气候变化领域集成服务门户(CCPortal): WeatherBench: A Benchmark Data Set for Data-Driven Weather Forecasting

CCPortal

DOI	10.1029/2020MS002203
	WeatherBench: A Benchmark Data Set for Data-Driven Weather Forecasting
	Rasp S.; Dueben P.D.; Scher S.; Weyn J.A.; Mouatadid S.; Thuerey N.
发表日期	2020
ISSN	19422466
卷号	12 期号:11
英文摘要	Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains. A natural question to ask is whether data-driven methods could also be used to predict global weather patterns days in advance. First studies show promise but the lack of a common data set and evaluation metrics make intercomparison between studies difficult. Here we present a benchmark data set for data-driven medium-range weather forecasting (specifically 3–5 days), a topic of high scientific interest for atmospheric and computer scientists alike. We provide data derived from the ERA5 archive that has been processed to facilitate the use in machine learning models. We propose simple and clear evaluation metrics which will enable a direct comparison between different methods. Further, we provide baseline scores from simple linear regression techniques, deep learning models, as well as purely physical forecasting models. The data set is publicly available at https://github.com/pangeo-data/WeatherBench and the companion code is reproducible with tutorials for getting started. We hope that this data set will accelerate research in data-driven weather forecasting. ©2020. The Authors.
英文关键词	artificial intelligence; benchmark; machine learning; NWP
语种	英语
scopus关键词	Deep learning; Learning systems; Computer scientists; Data-driven approach; Data-driven methods; Evaluation metrics; Forecasting models; Intercomparisons; Machine learning models; Simple linear regression; Weather forecasting; benchmarking; climate prediction; machine learning; prediction; regression analysis; weather forecasting
来源期刊	Journal of Advances in Modeling Earth Systems
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156576
作者单位	Department of Informatics, Technical University of Munich, Munich, Germany; European Centre for Medium-range Weather Forecasts, Reading, United Kingdom; Department of Meteorology and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden; Department of Atmospheric Sciences, University of Washington, Seattle, WA, United States; Department of Computer Science, University of Toronto, Toronto, ON, Canada
推荐引用方式 GB/T 7714	Rasp S.,Dueben P.D.,Scher S.,et al. WeatherBench: A Benchmark Data Set for Data-Driven Weather Forecasting[J],2020,12(11).
APA	Rasp S.,Dueben P.D.,Scher S.,Weyn J.A.,Mouatadid S.,&Thuerey N..(2020).WeatherBench: A Benchmark Data Set for Data-Driven Weather Forecasting.Journal of Advances in Modeling Earth Systems,12(11).
MLA	Rasp S.,et al."WeatherBench: A Benchmark Data Set for Data-Driven Weather Forecasting".Journal of Advances in Modeling Earth Systems 12.11(2020).