Projected changes in wave climate from a multi-model ensemble

被引:0
|
作者
Hemer M.A. [1 ]
Fan Y. [2 ]
Mori N. [3 ]
Semedo A. [4 ,5 ]
Wang X.L. [6 ]
机构
[1] CSIRO Wealth from Oceans National Research Flagship, Centre of Australian Weather and Climate Research, CSIRO and the Bureau of Meteorology, GPO Box 1538, Hobart
[2] Princeton University/GFDL, Princeton
[3] Disaster Prevention Research Institute, Kyoto University
[4] Escola Naval, CINAV
[5] Department of Earth Sciences, Uppsala University
[6] Climate Research Division, Science and Technology Branch, Environment Canada, Toronto, ON
基金
日本学术振兴会;
关键词
D O I
10.1038/nclimate1791
中图分类号
学科分类号
摘要
Future changes in wind-wave climate have broad implications for the operation and design of coastal, near- and off-shore industries and ecosystems, and may further exacerbate the anticipated vulnerabilities of coastal regions to projected sea-level rise. However, wind waves have received little attention in global assessments of projected future climate change. We present results from the first community-derived multi-model ensemble of wave-climate projections. We find an agreed projected decrease in annual mean significant wave height (H S) over 25.8% of the global ocean area. The area of projected decrease is greater during boreal winter (January-March, mean; 38.5% of the global ocean area) than austral winter (July-September, mean; 8.4%). A projected increase in annual mean H S is found over 7.1% of the global ocean, predominantly in the Southern Ocean, which is greater during austral winter (July-September; 8.8%). Increased Southern Ocean wave activity influences a larger proportion of the global ocean as swell propagates northwards into the other ocean basins, observed as an increase in annual mean wave period (T M) over 30.2% of the global ocean and associated rotation of the annual mean wave direction (θ M). The multi-model ensemble is too limited to systematically sample total uncertainty associated with wave-climate projections. However, variance of wave-climate projections associated with study methodology dominates other sources of uncertainty (for example, climate scenario and model uncertainties). © 2013 Macmillan Publishers Limited. All rights reserved.
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页码:471 / 476
页数:5
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