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Identifying the origins of extreme rainfall using storm track classification

Barnes, Andrew Paul; Santos, Marcus Suassuna; Garijo, Carlos; Mediero, Luis; Prosdocimi, Ilaria; McCullen, Nick; Kjeldsen, Thomas Rodding

Authors

Andrew Paul Barnes

Marcus Suassuna Santos

Carlos Garijo

Luis Mediero

Ilaria Prosdocimi

Nick McCullen

Thomas Rodding Kjeldsen



Abstract

Identifying patterns in data relating to extreme rainfall is important for classifying and estimating rainfall and flood frequency distributions routinely used in civil engineering design and flood management. This study demonstrates the novel use of several self-organising map (SOM) models to extract the key moisture pathways for extreme rainfall events applied to example data in northern Spain. These models are trained using various subsets of a backwards trajectory data set generated for extreme rainfall events between 1967 and 2016. The results of our analysis show 69.2% of summer rainfall extremes rely on recirculatory moisture pathways concentrated on the Iberian Peninsula, whereas 57% of winter extremes rely on deep-Atlantic pathways to bring moisture from the ocean. These moisture pathways have also shown differences in rainfall magnitude, such as in the summer where peninsular pathways are 8% more likely to deliver the higher magnitude extremes than their Atlantic counterparts.

Citation

Barnes, A. P., Santos, M. S., Garijo, C., Mediero, L., Prosdocimi, I., McCullen, N., & Kjeldsen, T. R. (2020). Identifying the origins of extreme rainfall using storm track classification. Journal of Hydroinformatics, 22(2), 296-309. https://doi.org/10.2166/hydro.2019.164

Journal Article Type Article
Acceptance Date Oct 7, 2019
Online Publication Date Oct 23, 2019
Publication Date Mar 1, 2020
Deposit Date Apr 12, 2022
Journal Journal of Hydroinformatics
Print ISSN 1464-7141
Electronic ISSN 1465-1734
Publisher IWA Publishing
Peer Reviewed Peer Reviewed
Volume 22
Issue 2
Pages 296-309
DOI https://doi.org/10.2166/hydro.2019.164
Keywords Atmospheric Science; Geotechnical Engineering and Engineering Geology; Civil and Structural Engineering; Water Science and Technology
Public URL https://uwe-repository.worktribe.com/output/9319908