多模式对东北地区月降水预测性能对比评估

Evaluation of forecast skill of monthly rainfall over Northeast China using multi-models

基于中国、美国、欧洲和日本的4种气候模式对1983—2010年东北地区降水的回报试验结果,利用2011—2014年东北地区业务应用的结果和国家气象信息中心提供的东北地区172个气象站的观测资料,采用距平相关系数(ACC)、趋势异常综合评分(Ps)和距平符号一致率(Pc)3种定量方法对比评估了4种模式对东北地区月降水的预测性能。结果表明:EC模式和CFSv 2模式与BCC模式和TCC模式相比,EC模式和CFSv 2模式对东北地区月降水的总体预测效果较好,具有一定的预测技巧。从空间上来看,CFSv 2模式各月Pc的分布存在较明显的差异,模式仍有较大的改进空间。CFSv 2模式对东北地区初夏典型旱涝年具有一定的预测能力,对典型涝年的预测效果优于典型旱年。

The prediction skill of four climate models for monthly rainfall over Northeast China was evaluated using three qualitative evaluation methods,i. e.,anomaly correlation coefficient（ ACC）, trend anomaly inspection evaluation（ Ps） and anomaly symbol consistency rate（ Pc）. Many data were used in this study, including 172 meteorological stations over Northeast China supplied by the National Meteorological Information Center, the hindcast experimental results of rainfall over Northeast China from 1983 to 2010 according to four climate models from China,America, Japan and Europe,and the operational application results over Northeast China from 2011 to 2014.The results indicate that the monthly rainfall prediction skills of EC（ European Center for Medium-Range Weather Forecasts） and CFSv 2（ Coupled Forecast System Model Version 2） models are better than those of BCC（ Beijing Climate Center） and TCC（ Tokyo Climate Center） models. Looking at the spatial distribution, there is a significant difference in the distribution of each monthly Pc for CFSv 2 model, indicating that this model has a big space for its improvement. The CFSv 2 model has some prediction skills in early summer during typical drought and flood years,and the prediction effect in typical flood years is better than that in typical drought years.