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...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 precipita- tion tendency accurately, which was closer to the observation than in the control forecast. For heavy rainfall, the pre- cipitation 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 pre- cipitation for heavy rainfall. Preliminary results demonstrated that convection-allowing ensemble forecast could im- prove 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.展开更多
基金Supported by the Natural Science Foundation of Nanjing Joint Center of Atmospheric Research(NJCAR2016MS02)National Natural Science Foundation of China(41205073,41275012,and 41275099)
文摘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 precipita- tion tendency accurately, which was closer to the observation than in the control forecast. For heavy rainfall, the pre- cipitation 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 pre- cipitation for heavy rainfall. Preliminary results demonstrated that convection-allowing ensemble forecast could im- prove 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.
