Evaluating wind extremes in CMIP5 climate models

被引:78
作者
Kumar, Devashish [1 ]
Mishra, Vimal [1 ,2 ]
Ganguly, Auroop R. [1 ]
机构
[1] Northeastern Univ, Sustainabil & Data Sci Lab, Civil & Environm Engn, Boston, MA 02115 USA
[2] Indian Inst Technol, Civil Engn, Gandhinagar, India
基金
美国国家科学基金会;
关键词
CMIP5; models; Wind extremes; Gumbel distribution; Model evaluation; SOUTHERN-OCEAN; PERFORMANCE; SCENARIOS;
D O I
10.1007/s00382-014-2306-2
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Wind extremes have consequences for renewable energy sectors, critical infrastructures, coastal ecosystems, and insurance industry. Considerable debates remain regarding the impacts of climate change on wind extremes. While climate models have occasionally shown increases in regional wind extremes, a decline in the magnitude of mean and extreme near-surface wind speeds has been recently reported over most regions of the Northern Hemisphere using observed data. Previous studies of wind extremes under climate change have focused on selected regions and employed outputs from the regional climate models (RCMs). However, RCMs ultimately rely on the outputs of global circulation models (GCMs), and the value-addition from the former over the latter has been questioned. Regional model runs rarely employ the full suite of GCM ensembles, and hence may not be able to encapsulate the most likely projections or their variability. Here we evaluate the performance of the latest generation of GCMs, the Coupled Model Intercomparison Project phase 5 (CMIP5), in simulating extreme winds. We find that the multimodel ensemble (MME) mean captures the spatial variability of annual maximum wind speeds over most regions except over the mountainous terrains. However, the historical temporal trends in annual maximum wind speeds for the reanalysis data, ERA-Interim, are not well represented in the GCMs. The historical trends in extreme winds from GCMs are statistically not significant over most regions. The MME model simulates the spatial patterns of extreme winds for 25-100 year return periods. The projected extreme winds from GCMs exhibit statistically less significant trends compared to the historical reference period.
引用
收藏
页码:441 / 453
页数:13
相关论文
共 50 条
[1]   A comparison of methods of extreme wind speed estimation [J].
An, Y ;
Pandey, MD .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2005, 93 (07) :535-545
[2]   Extreme value analysis for estimating 50 year return wind speeds from reanalysis data [J].
Anastasiades, G. ;
McSharry, P. E. .
WIND ENERGY, 2014, 17 (08) :1231-1245
[3]  
Barros V, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, pIX
[4]   The catastrophic effects of natural disasters on insurance markets [J].
Born, Patricia ;
Viscusi, W. Kip .
JOURNAL OF RISK AND UNCERTAINTY, 2006, 33 (1-2) :55-72
[5]   Assessment of surface winds over the Atlantic, Indian, and Pacific Ocean sectors of the Southern Ocean in CMIP5 models: historical bias, forcing response, and state dependence [J].
Bracegirdle, Thomas J. ;
Shuckburgh, Emily ;
Sallee, Jean-Baptiste ;
Wang, Zhaomin ;
Meijers, Andrew J. S. ;
Bruneau, Nicolas ;
Phillips, Tony ;
Wilcox, Laura J. .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2013, 118 (02) :547-562
[6]  
Coles S. G., 2001, SPRINGER SERIES STAT, DOI DOI 10.1007/978-1-4471-3675-0
[7]   Consolidation of analysis methods for sub-annual extreme wind speeds [J].
Cook, Nicholas J. .
METEOROLOGICAL APPLICATIONS, 2014, 21 (02) :403-414
[8]   Rebuttal of "Problems in the extreme value analysis" [J].
Cook, Nicholas J. .
STRUCTURAL SAFETY, 2012, 34 (01) :418-423
[9]  
COOK NJ, 1982, J WIND ENG IND AEROD, V9, P295, DOI 10.1016/0167-6105(82)90021-6
[10]   A decade of weather extremes [J].
Coumou, Dim ;
Rahmstorf, Stefan .
NATURE CLIMATE CHANGE, 2012, 2 (07) :491-496