西非极端降雨事件的天气学分析:以lingu为例

M. Fall, A. Dieng, S. Sall, Y. Sané, Moussa Diakhaté
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引用次数: 1

摘要

在70年代和80年代的干旱期之后,萨赫勒国家经历了暴雨现象和毁灭性洪水的死潮,自21世纪初以来造成了许多社会经济损失。在这项工作中,通过使用塞内加尔民防方向(DPC)的极端事件数据库、卫星产品、ERA-Interim再分析和五个天气模式预测数据集,研究了与导致塞内加尔高度社会经济影响的极端降雨事件相关的环境条件。降雨事件发生在2017年8月26日的Linguere(15.07°W和15.23°N)。本研究旨在分析与该事件有关的天气条件,以及数值预报模式预测该事件的能力。卫星资料显示,降水对流系统于8月25日下午在低压槽层面启动,并于8月26日0600UTC - 1200UTC在林格尔上空发生了极端降雨事件。各种大气参数,如低层水汽输送的配置、可降水量、200和700 hpa的相对湿度以及700 hpa的相对涡度等,都是表征极端降雨的良好指标。所使用的数值预报模型能够预测林格尔附近的短期降雨。然而,没有一个模型可以预测降水的极端方面,因为与雨量计记录相比,它们往往低估了降水的强度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synoptic Analysis of Extreme Rainfall Event in West Africa: the Case of Linguère
After the drought period of the 70s and 80s, the Sahelian countries have experienced a resurgence of heavy rains phenomena and devastating floods causing a lot of socio-economic damages since the beginning of the 21st century. In this work, the environmental conditions associated with an extreme rainfall event that has led to high socio-economic impact in Senegal is studied by using the database of the extreme event from the DPC (Direction de la Protection Civil) of Senegal, Satellite products, ERA-Interim reanalysis and five Weather Model Prediction datasets. The rain event occurred on 26 August 2017 at Linguere (15.07°W and 15.23°N). This study aims to analyse the synoptic conditions associated to the event and also the ability of the numerical forecast models to predict it. The satellite dataset shows that the precipitating convective system was initiated at the level of a trough, on August 25 in the afternoon, and the extreme rain event took place on August 26 between 0600UTC and 1200UTC over Linguere. Various atmospheric parameters such as the configuration of the low-level moisture transport, precipitable water, relative humidity at 200 and 700-hPa as well as relative vorticity at 700-hPa appear as good indicators to characterize extreme rainfalls. The numerical forecast models used were able to predict short-term rainfall around Linguere. However, none of the models could predict the extreme aspect of precipitation because they tend to underestimate the intensity compared to rain gauge records.
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