Quantifying flood risk of extreme events using density forecasts based on a new digital archive and weather ensemble predictions

被引:2
作者
McSharry, Patrick E. [1 ]
Little, Max A. [2 ]
Rodda, Harvey J. E. [3 ]
Rodda, John [3 ]
机构
[1] Univ Oxford, Smith Sch Enterprise & Environm, Oxford OX1 2BQ, England
[2] MIT, Media Lab, Cambridge, MA 02139 USA
[3] HydroGIS, Southampton, Hants, England
关键词
daily rainfalls; precipitation; risk analysis; risk management; forecasting; extremes; climate change; climate variability; RAINFALL EVENTS; TRENDS;
D O I
10.1002/qj.2136
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Non-coastal flood events in the UK are usually associated with extreme rainfall and can last from minutes to weeks. Efficient management and mitigation of flood risk requires accurate and reliable precipitation forecasts as inputs to flood risk models. We constructed an archive of British Rainfall data from 1866 to the present day to improve our understanding of historical extreme rainfall events. The relationship between record rainfall and flooding is nonlinear and uncertain, implying that probabilistic forecasts of rainfall are required. We developed an objective classification scheme of extreme rainfall events consisting of eight types, analysed extreme rainfall events and produced probabilistic forecasts by combining statistical techniques with the outputs of ensemble predictions from a numerical weather predictions model. Copyright (c) 2010 Royal Meteorological Society
引用
收藏
页码:328 / 333
页数:6
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