中文摘要：

一条动态统计的 processing 以后途径在夏天期间在中国被用于季节的降水预报。数据是整体平均数在从在从 1969 ～ 2001 的加拿大的历史的预报工程(HFP2 ) 的第二个阶段的四个大气的一般发行量模型(GCM ) 的夏天(6 月 8 月) 的季节的预报。这条动态统计的途径基于在预报和观察的海表面温度(SST ) 预报校准降水的 500 geopotential 高度(Z500 ) 之间的关系被设计。结果证明 processing 以后能在中国为许多区域改进夏天降水预报。进一步的检查证明这条 processing 以后途径在减少错误的模型依赖者部分是很有效的，它与 GCM 被联系。在预报改进后面的可能的机制被调查。

英文摘要：

A dynamical-statistical post-processing ap- proach is applied to seasonal precipitation forecasts in China during the summer. The data are ensemble-mean seasonal forecasts in summer （June-August） from four atmospheric general circulation models （GCMs） in the second phase of the Canadian Historical Forecasting Project （HFP2） from 1969 to 2001. This dynamical-statistical approach is designed based on the relationship between the 500 geopotential height （Z500） forecast and the observed sea surface temperature （SST） to calibrate the precipitation forecasts. The results show that the post-processing can improve summer precipitation forecasts for many areas in China. Further examination shows that this post-processing approach is very effective in reducing the model-dependent part of the errors, which are associated with GCMs. The possible mechanisms behind the fore- cast＇s improvements are investigated.