报告时间：2026年4月22日（周三）上午 10:00

报告地点：气象楼210报告厅

主  持 人： 曾跃飞 教授

报告题目：The impact of Aeolus satellite wind lidar observations in global NWP models

报告专家：Dr. Martin Weissmann 教授

专家简介:

Prof. Dr. Martin Weissmann has been the head of Data Assimilation Branch, Hans-Ertel Centre for Weather Research at the University of Munich in Germany until 2019 and the head of department of meteorology and geophysics at University of Vienna in Austria between 2020 and 2022. He is currently the member of the ESA Aeolus Science and data quality Advisory Group, the coordinator of the project Experimental Validation and Assimilation of Aeolus Observations (EVAA) and the lead organizer of International Symposium on Data Assimilation. His research interests cover atmospheric data assimilation, error modelling, wind lidars and Aeolus satellite.

报告摘要：

Launched in 2018, the Aeolus wind lidar satellite aimed to mitigate the lack of global wind profile observations for NWP models. Over nearly five years, it provided unprecedented direct wind profiles. Various NWP centers have demonstrated Aeolus's remarkable impact on forecast skill—according to ECMWF, the largest impact per satellite. Assimilation also improved mid-latitude precipitation forecasts. Despite proven benefits, the mechanisms behind improvements remain unclear, as Aeolus adds few observations with relatively high errors (~5 m/s) and low spatial resolution (~100 km). Largest gains occurred in the tropics, linked to better representation of tropical waves and correction of systematic structural errors in NWP models. This likely stems from Aeolus's ability to provide wind profiles, unlike most tropical wind observations (e.g., atmospheric motion vectors) limited to a single layer. In midlatitudes, improvements appear associated with Rossby wave packet excitation, but whether Aeolus can constrain divergent upper-level winds remains under investigation. This talk summarizes Aeolus impact studies, focusing on knowledge gaps that need resolution for a planned follow-on European wind lidar mission.

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气候系统预测与变化应对全国重点实验室

气象灾害教育部重点实验室

气象灾害预报预警与评估协同创新中心

大气科学学院

2026.04.17