摘要
数值天气预报检验是改进及应用数值模式的重要环节。近年来,模式检验中的观念不断更新,适用于不同预报产品及不同用户需求的模式检验方法也不断涌现。首先简单回顾了以列联表为基础的传统的模式检验方法。其次重点总结了伴随高分辨率数值预报而出现的空间诊断检验技术,按照检验目的的不同,诊断方法可以归纳为:①基于滤波技术的分辨模式在不同时空尺度上预报能力的邻域法、尺度分离法;②利用位移偏差诊断模式预报位置、面积、方位、轴角等与观测差异的属性判别法、变形评估法。然后阐述了集合样本成员的概率分布函数(PDF)、集合预报与观测概率分布函数相似程度、事件发生的概率预报等集合预报检验方法。最后论述了空间诊断技术、集合预报检验方法的适用领域,并讨论了模式检验中存在的一些问题及未来的发展方向。
The numerical weather prediction verification is a key step to improving applied numerical models. In recent years, the concepts used in model verification have been updated constantly and the model verification ap- proaches fit for different prediction products and meeting the needs of different customers have proposed continuous- ly. First, this research gives a brief overview of traditional model verification methods based on contingency table. Second, the spatial verification technology along with high resolution numerical prediction is illustrated. According to different purposes, the spatial verification methods can mostly be classified into two general categories： filtering methods and displacement methods. The filtering methods can be further delineated into neighborhood and scale separation, and the displacement methods can be divided into features-based ones and field deformations. Third, the probability distribution function of ensemble prediction sample members, the similar degrees between probability distribution function of ensemble prediction and the observation distribution function, the probability of an event oc- curring and such ensemble prediction verification methods are described. Finally, the fields where spatial verifica- tion technology and ensemble prediction verification methods can be used are analyzed and some problems concern- ing model verification and the direction in which these technologies will go are discussed.
出处
《地球科学进展》
CAS
CSCD
北大核心
2014年第3期327-335,共9页
Advances in Earth Science
基金
中国气象局预报员专项"T639
ECMWF
日本高分辨率模式对陕西强降水过程预报性能的诊断分析"(编号:CMAYBY2014-070)
陕西省气象局数值模式应用团队
预报员专项"基于MODE方法的日本
T639高分辨率模式降水预报能力的诊断分析"(编号:2014Y-9)资助
关键词
空间诊断
集合预报
概率预报
Spatial forecast verification
Ensemble forecasts
Probability forecasts.
