基于降水空间分布相似的最优集成降水预报及其检验  

Prediction and test of optimal integrated precipitation based on similar spatial distribution of precipitation

作　　者：钱磊 邱学兴 郑淋淋[1,2,3] 朱红芳 安晶晶[1] 胡玥琦[4] QIAN Lei;QIU Xuexing;ZHENG Linlin;ZHU Hongfang;AN Jingjing;HU Yueqi(Anhui Meteorological Observatory,Hefei 230031;Anhui Institute of Meteorological Sciences,Hefei 230031;Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing,Hefei 230031;Huangshan Meteorological Bureau,Huangshan 245000)

机构地区：[1]安徽省气象台,合肥230031 [2]安徽省气象科学研究所,合肥230031 [3]大气科学与卫星遥感安徽省重点实验室,合肥230031 [4]安徽省黄山市气象局,黄山245000

出　　处：《暴雨灾害》2022年第3期324-335,共12页Torrential Rain and Disasters

基　　金：国家自然科学青年基金项目(41705029)。

摘　　要：利用预报业务上常用的ECMWF (European Centre for Medium-Range Weather Forecasts)全球模式和华东区域模式(WARMS 2.0)的降水预报,建立了基于空间分布相似的降水集成方法,主要分为3个步骤:(1)实时降水预报场空间尺度分离;(2)检索历史相似预报个例;(3)确定最优集成系数。在第(1)步尺度分离中采用高斯低通滤波方法,将降水场分解成连续性和分散性降水场;第(2)步相似个例检验利用了图像相似技术,根据连续性和分散性降水场综合寻找历史同期相似个例;在第(3)步集成系数确定中根据历史相似个例确定最优集成系数,并应用于最新实时预报中。通过结合图像识别、权重优化、建立历史样本数据库等方法,针对2018—2019年汛期(6—8月)检验结果表明:多模式集成产品的晴雨预报准确率相较于单模式而言有明显提高,且随时间变化表现较为稳定。在暴雨以上量级降水预报方面,集成产品的汛期整体TS评分高于单模式,Bias评分更接近1.0。通过CRA空间检验分析发现,集成产品既能一定程度上弥补全球模式在预报中尺度降水过程时强度偏弱的劣势,又纠正了区域模式在降水落区位置预报方面的偏差,进而实现了暴雨TS评分的提高。A precipitation integration method based on spatial distribution similarity was established by using ECMWF Global Model and Warms 2.0 precipitation Forecasts. The method basically contains 3 steps, i.e., step 1, spatial scale separation of real-time precipitation forecast field, step 2, retrieval of historical similar forecast cases, and step 3, determination of the optimal integration coefficient. In the first step of scale separation, Gaussian low-pass filtering is used to decompose the precipitation field into continuous and dispersive precipitation fields. The second step is similar case test, which uses image similarity technology to find similar cases in the historical period according to the continuity and dispersion of precipitation field. In the third step, the optimal integration coefficient is determined according to the historical similar cases and applied to the latest real-time forecast. By combining the methods of image recognition, weight optimization and establishment of historical sample database, the test results for flood season(June to August) in 2018-2019 are as follows: The accuracy of the weather forecast of multi-mode integrated products is significantly improved compared with the single mode, and the performance over time is relatively stable. In terms of precipitation forecast of magnitude above rainstorm, the overall TS score of the integrated product in the flood season is higher than that of the single model. When the scores of the ECMWF model and the East China model are similar, the integrated product tends to perform better, and the rainstorm range is more biased than the ECMWF model. Due to the small and large East China model, the range of integrated products is relatively moderate. Through CRA spatial inspection and analysis, it is found that the integrated product can not only compensate for the weakness of the global model in forecasting the mesoscale precipitation process to a certain extent, but also correct the deviation of the regional model in the prediction of the locat

关 键 词：多模式集成 定量降水预报 空间分布相似 CRA空间检验 

分 类 号：P456.7[天文地球—大气科学及气象学]