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A convection-allowing ensemble forecast based on the breeding growth mode and associated optimization of precipitation forecast
Authors:Xiang Li  Hongrang He  Chaohui Chen  Ziqing Miao  Shigang Bai
Institution:1.College of Meteorology and Oceanography,PLA University of Science and Technology,Nanjing,China;2.Nanjing Joint Center of Atmospheric Research,Nanjing,China;3.PLA Troop 96219,Kunming,China;4.PLA Troop 96319,Puning,China
Abstract:A convection-allowing ensemble forecast experiment on a squall line was conducted based on the breeding growth mode (BGM). Meanwhile, the probability matched mean (PMM) and neighborhood ensemble probability (NEP) methods were used to optimize the associated precipitation forecast. The ensemble forecast predicted the precipitation tendency accurately, which was closer to the observation than in the control forecast. For heavy rainfall, the precipitation center produced by the ensemble forecast was also better. The Fractions Skill Score (FSS) results indicated that the ensemble mean was skillful in light rainfall, while the PMM produced better probability distribution of precipitation for heavy rainfall. Preliminary results demonstrated that convection-allowing ensemble forecast could improve precipitation forecast skill through providing valuable probability forecasts. It is necessary to employ new methods, such as the PMM and NEP, to generate precipitation probability forecasts. Nonetheless, the lack of spread and the overprediction of precipitation by the ensemble members are still problems that need to be solved.
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