气候变化领域集成服务门户(CCPortal): Decadal predictability of temperature and precipitation means and extremes in a perfect-model experiment

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DOI	10.1007/s00382-019-04734-z
	Decadal predictability of temperature and precipitation means and extremes in a perfect-model experiment
	Liu Y.; Donat M.G.; Rust H.W.; Alexander L.V.; England M.H.
发表日期	2019
ISSN	0930-7575
起始页码	3711
结束页码	3729
卷号	53 期号:2020-07-08
英文摘要	The assessment of predictability for decadal predictions of quantities like temperature and precipitation typically focuses on regional and temporal mean values. However, changes in extremes can be different to changes in mean climate, and accordingly their predictability may be different. We use simulations from CSIRO-Mk3-6-0 (CMIP5 archive) to set up a ‘perfect model’ experiment to compare the predictability for mean and extreme temperature and precipitation on interannual to decadal time-scales. The results show that both the mean and likelihood of near-surface temperature extremes is potentially predictable in many regions in the first lead year, while the areas with precipitation predictability tend to be mostly in low-latitude regions during this period. On decadal time scales, significant potential skill for mean and extreme temperatures is found over the North Atlantic and Southern Ocean but also over some land areas including North Africa, Europe and North America. The general spatial patterns of predictability are very similar between the mean and extremes. However, indices of moderate temperature extremes in particular show a tendency towards higher predictability than the mean. The approach to studying predictability presented here uses international coordinated model intercomparison project simulations. However a larger number of different initializations would be required from more models to allow improved robustness of the results. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
英文关键词	Climate extremes; Climate prediction; CMIP5; Perfect model; Precipitation; Predictability; Temperature
语种	英语
scopus关键词	climate prediction; CMIP; decadal variation; experimental study; extreme event; numerical model; precipitation assessment; spatiotemporal analysis; temperature effect; Europe; North Africa; North America
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/146003
作者单位	Climate Change Research Centre and ARC Centre of Excellence for Climate Extremes, UNSW, Sydney, NSW, Australia; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Institut fuer Meteorologie, Freie Universität Berlin, Berlin, Germany
推荐引用方式 GB/T 7714	Liu Y.,Donat M.G.,Rust H.W.,et al. Decadal predictability of temperature and precipitation means and extremes in a perfect-model experiment[J],2019,53(2020-07-08).
APA	Liu Y.,Donat M.G.,Rust H.W.,Alexander L.V.,&England M.H..(2019).Decadal predictability of temperature and precipitation means and extremes in a perfect-model experiment.Climate Dynamics,53(2020-07-08).
MLA	Liu Y.,et al."Decadal predictability of temperature and precipitation means and extremes in a perfect-model experiment".Climate Dynamics 53.2020-07-08(2019).