Evaluation of the Dynamical–Statistical Downscaling Model for Extended Range Precipitation Forecasts in China

In order to focus on pentad-scale precipitation forecasts, we investigated the coupling relationship between 500 hPa geopotential height (Z500) anomalies and using China Meteorological Administration Global Land Surface ReAnalysis Interim (CRA40/Land) gridded dataset from 1999 2018 National Centers for Environmental Prediction 1 reanalysis Z500. We obtained a dynamical–statistical downscaling model (DSDM) pentad scale used daily Z500 forecast product sub-seasonal seasonal forecasts (15–60 days) of FGOALS-f2 as predictor. Our results showed that prediction is key bridging current deficiencies in forecasts. Compared with model, DSDM had higher skill at lead times longer than four pentads throughout year two summer months. excellent predictability less three (15 days), so proposed could not perform better this period. However, greater pentads, scores (such anomaly correlation coefficient (ACC), temporal (TCC) mean square score (MSSS)) whole were those model. With rate increase ranging 76% 520%, ACC basically 0.04 after time five whereas 0.04. An analysis Zhengzhou “720” super heavy rainstorm event also distribution extreme event.