气候变化领域集成服务门户(CCPortal): Machine learning and artificial intelligence to aid climate change research and preparedness

CCPortal

DOI	10.1088/1748-9326/ab4e55
	Machine learning and artificial intelligence to aid climate change research and preparedness
	Huntingford C.; Jeffers E.S.; Bonsall M.B.; Christensen H.M.; Lees T.; Yang H.
发表日期	2019
ISSN	17489318
卷号	14 期号:12
英文摘要	Climate change challenges societal functioning, likely requiring considerable adaptation to cope with future altered weather patterns. Machine learning (ML) algorithms have advanced dramatically, triggering breakthroughs in other research sectors, and recently suggested as aiding climate analysis (Reichstein et al 2019 Nature 566 195-204, Schneider et al 2017 Geophys. Res. Lett. 44 12396-417). Although a considerable number of isolated Earth System features have been analysed with ML techniques, more generic application to understand better the full climate system has not occurred. For instance, ML may aid teleconnection identification, where complex feedbacks make characterisation difficult from direct equation analysis or visualisation of measurements and Earth System model (ESM) diagnostics. Artificial intelligence (AI) can then build on discovered climate connections to provide enhanced warnings of approaching weather features, including extreme events. While ESM development is of paramount importance, we suggest a parallel emphasis on utilising ML and AI to understand and capitalise far more on existing data and simulations. © 2019 The Author(s). Published by IOP Publishing Ltd.
英文关键词	artificial intelligence; climate change; climate simulations; drought; extreme weather; global warming; machine learning
语种	英语
scopus关键词	Artificial intelligence; Climate change; Drought; Earth (planet); Extreme weather; Global warming; Learning systems; Climate analysis; Climate simulation; Climate system; Earth system model; Earth systems; Extreme events; Teleconnections; Weather patterns; Machine learning; artificial intelligence; climate change; climate feedback; drought; extreme event; global warming; machine learning; research work; simulation; teleconnection; weather
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/154324
作者单位	Centre for Ecology and Hydrology, Oxfordshire, Wallingford, OX10 8BB, United Kingdom; Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS, United Kingdom; Atmospheric Oceanic and Planetary Physics, Department of Physics, Clarendon Laboratory, University of Oxford, Oxford, OX1 3PU, United Kingdom; School of Geography and the Environment, University of Oxford, South Parks Road, Oxford, OX1 3QY, United Kingdom; Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
推荐引用方式 GB/T 7714	Huntingford C.,Jeffers E.S.,Bonsall M.B.,et al. Machine learning and artificial intelligence to aid climate change research and preparedness[J],2019,14(12).
APA	Huntingford C.,Jeffers E.S.,Bonsall M.B.,Christensen H.M.,Lees T.,&Yang H..(2019).Machine learning and artificial intelligence to aid climate change research and preparedness.Environmental Research Letters,14(12).
MLA	Huntingford C.,et al."Machine learning and artificial intelligence to aid climate change research and preparedness".Environmental Research Letters 14.12(2019).