Climate change change impact on precipitation extremes over Indian cities: Non-stationary analysis

被引:30
作者
Goyal, Manish Kumar [1 ]
Gupta, Anil Kumar [2 ]
Jha, Srinidhi [1 ]
Rakkasagi, Shivukumar [1 ]
Jain, Vijay [1 ]
机构
[1] Indian Inst Technol Indore, Discipline Civil Engn, Indore, India
[2] Natl Inst Disaster Management, New Delhi, India
关键词
Extreme events; Precipitation; Nonstationary; Return level; Indian cities; FLOOD FREQUENCY-ANALYSIS; MONSOON RAINFALL; RIVER-BASIN; STATIONARITY; VARIABILITY; DEAD;
D O I
10.1016/j.techfore.2022.121685
中图分类号
F [经济];
学科分类号
02 ;
摘要
The phenomena of climate change and increase in warming conditions across the globe causes changes in the frequency and severity of extreme weather events. The present study analyzed extreme precipitation weather events across four Indian cities in different climatic conditions. The study uses IMD precipitation datasets from 1900 to 2004 to analyze different atmospheric influencing parameters like ENSO, AMO, and IOD on future extreme precipitation conditions. The Bayesian analysis is carried out for nonstationary analysis of extreme indices like Rx1 Day, SDII, R10, and CWD with a 10, 20, 50, and 100 years return period. Significant outcomes of the comparative study of the stationary and nonstationary analysis showed an intensification in extreme precipitation across Indian cities for all return periods using the CWD indicator. The remaining three indicators of the nonstationary study suggested intensifying extreme rainfall across all Indian cities except Guwahati.
引用
收藏
页数:7
相关论文
共 56 条
[1]   Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis [J].
Adarsh, S. ;
Reddy, M. Janga .
METEOROLOGY AND ATMOSPHERIC PHYSICS, 2018, 130 (06) :667-688
[2]   ENSO-Monsoon relationships in a greenhouse warming scenario [J].
Ashrit, RG ;
Kumar, KR ;
Kumar, KK .
GEOPHYSICAL RESEARCH LETTERS, 2001, 28 (09) :1727-1730
[3]  
Behera S., 2013, OCEAN CIRCULATION CL
[4]  
Benfield A, 2016, annual global climate and catastrophe report
[5]   A Bayesian Hierarchical Approach to Multivariate Nonstationary Hydrologic Frequency Analysis [J].
Bracken, C. ;
Holman, K. D. ;
Rajagopalan, B. ;
Moradkhani, H. .
WATER RESOURCES RESEARCH, 2018, 54 (01) :243-255
[6]   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
[7]   A fully probabilistic approach to extreme rainfall modeling [J].
Coles, S ;
Pericchi, LR ;
Sisson, S .
JOURNAL OF HYDROLOGY, 2003, 273 (1-4) :35-50
[8]  
Cooley D., 2013, EXTREMES CHANGING CL, P97
[9]   Extreme value analysis and the study of climate change [J].
Cooley, Daniel .
CLIMATIC CHANGE, 2009, 97 (1-2) :77-83
[10]   Global increase in record-breaking monthly-mean temperatures [J].
Coumou, Dim ;
Robinson, Alexander ;
Rahmstorf, Stefan .
CLIMATIC CHANGE, 2013, 118 (3-4) :771-782