%0 Journal Article %A YE Mao %A WU Zheng %A GAO Song %A CHEN Lianglü %A YOU Ting %T Analysis on precipitation forecast performance of convective-scale ensemble system in Sichuan-Chongqing region %D 2023 %R 10.11755/j.issn.1006-7639(2023)-01-0152 %J Journal of Arid Meteorology %P 152-163 %V 41 %N 1 %X

In order to learn more about the performance of convective-scale ensemble forecast system for precipitation prediction in the Sichuan-Chongqing region, the control forecast (CNTL), the ensemble mean (MEAN) and the probability-matched ensemble mean (PM) of convective-scale ensemble prediction system are comprehensively analyzed based on daily precipitation data collected at 7 213 stations in the Sichuan-Chongqing region in warm season (from May to September) from 2020 to 2021, and differences between rainfall forecasts starting at 08:00 and 20:00 are compared. Results are as follows: (1) The forecast performance of PM and MEAN is better than that of CNTL. MEAN is skillful at forecasting moderate rain and heavy rain, and PM has obvious advantages for large rainfall. (2) Positive forecast deviations of light rainfall frequency are obvious in the whole research region, while for moderate rain and above, positive deviations are concentrated in high-altitude mountains such as the Daba Mountain, the Huaying Mountain and the Wuling Mountain, and negative deviations are mainly located in the Sichuan Basin and hilly areas. Positive (negative) deviations of light rain and moderate rain (heavy rain and rainstorm) predicted by MEAN are more obvious than those predicted by CNTL and PM. (3) The critical success index (CSI) and probability of detection (POD) scores with lead time of 36 h for the forecasts starting at 08:00 are higher than those with lead time of 48 h for the forecasts starting at 20:00, but the overestimation of rainfall frequency starting at 08:00 is more obvious in high-altitude mountains. (4) Compared with CNTL, PM and MEAN are better for the rainfall area of the heavy rain process from September 4 to 7, 2021 in the Sichuan Basin, which is related to the fact that ensemble forecast can better capture the position and morphology of the weather system.

%U http://www.ghqx.org.cn/EN/10.11755/j.issn.1006-7639(2023)-01-0152