Open AccessUse of probabilistic medium‐ to long‐range weather‐pattern forecasts for identifying periods with an increased likelihood of coastal flooding around the UK
Author(s) -
Neal Robert,
Dankers Rutger,
Saulter Andrew,
Lane Andrew,
Millard Jonathan,
Robbins Gavin,
Price David
Publication year - 2018
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.1719
Subject(s) - hindcast , coastal flood , environmental science , climatology , flooding (psychology) , range (aeronautics) , meteorology , anomaly (physics) , preparedness , scale (ratio) , flood myth , weather patterns , submarine pipeline , geography , climate change , oceanography , cartography , geology , sea level rise , psychology , materials science , physics , archaeology , condensed matter physics , political science , law , composite material , psychotherapist
A medium‐ to long‐range forecast highlighting periods with an increased likelihood of coastal flooding is useful to United Kingdom governments and response agencies when considering proactive, large‐scale and multiregional responses. For this purpose, a new operational forecasting tool called Coastal Decider was developed for use by the Flood Forecasting Centre (FFC). Coastal Decider is used for internal preparedness within the FFC and provides the likelihood of coastal flooding around the UK, which is associated with the occurrence of specific predefined weather patterns in combination with high astronomical tides. Forecasts are available for medium‐range and monthly time‐scales using output from several ensemble prediction systems, whereby ensemble members are objectively assigned to the closest matching weather pattern definition. Ensemble members already clustered by weather pattern are then grouped to provide objective probabilities of a broader cluster of coastal‐risk weather patterns occurring. The coastal‐risk weather patterns were objectively derived for 21 coastal sites by relating daily historical weather pattern classifications to a wave hindcast, using a Met Office configuration of WAVEWATCH III, as well as observed skew surges, derived using tide‐gauge data from the British Oceanographic Data Centre (BODC). Finally, metrics based on the pressure‐anomaly difference between ensemble members and their assigned weather patterns, alongside forecasts of daily maximum 10 m wind speed are used to estimate the magnitude of coastal flooding.