The model ability to predict summer precipitation at seasonal time scale in China is evaluated by using the re-forecast data during 1996-2015 from the BCC second-generation short-range climate forecast system with the lead time of 1~3 months, and the interannual differences of model's prediction ability are analyzed. The possible causes of model prediction errors are also discussed. The results show that the model has a certain seasonal forecasting ability for summer precipitation in China, it has high seasonal forecasting skill over southwest China, the middle and lower reaches of the Yangtze River, west of Huanghuai Plain, North China and Northern Tibet Plateau. Generally speaking, the model has good prediction ability for precipitation anomalies in China. The anomaly sign consistency is high in middle and lower reaches of the Yangtze river, Huanghuai area, South China, Northwest China and northern part of North China. However, there are also some deviations, which are mainly manifested in the less precipitation in East China predicted by the model, the limited forecasting skills for summer precipitation anomalies and the large differences of prediction ability in different years. The predicted high temperature areas in western Pacific and Indian Ocean SST is limited, the intensity of the subtropical high and water vapor convergence is significantly weak, which lead to the less precipitation in East China. Judging from the interannual differences in model's prediction ability, when the precipitation in South China is more than normal years, and the precipitation in the middle and lower reaches of the Yangtze River and North China is less, the model has higher prediction skills. On the contrary, the forecast skill is lower. The analyses of the relationship between summer precipitation in East China and sea surface temperature show that the Northwest Pacific Ocean, the tropical western Pacific and the North Indian Ocean are three key areas for summer precipitation prediction in East China and the SST biases in the Northwest Pacific Ocean have important effects on the model's forecasting skills. The mutual configuration of SST, geopotential height, wind field and water vapor flux divergence field leads to the distribution and intensity difference of summer precipitation in East China, but the model cannot reasonably capture the relationship between them, thus reduce the model's ability to predict summer precipitation in East China. Therefore, accurate prediction on the relationship between external forcing factors and precipitation anomalies is important for the improvement of the precipitation forecasting skills in China.
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