Assessment of potential risks induced by increasing extreme precipitation under climate change

被引:47
作者
Huang, Hefei [1 ,2 ]
Cui, Huijuan [1 ]
Ge, Quansheng [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Patterns & Simulat, Beijing 100101, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
Potential risk; Extreme precipitation; Threshold; Climate change; DURATION SERIES METHODS; ANNUAL MAXIMUM SERIES; CHANGE PROJECTIONS; HYDROLOGIC EVENTS; SYSTEM MODEL; RIVER-BASIN; FLOOD RISK; FREQUENCY; RAINFALL; TRENDS;
D O I
10.1007/s11069-021-04768-9
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
A warmer climate has caused more extreme climate events like the heatwave or extreme precipitation, which has led to a large number of lives and economic losses. In this study, we adopt historical daily precipitation from rainfall estimates on a gridded network (REGEN) and future daily projections from 10 general circulation models (GCMs) to analyze the potential risks of extreme precipitation due to changes in the magnitude and frequency. We calculate the 10-year and 100-year return levels by fitting the partial duration series (PDS) data with the generalized Pareto (GP) distribution. The potential risks are quantified in two terms: by the ratio of the magnitude to the threshold and by the exceedance frequency comparing to the theoretical value. The results show that in the future, about 46% of the world may suffer from mid or high risk of change in extreme precipitation. Most regions show higher risk due to the increased frequency of extreme precipitation events under the RCP8.5 scenario. The high risk of humid regions mainly appears under the RCP8.5 scenario and is mainly driven by frequency change, while that of arid regions appears under both the scenarios and is driven by both the frequency and magnitude change. The tropical rainforest climate areas of South America (SA (N)), the tropical savanna or tropical wet monsoon and tropical dry areas of South Asia (SA), and the subarctic climate areas of Northern Asia (NOA) may suffer more risks from the view of both magnitude and frequency changes of extreme precipitation.
引用
收藏
页码:2059 / 2079
页数:21
相关论文
共 50 条
[1]  
Abbas K., 2012, EUR J SCI RES, V79, P418
[2]   Global projections of river flood risk in a warmer world [J].
Alfieri, Lorenzo ;
Bisselink, Berny ;
Dottori, Francesco ;
Naumann, Gustavo ;
de Roo, Ad ;
Salamon, Peter ;
Wyser, Klaus ;
Feyen, Luc .
EARTHS FUTURE, 2017, 5 (02) :171-182
[3]   Projection and uncertainty analysis of global precipitation-related extremes using CMIP5 models [J].
Chen, Huopo ;
Sun, Jianqi ;
Chen, Xiaoli .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2014, 34 (08) :2730-2748
[4]   Non-stationary extreme value analysis in a changing climate [J].
Cheng, Linyin ;
AghaKouchak, Amir ;
Gilleland, Eric ;
Katz, Richard W. .
CLIMATIC CHANGE, 2014, 127 (02) :353-369
[5]   Climate modelling: Severe summertime flooding in Europe [J].
Christensen, JH ;
Christensen, OB .
NATURE, 2003, 421 (6925) :805-806
[6]  
Chylek P., 2011, Atmos. Chem. Phys. Discuss, V11, P22893, DOI [10.5194/acpd-11-22893-2011, DOI 10.5194/ACPD-11-22893-2011]
[7]  
Coles, 2001, AN INTRO STAT MODELL
[8]   Rainfall Estimates on a Gridded Network (REGEN) - a global land-based gridded dataset of daily precipitation from 1950 to 2016 [J].
Contractor, Steefan ;
Donat, Markus G. ;
Alexander, Lisa, V ;
Ziese, Markus ;
Meyer-Christoffer, Anja ;
Schneider, Udo ;
Rustemeier, Elke ;
Becker, Andreas ;
Durre, Imke ;
Vose, Russell S. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2020, 24 (02) :919-943
[9]  
Dan'azumi Salisu, 2010, American Journal of Environmental Sciences, V6, P238, DOI 10.3844/ajessp.2010.238.243
[10]   Weak limits for exploratory plots in the analysis of extremes [J].
Das, Bikramjit ;
Ghosh, Souvik .
BERNOULLI, 2013, 19 (01) :308-343