1) dynamical seasonal prediction
动力季节预测
1.
In order to better improve dynamical seasonal prediction by utilizing statistical experiences, the problem of capturing statistical experiences associated with climate model is discussed from the point of view of studying the impacts of physical predictors in climate system on model prediction errors.
为了在动力季节预测中更好地运用统计经验来改进预报,从研究气候系统物理因子影响模式预报误差的角度入手,探讨了与气候模式有关的统计经验获取问题,并利用国家气候中心海-气耦合模式的历史回报数据,考察了动力季节预测中夏季环流和降水的预报误差与主要物理因子,包括Nio3区海温指数、太平洋年代际振荡指数、南北