Xin-Zhong Liang1,2* and Chao Sun1,2
1Department of Atmospheric & Oceanic Science, University of Maryland
2Earth System Science Interdisciplinary Center, University of Maryland
The CWRF (Climate extension of the Weather Research and Forecasting model) incorporates a comprehensive ensemble of multiple alternate representations for major physical processes, including interactions among land–atmosphere–ocean, convection–microphysics-precipitation and cloud–aerosol–radiation. Among the select 25 physics configurations, only those coupled with an ensemble cumulus parameterization can capture the extreme precipitation features (95th percentile, rainy days, consecutive dry days) over the United States, especially in summer. This includes both climatology and linear trends during 1980-2015, with the downscaling CWRF performance even more faithfully than the driving ECMWF-Interim reanalysis without relying on assimilated surface data. This study will present a process understanding of how CWRF/ ensemble cumulus parameterization can achieve such skill enhancement, including its roles on atmosphere-land-hydrology coupling, convective versus resolved precipitation partitioning, and low-level jet moisture transport.
For a presentation at the AMS 98th Annual Meeting: the 32nd Conference on Hydrology, 7–11 January 2018, Austin, Texas.
* Corresponding author address: Dr. Xin-Zhong Liang, Earth System Science Interdisciplinary Center, University of Maryland, 5825 University Research Court, Suite 4001, College Park, MD 20740. E-mail: email@example.com