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Quantifying flood risk of extreme events using density forecasts based on a new digital archive and weather ensemble predictions
Author(s) -
McSharry Patrick E.,
Little Max A.,
Rodda Harvey J. E.,
Rodda John
Publication year - 2013
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.2136
Subject(s) - flood myth , climatology , flooding (psychology) , environmental science , probabilistic logic , precipitation , meteorology , extreme weather , geography , statistics , climate change , geology , mathematics , psychology , oceanography , archaeology , psychotherapist
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 © 2010 Royal Meteorological Society