Application of Fusing Analog Method in Short-term Heavy Precipitation Forecast in Southeastern Gansu
Based on similar forecast method with step-by-step filter and Self-organizing map(SOM)neural net-work,a fusing analog forecast method is proposed.Using ECMWF model forecast products,ERA5 reanalysis data and station data,this method is used to carry out a 72-hour forecast of heavy precipitation in southeastern Gansu from 2021 to 2022,and the forecast effect is tested.The results show that the TS score of the fusing ana-log forecast method ranges from 4.5％to 9.1％,demonstrating a certain advantage compared to the forecast re-sults of the ECMWF model.As the forecast lead time increases,the TS score of the heavy precipitation forecast shows a decreasing trend,with relatively higher TS scores forecasted at 08:00.Compared with the similar fore-cast method with step-by-step filter alone,the accuracy of the fusing analog forecast method is improved,and it can alleviate the problem of high false alarm rate to a certain extent.Specifically,the TS scores forecasted at 08:00 and 20:00 are increased by 1.31％and 0.63％,while the FAR is decreased by 2.39％and 1.25％.
heavy precipitationshort-term forecastsimilar forecastsimilar forecast method with step-by-step filterself-organizing map(SOM)
万方数据
维普
