气候变化领域集成服务门户(CCPortal): Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes

CCPortal

DOI	10.1038/s41612-020-00149-4
	Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes
	Kelder T.; Müller M.; Slater L.J.; Marjoribanks T.I.; Wilby R.L.; Prudhomme C.; Bohlinger P.; Ferranti L.; Nipen T.
发表日期	2020
ISSN	23973722
卷号	3 期号:1
英文摘要	Sample sizes of observed climate extremes are typically too small to reliably constrain return period estimates when there is non-stationary behaviour. To increase the historical record 100-fold, we apply the UNprecedented Simulated Extreme ENsemble (UNSEEN) approach, by pooling ensemble members and lead times from the ECMWF seasonal prediction system SEAS5. We fit the GEV distribution to the UNSEEN ensemble with a time covariate to facilitate detection of changes in 100-year precipitation values over a period of 35 years (1981–2015). Applying UNSEEN trends to 3-day precipitation extremes over Western Norway substantially reduces uncertainties compared to estimates based on the observed record and returns no significant linear trend over time. For Svalbard, UNSEEN trends suggests there is a significant rise in precipitation extremes, such that the 100-year event estimated in 1981 occurs with a return period of around 40 years in 2015. We propose a suite of methods to evaluate UNSEEN and highlight paths for further developing UNSEEN trends to investigate non-stationarities in climate extremes. © 2020, The Author(s).
语种	英语
scopus关键词	climate prediction; decadal variation; ensemble forecasting; extreme event; historical record; precipitation (climatology); seasonal variation; trend analysis
来源期刊	npj Climate and Atmospheric Science
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178018
作者单位	Geography and Environment, Loughborough University, Loughborough, United Kingdom; The Norwegian Meteorological Institute, Oslo, Norway; Section for Meteorology and Oceanography, Department of Geosciences, University of Oslo, Oslo, Norway; School of Geography and the Environment, University of Oxford, Oxford, United Kingdom; School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough, United Kingdom; European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, United Kingdom; Centre for Ecology and Hydrology, Wallingford, United Kingdom
推荐引用方式 GB/T 7714	Kelder T.,Müller M.,Slater L.J.,et al. Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes[J],2020,3(1).
APA	Kelder T..,Müller M..,Slater L.J..,Marjoribanks T.I..,Wilby R.L..,...&Nipen T..(2020).Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes.npj Climate and Atmospheric Science,3(1).
MLA	Kelder T.,et al."Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes".npj Climate and Atmospheric Science 3.1(2020).