多模式对东北地区月气温的预测性能对比评估  

Contrast and Evaluation of Multi-Model Forecast Performance of Monthly Temperature over Northeast China

作　　者：王莹[1] 李永生[2] 段春锋[3] 

机构地区：[1]黑龙江省气象服务中心,哈尔滨150036 [2]黑龙江省气候中心,哈尔滨150030 [3]安徽省气候中心,合肥230031

出　　处：《气象科技》2016年第5期749-753,762,共6页Meteorological Science and Technology

基　　金：公益性行业(气象)科研专项(GYHY201006006);黑龙江省气象局项目(HQ2015027);安徽省自然科学基金(1308085QD69)共同资助

摘　　要：基于BCC的DERF 2.0(中国)、CFSv2(美国)、EC(欧洲)、TCC(日本)4种模式开展的1983—2010年对东北地区的回报试验结果、2011—2014年业务应用结果和国家气象信息中心提供的东北地区172个台站气象观测资料,利用距平相关系数(ACC)、趋势异常综合检验(PS)评估和距平符号一致率(PC)3种定量方法对比评估了4种模式对东北地区月气温的预测性能。结果表明,EC模式和CFSv2模式与BCC模式和TCC模式相比,对月气温的总体预测效果较好,有一定的预测技巧。从空间上来看,CFSv2的PC在前半年表现的比后半年的略好,PC超过80%的范围比较大。CFSv2和EC模式对东北地区夏季典型低温年有一定的预测能力。Based on the data of 172 weather stations supplied by the National Meteorological Information Center and the hindcast data of the models from China,American,Japan and Europe from 1983 to 2010and operational application results from 2011 to 2014,the prediction performance of monthly temperature is evaluated and analyzed by using Anomaly Correlation Coefficient（ACC）,Trend Anomaly Inspection Evaluation（PS）,and Anomaly Symbol Consistency rate（PC）.The results indicate that the monthly temperature prediction performance of EC and CFSv2 is better than those of BCC and TCC model and have some skill.From space,the PC from CFSv2 is better in the first half year than in the second half year,and the range of more than 80%is larger.It is also shown that CFSv2 and EC have certain skill in typical low temperature years in summer in Northeast China

关 键 词：气候模式 月气温 预测性能 评估 

分 类 号：P456.7[天文地球—大气科学及气象学]