中国区域月气候预测方法和预测能力评估  

Assessment and Analysis of Monthly Climate Prediction in China

作　　者：陈丽娟[1] 李维京[2] 刘绿柳[2] 张培群[2] 

机构地区：[1]中国科学院大气物理研究所,北京100029 [2]中国气象局国家气候中心中国气象局气候研究开放实验室,北京100081

出　　处：《高原气象》2008年第4期838-843,共6页Plateau Meteorology

基　　金：国家自然科学基金项目(40675039);国家科技支撑计划项目(2006BAC02B04);中国气象局业务建设项目“气候模式产品在区域气候预测业务中的应用”共同资助

摘　　要：利用我国台站降水和温度观测资料,评估了BCC_AGCM1.0月动力延伸预报的回算和预测、国家气候中心月气候预测业务统计方法、持续性预报以及业务发布预报对中国区域月气候要素的预测能力。结果表明,业务发布月平均温度和降水预测的技巧平均低于动力方法和统计方法的预测结果。温度的持续性预报和最优气候值统计方法预报技巧高于其它统计预报方法,考虑了综合相似特征的统计方法对降水预测有相对的优势。动力延伸预报的三种超前预报时间的预测结果总体高于统计方法,在月气候预测能力上具有明显优势。月尺度预测动力和统计方法评估的年际变化特征表明月降水和温度的可预报性一般在El Nio状态下较高,而在La Nia发生时偏低。Using the observation data over China, the hindcast and predict data of BCC_AGCM1.0, statistic methods, persistent prediction, operational forecasts were evaluated and analyzed. It showed that the score skill of the operational forecast was lower than that of statistical and dynamical methods. The persistent forecast and optimal climate normal on temperature have relatively high skills. The other statistical methods indicate relatively low skills. The statistical method which reflects the analogue of the ocean and atmosphere has higher skill on precipitation forecast than others. The skill of three leadtime results of the dynamic model was absolutely higher than other statistic methods. Annual score skill of different methods show that the predictability of the monthly climate was affected by the ENSO cycle. The skill is higher under El Nino state than under La Nina state.

关 键 词：中国区域 月气候预测 大气可预报性 

分 类 号：P456[天文地球—大气科学及气象学]