肖柳斯,张华龙,张旭斌,冯璐,谌志刚,戴光丰. 2021. 基于CMA-TRAMS集合预报的“5·22”极端降水事件可预报性分析[J]. 气象学报, 79(6):956-976, doi:10.11676/qxxb2021.058
基于CMA-TRAMS集合预报的“5·22”极端降水事件可预报性分析
Predictability analysis of the extremely heavy rainfall in the Pearl River Delta on 22 May 2020 using CMA-TRAMS-based ensemble prediction system
投稿时间:2020-11-05  修订日期:2021-07-09
DOI:10.11676/qxxb2021.058
中文关键词:  集合预报  热带中尺度集合预报系统  极端降水  可预报性
英文关键词:Ensemble forecast  CMA-TRAMS (EPS)  Extremely heavy rainfall  Predictability
基金项目:国家自然科学基金项目(41975136、41875182)、广东省基础与应用基础研究基金项目(2019A1515011118)、广东省重点领域研发计划项目(2020B1111200001)、广东省气象局科研项目(GRMC2018Z05)、广州市气象学会科研项目(M202101)、雷达应用及强对流短临预警技术创新团队项目(GRMCTD202002)
作者单位E-mail
肖柳斯 广州市气象台广州511430  
张华龙 广东省气象台广州510641  
张旭斌 中国气象局广州热带海洋气象研究所广州510641
广东省区域数值天气预报重点实验室广州510641 
xbzhang@gd121.cn 
冯璐 中国气象局广州热带海洋气象研究所广州510641  
谌志刚 广州市气象局广州511430  
戴光丰 中国气象局广州热带海洋气象研究所广州510641
广东省区域数值天气预报重点实验室广州510641 
 
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中文摘要:
      2020年5月22日珠江三角洲地区出现了一次极端强降水天气,最大滑动小时雨量201.8 mm,3 h雨量达到351 mm。为探讨此次极端强降水的关键预报因子及可预报性,对热带中尺度集合预报系统(CMA-TRAMS(EPS))降水预报产品进行检验评估和敏感性分析,结果表明:与欧洲中期数值预报中心集合预报系统(ECMWF-EPS)相比,CMA-TRAMS(EPS)的好成员对本次过程降水强度及位置的预报结果与实况更接近,但对极端性预报仍有欠缺。好成员的预报能力来自于对低涡和(超)低空急流的演变特征以及两者强度和位置耦合的有效预测。好成员组预报珠江三角洲东部(超)低空急流南风分量较强,有利于低涡缓慢移动和气旋性辐合增强,致使降水持续时间长、效率高。而低涡自身发展又反馈于急流强度变化,好成员组较准确地刻画了增强的低涡环流反馈导致急流小范围加速的耦合特征。其他成员组预报的低涡和(超)低空急流的耦合位置偏东、偏南,辐合强度偏弱,导致降水强度或落区出现偏差。此外,强降水致使冷池形成,并增强激烈的冷、暖气团对峙(水平温度梯度达0.23—0.76℃/km),有利于中尺度辐合线维持,加强对流后向传播并产生极端降水量。但CMA-TRAMS(EPS)两组成员在预报中尺度系统的组织性和传播特征方面均存在明显不足,限制了集合预报系统对极端降水的预报能力。
英文摘要:
      An extremely heavy rainfall occurred in the Pearl River Delta on 22 May 2020 with the sliding 1 h maximum precipitation of 201.8 mm, and the total rainfall of 351 mm in 3 h. In order to investigate the key forecasting factors and the predictability of this case, the evaluation and sensitivity analysis of precipitation forecasts by the mesoscale ensemble prediction system that is based on the Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS(EPS)) are carried out. The results show that compared with the ECMWF Ensemble Prediction System (ECMWF-EPS), the good-performance members of CMA-TRAMS(EPS) have better ability to capture the intensity and spatial distribution of the heavy rainfall, but they still miss the extremity. The better prediction ability of these members comes from their effective prediction of the evolution characteristics of the low vortex and low-level jet (or boundary layer jet) as well as the intensity and location of the coupling between the two systems. The strong southerly wind component of the low-level jet (boundary layer jet) over the eastern part of the Pearl River Delta is conducive to the deceleration of the low vortex moving and the enhancement of cyclonic convergence, both of which are favorable for long duration and high efficiency of precipitation. In addition, the development of the low vortex itself has feedback on changes in the intensity of low-level jet (boundary layer jet). The low-level jet (boundary layer jet) is accelerated in a small area due to the feedback of the enhanced vortex circulation. This coupling mechanism is well described by the good-performance ensemble members. However, the coupling position of the low vortex and low-level jet (or boundary layer jet) predicted by other members is located to the east and south of its actual position, and the convergence intensity is underestimated. The above biases in the simulation lead to the deviation of rainfall intensity and rainfall area. In addition, heavy rainfall results in the formation of cold pool and intensifies the contrast between the surface warm ridge and cold pool (with horizontal temperature gradient of 0.23—0.76℃/km), which is conducive to the maintenance of mesoscale convergence line and strengthens the backward propagation of convection, leading to extreme rainfall. However, all the members of CMA-TRAMS(EPS) have obvious deficiencies in forecasting the organization and propagation characteristics of the mesoscale systems, which limits the ability of CMA-TRAMS(EPS) for predicting extremely heavy rainfall.
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