基于超级集合思想的数值预报产品变权集成方法探讨

Exploration on Ensemble Model of Numerical Forecasting Based on Variable-weight Super-ensemble Method

针对目前地方气象台站能获取的国内外数值预报产品种类多、数量大、质量参差不齐的实际情况,探讨了几种基于超级集合思想的多模式数值预报动态变权集成处理方法。该方法经济、简便、有效,为预报员从海量的数值产品信息中提取更为准确和精细的集成形势场、物理量场、降水预报、冷空气活动预报、集成矩、特征线路图等多种具有较高质量的集成统计新产品,能动态反映各类数值预报模式的预报能力变化,在一定程度上提高了不同时间、不同区域的精细化预报水平和数值产品的利用效率,为业务预报提供了有价值的参考。

The ensemble methods to get a better combined result from large quantities of numerical forecast model output products are investigated. Some variable-weight decision-making models based on super-ensemble methods are put forward. Evidences suggest that these models are simple, convenient and effective, which can help forecasters to pick up enough high-quality ensemble statistics information from massive numerical products, such as circulation situation, fields of physical elements, precipitation prediction, cold air prediction, ensemble matrix, map of character. The ensemble methods are more perfect and refined, which can dynamically reflect the abilities of charactering each numerical model. And this helps to improve the effect and skill of refined numerical weather forecasting for different area and time to some extent, and provides valuable reference to the operational prediction.