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Atmospheric river orientation determines flood occurrence
Author(s) -
Griffith Helen V.,
Wade Andrew J.,
Lavers David A.,
Watts Glenn
Publication year - 2020
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.13905
Subject(s) - flood myth , environmental science , orographic lift , hydrology (agriculture) , drainage basin , climatology , scale (ratio) , flux (metallurgy) , meteorology , geology , precipitation , geography , cartography , geotechnical engineering , archaeology , materials science , metallurgy
Atmospheric Rivers (ARs) have been linked to many of the largest recorded UK winter floods. These large‐scale features can be 500–800 km in width but produce markedly different flood responses in adjacent catchments. Here we combine meteorological and hydrological data to examine why two impermeable catchments on the west coast of Britain respond differently to landfalling ARs. This is important to help better understand flood generation associated with ARs and improve flood forecasting and climate‐change impact assessment. Analysis of 32 years of a newly available ERA5 high‐resolution atmospheric reanalysis and corresponding 15‐min river flow data show that the most impactful ARs arise through a combination of the orientation and magnitude of their water vapour flux. At the Dyfi catchment, AR orientations of between 238–258° result in the strongest hydrological responses, whereas at the Teifi the range is 224–243°. We believe this differential flood response is the result of catchment orientation and topography enhancing or suppressing orographic rainfall totals, even in relatively low‐relief coastal catchments. Further to the AR orientation, ARs must have an average water vapour flux of 400–450 kg m −1 s −1 across their lifetime. Understanding the preferential properties of impactful ARs at catchments allows for the linking of large‐scale synoptic features, such as ARs, directly to winter flood impacts. These results using two test catchments suggest a novel approach to flood forecasts through the inclusion of AR activity.