The sensitivity of the Extreme Precipitation Forecast Index on climatological cumulative probabilitydistribution

The history of the T213 Ensemble Prediction System (EPS) is short, and the sample of the model's climatological cumulative probabilitydistribution is small in establishing a mathematical model of Extreme Precipitation Forecast Index (EPFI). For minimizing this problem,we select the middle and lower reaches of the Yangtze River as the study area where the climatological backgrounds as well as the geographicaland topographic features are similar. Additionally, we extend the samples of the T213 EPS precipitation forecast and improve model'sclimatological cumulative distribution function by using the extended time series and the range of spatial coverge. A new EPFI is establishedand applied to forecast experiments of several extreme rainfall events in Yangtze River reaches from June 10 to 20 in 2011. The resultsshow that the above method, i.e., time series and spatial range are extended to increase the number of samples of T213 ensemble forecasts,have generated more representative model climatological cumulative distribution function than a single grid method, and it can improve EPFIidentify skills and forecast the extreme precipitation events in the Yangtze River reaches by 8 days in advance.