基于延伸期可预报性的集合预报方法和数值试验

Predictability-based extended-range ensemble prediction method and numerical experiments

集合预报是考虑初始条件和模式不确定性的有效途径.结合延伸期可预报性特征,对具有不同特性的可预报分量和随机分量采用不同的集合预报方案和策略,发展了一种基于延伸期可预报性的集合预报新方法(PBEP).该方法以延伸期数值预报模式为平台,对可预报分量采用多个模式误差订正方案,从考虑模式不确定性的角度进行集合;而对随机分量则利用历史资料从气候概率的角度给出集合概率分布,避免模式误差对随机分量概率分布的影响.试验结果表明,相比于国家气候中心的业务动力延伸集合预报系统,该集合预报方法对全球各区域环流预报技巧均有提高,对不同空间尺度的波也有不同程度的改进,显示出潜在的业务应用前景.

Ensemble prediction is an effective approach to accounting for uncertainties of initial conditions and model error. By combining the predictability of extended-range, both predictable components and unpredictable random components with different characteristics are treated with different ensemble prediction schemes and strategies. A new predictability-based extended-range ensemble prediction method （PBEP） is proposed. In this method, for predictable component, the uncertainty of model is taken into account through the use of multiple error correction scheme; while the random component probability distribution is obtained from the climate probability distribution of historical data, for the sake of avoiding the influence of model error. Prediction results show that the ensemble prediction method can improve the forecast skill in all regions of the world, and the extents of improvement are different for waves with differ- ent spatial scales compared with the operational dynamical extended-range ensemble prediction system of NCC/CMA, exhibiting its potential application perspective to operational extended-range prediction.