基于局地增长模培育法的对流可分辨尺度WRF模式对河南“21·7”特大暴雨的预报评估

基于WRF(Weather Research and Forecasting)模式,选取河南“21·7”特大暴雨事件,采用局地增长模培育法(Local Breeding Growth Mode,LBGM)生成对流尺度集合预报系统,在此基础上对24 h累积降水量进行SAL(Structure,Amplitude and Location)检验,结合预报成功指数(Threat Score,TS)、公平成功指数(Equitable Threat Score,ETS)评分等评分结果进行对比分析,综合评估集合预报成员的预报效果,表明:1)基于局地增长模培育法生成初始扰动的集合预报系统成员对于强降水预报有一定优势,在降水强度和位置的预报上与实况较接近;2)经检验,成员e003的TS和ETS评分在20日00时—21日00时(北京时,下同)和21日08时—22日08时两个强降水时段内表现最佳,并在SAL检验中对应较好的降雨强度A和雨区位置L,而成员e008暴雨TS、ETS评分最低,对应SAL检验中具有一定的位置偏差,即TS、ETS评分和SAL检验之间存在相关性,将二者有机结合,可以为业务工作中定量评估模式降水预报效果提供参考;3)通过对比整体评分表现较好的成员e003和较差的成员e008,两者预报的位势高度场与ERA5(ECMWF reanalysis v5,ERA5)再分析资料之间的差值,可以验证降水预报误差主要源于对低涡系统的预报偏差,同时预报评分较好的成员其位势高度偏差较小,综合评估效果更佳。

Assessment of the convection-allowing scale WRF model using LBGM theory:a case study of severe torrential rain in Henan Province,July 2021

Ensemble forecasting has emerged as a crucial method for enhancing quantitative precipitation forecasting in operational meteorology.To advance our understanding and improve effectiveness of ensemble predictions,it is imperative to rigorously and accurately assess the predictive skills of ensemble forecast systems.This study offers a comprehensive evaluation of prediction performance using statistical scoring methods such as Threat Score (TS),Equitable Threat Score (ETS),and spatial forecast verification (SAL) based on precipitation forecasts from perturbation and control ensemble members.Our results reveal the following:1) Ensemble members that initialize disturbances based on local breeding growth processes exhibit distinct advantages in forecasting heavy rainfall,yielding predictions that closely align with observed precipitation intensity and spatial distribution.2) Among all ensemble members,member e003 demonstrates the highest TS and ETS scores,along with the lowest false alarm rate and missing alarm rate.These scores are associated with superior accuracy in forecasting rainfall intensity (A) and rain area (L) in SAL verification.Conversely,member e008 displays the lowest scores for TS and ETS related to heavy rainfall,indicating a certain positional deviation in the SAL evaluation.3) Model precipitation forecast bias primarily arises from deviations in forecasting the low vortex system.Furthermore,the evaluation results of precipitation forecast scores for proficient ensemble members tend to exhibit a high degree of consistency.