Probability Prediction of Monthly Precipitation over Huaihe River Basin in China in Summer Based on SpatioTemporal Statistical Downscaling Method
Skillful precipitation prediction is useful in managing water resources and preventing droughts and floods for the Huaihe River Basin. A hybrid spatiotemporal statistical downscaling model based on the ensemble reforecast dataset (1991-2014) of the seasonal climate model (CSM1.1m) was developed to predict the summer monthly precipitation over the basin ahead of 1-3 months, i.e., starting from March, April and May. Crossvalidation tests indicate that compared with CSM1.1m, the established statistical downscaling model is more skillful for the precipitation forecasted in March, April and May for four ensemble schemes. Independent sample tests present that the statistical downscaling model can reduce prediction error, especially for precipitation in June and August forecasted in March and May. These results suggest that it is possible to use the statistical downscaling method for precipitation probability forecasting and further hydrological forecasting in summer over Huaihe River Basin.