Classification analysis of prediction skill among ensemble members in MJO subseasonal predictions——based on the results of the CAMS-CSM subseasonal prediction systemOA
由于模式误差和初始误差所致,次季节-季节预报技巧整体偏低.国际上多数模式都采用集合预报的方式来提高次季节预报的准确率.热带大气季节内振荡(MJO)作为次季节尺度可预报性的重要来源,其预测水平取决于模式性能和MJO事件本身的物理特性.根据中国气象科学研究院气候系统模式次季节预测系统的回报结果,结合不同类型MJO事件的特征,对模式集合成员间的预报技巧进行了分类和比较.在集合成员预报技巧普遍较高的一类MJO事件中,对流异常信号持续时间较长,强度较大,强…查看全部>>
Yihao Peng;Xiaolei Liu;Jingzhi Su;Xinli Liu
State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing,China Center for Earth System Modeling and Prediction of CMA(CEMC),Beijing,ChinaState Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing,ChinaState Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing,China Center for Earth System Modeling and Prediction of CMA(CEMC),Beijing,China Key Laboratory of Earth System Modeling and Prediction China Meteorological Administration,Beijing,ChinaState Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing,China
大气科学
次季节-季节预测预报技巧热带大气季节内振荡
《Atmospheric and Oceanic Science Letters》 2024 (4)
P.8-14,7
supported by the National Key Research and Development Program [grant number 2022YFC3004203]。
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