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DOI10.1038/s41558-018-0359-7
Towards operational predictions of the near-term climate
Kushnir, Yochanan1; 39;Kane, Terence2
2019-02-01
发表期刊NATURE CLIMATE CHANGE
ISSN1758-678X
EISSN1758-6798
出版年2019
卷号9期号:2页码:94-101
文章类型Article
语种英语
国家USA; England; Canada; Spain; Japan; Switzerland; Germany; Australia; Peoples R China
英文摘要

Near-term climate predictions - which operate on annual to decadal timescales - offer benefits for climate adaptation and resilience, and are thus important for society. Although skilful near-term predictions are now possible, particularly when coupled models are initialized from the current climate state (most importantly from the ocean), several scientific challenges remain, including gaps in understanding and modelling the underlying physical mechanisms. This Perspective discusses how these challenges can be overcome, outlining concrete steps towards the provision of operational near-term climate predictions. Progress in this endeavour will bridge the gap between current seasonal forecasts and century-scale climate change projections, allowing a seamless climate service delivery chain to be established.


领域资源环境
收录类别SCI-E ; SSCI
WOS记录号WOS:000456994900011
WOS关键词MODEL INTERCOMPARISON PROJECT ; SURFACE-TEMPERATURE ; DECADAL PREDICTION ; SUBPOLAR GYRE ; EXPERIMENTAL-DESIGN ; OCEAN REANALYSES ; PACIFIC ; PREDICTABILITY ; VARIABILITY ; CMIP5
WOS类目Environmental Sciences ; Environmental Studies ; Meteorology & Atmospheric Sciences
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/34613
专题资源环境科学
作者单位1.Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY 10964 USA;
2.Met Off Hadley Ctr Climate Predict & Res, Exeter, Devon, England;
3.Univ Exeter, Coll Engn Math & Phys Sci, Exeter, Devon, England;
4.Iowa State Univ, Dept Agron, Ames, IA USA;
5.European Ctr Medium Range Weather Forecasts, Reading, Berks, England;
6.Environm Canada & Climate Change, Canadian Ctr Climate Modelling & Anal, Victoria, BC, Canada;
7.ICREA, Barcelona, Spain;
8.Barcelona Supercomp Ctr, Barcelona, Spain;
9.Univ Reading, Dept Meteorol, Natl Ctr Atmospher Sci, Reading, Berks, England;
10.Univ Tokyo, Atmosphere & Ocean Res Inst, Kashiwa, Chiba, Japan;
11.World Meteorol Org, World Climate Applicat & Serv Div, Climate Predict & Adaptat Branch, Climate & Water Dept, Geneva, Switzerland;
12.Climate Predict Ctr, College Pk, MD USA;
13.Max Planck Inst Meteorol, Hamburg, Germany;
14.GEOMAR Helmholtz Ctr Ocean Res Kiel, Kiel, Germany;
15.Christian Albrechts Univ Kiel, Kiel, Germany;
16.Deutsch Wetterdienst, Hamburg, Germany;
17.CSIRO Oceans & Atmosphere, Hobart, Tas, Australia;
18.Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO USA;
19.NOAA, Phys Sci Div, Earth Syst Res Lab, Boulder, CO USA;
20.Bur Meteorol, Melbourne, Vic, Australia;
21.Univ Calif Los Angeles, Los Angeles, CA USA;
22.Japan Meteorol Agcy, Tokyo, Japan;
23.WCRP WMO, Geneva, Switzerland;
24.Chinese Acad Sci, Inst Atmospher Phys, LASG, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Kushnir, Yochanan,39;Kane, Terence. Towards operational predictions of the near-term climate[J]. NATURE CLIMATE CHANGE,2019,9(2):94-101.
APA Kushnir, Yochanan,&39;Kane, Terence.(2019).Towards operational predictions of the near-term climate.NATURE CLIMATE CHANGE,9(2),94-101.
MLA Kushnir, Yochanan,et al."Towards operational predictions of the near-term climate".NATURE CLIMATE CHANGE 9.2(2019):94-101.
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