in consistently representing surface fluxes, runoff, and soil moisture. The CWRF has been shown to produce more realistic surface radiation and terrestrial hydrology than other regional climate models, and significant skill enhancement for precipitation over the NCEP operational Climate Forecast System (CFS) winter seasonal forecast and the ECMWF/Hamburg (ECHAM) retrospective simulation throughout the year. These results suggest that CWRF has capability to provide more credible prediction of hydroclimate conditions on the regional and seasonal scales. This study will exploit the potential for using the high-resolution CWRF coupled with CSSP, where both realistic initial-condition specification and full climate-hydrology interaction during the forecast period are incorporated. The meteorological, agricultural, and hydrological droughts as classified respectively by precipitation, soil moisture and runoff, will be examined. We will demonstrate the significant advantage of CWRF for the regional drought prediction, especially when using the optimized physics ensemble driven by multiple large-scale forcing predictions.
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