2020年梅汛期强降水事件的预报误差来源分析  

Forecast Error Source Analysis of Heavy Rainfall Events in the Meiyu period of 2020

作　　者：林琳 卢楚翰[1] 周菲凡[2,3] LIN Lin;LU Chuhan;ZHOU Feifan(Key Laboratory of Meteorological Disaster,Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science and Technology,Nanjing 210044;Laboratory of Cloud−Precipitation Physics and Severe Storms,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029;University of Chinese Academy of Sciences,Beijing 100049)

机构地区：[1]南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心,南京210044 [2]中国科学院大气物理研究所云降水物理与强风暴实验室,北京100029 [3]中国科学院大学,北京100049

出　　处：《气候与环境研究》2022年第4期469-479,共11页Climatic and Environmental Research

基　　金：国家重点研发计划项目:2018YFC1507405、2017YFC1501601。

摘　　要：基于WRF模式(Weather Research and Forecasting Model)分析2020年超长梅汛期内11次强降水事件的预报误差来源。分别以FNL(Final Global Data Assimilation System)、TIGGE_EC(THORPEX Interactive Grand Global Ensemble from European Centre for Medium-Range Weather Forecasts)作为初始场进行预报,对比预报结果发现,TIGGE_EC初始场的预报结果普遍优于FNL,这说明初始条件的不确定性对预报结果有重要影响。进一步探究初始条件不确定性(初始误差)来源的区域(敏感区)和变量(敏感变量)发现,敏感区集中分布于降水区西侧上游,相对应的敏感变量为水汽场。分别考察动能、有效位能以及比湿能在初始误差总能量中的占比,结果表明,扰动比湿能占比最小,但敏感性试验表明比湿场扰动对预报效果的影响最大。选取比湿场扰动对预报效果影响最大且WRF_EC具有更好预报效果的6个暴雨事件,通过HYSPLIT后向轨迹模式分别追踪其累计降水量最大值点的水汽来源及路径发现,有6个事件均有向降水区西侧上游延伸的水汽来源通道,进一步表明了敏感区的初始水汽场的准确性对暴雨预报的影响。因此降水区西侧上游的水汽场的误差是这11次梅汛期暴雨过程重要的预报误差来源,对其准确描述可有助于预报效果的提升。Based on the WRF(Weather Research and Forecasting)model,this study investigates the forecast error sources of eleven heavy precipitation events during the Meiyu period in 2020.Forecasts using the WRF model were generated with the initials of NCEP_FNL(Final Global Data Assimilation System)and TIGGE_EC(THORPEX Interactive Grand Global Ensemble from European Centre for Medium-Range Weather Forecasts)and were subsequently compared.Results indicated that the TIGGE_EC initially exhibited higher forecast skills,demonstrating that the uncertainty of the initial conditions heavily influences the forecast results.Next,the regions(sensitive areas)and variables(sensitive variables)where the uncertainty of the initial errors originated were explored.It was observed that the sensitive areas were concentrated in the upper reaches of the western side of the precipitation area.The proportions of the kinetic,effective potential and specific humidity energies in the total energy of the initial error indicated that the specific humidity energy occupied the smallest proportion;however,the sensitivity experiment demonstrated that the disturbance in a specific humidity field has the highest impact on the forecast.Therefore,seven rainstorm events were selected wherein the specific humidity field had the greatest impact on the forecasts and the water vapor source and path of the maximum accumulated precipitation point were tracked using the HYSPLIT backward trajectory model.Of the seven rainstorm events,six events showed the water vapor source channels moving upstream to the west of the precipitation area.Therefore,the upstream water vapor change in the west of the precipitation area was a valuable source for forecast errors in the heavy precipitation events during the Meiyu period in 2020,and its accurate description could help improve the rainfall forecasts.

关 键 词：初始误差 梅雨期强降水 敏感区 敏感变量 水汽来源 

分 类 号：P457[天文地球—大气科学及气象学]