文章基本信息

标题：ESA-ECMWF Report on recent progress and research directions in machine learning for Earth System observation and prediction
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作者：Rochelle Schneider ; Massimo Bonavita ; Alan Geer 等
期刊名称：npj Climate and Atmospheric Science
电子版ISSN：2397-3722
出版年度：2022
卷号：5
期号：1
页码：1-5
DOI：10.1038/s41612-022-00269-z
语种：English
出版社：Nature Publishing Group
摘要：This paper provides a short summary of the outcomes of the workshop on Machine Learning (ML) for Earth System Observation and Prediction (ESOP / ML4ESOP) organised by the European Space Agency (ESA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) between 15 and 18 November 2021. The 4-days workshop had more than 30 speakers and 30 poster-presenters, attracting over 1100 registrations from 85 countries around the world. The workshop aimed to demonstrate where and how the fusion between traditional ESOP applications and ML methods has shown limitations, outstanding opportunities, and challenges based on the participant’s feedback. Future directions were also highlighted from all thematic areas that comprise the ML4ESOP domain.