Modelling the spatial extent and severity of extreme European windstorms
Windstorms are a primary natural hazard affecting Europe that are commonly linked to substantial property and infrastructural damage and are responsible for the largest spatially aggregated financial losses. Such extreme winds are typically generated by extratropical cyclone systems originating in t...
Published in: | Journal of the Royal Statistical Society: Series C (Applied Statistics) |
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ftulancaster:oai:eprints.lancs.ac.uk:138304 2023-08-27T04:10:55+02:00 Modelling the spatial extent and severity of extreme European windstorms Sharkey, Paul Tawn, Jonathan Brown, Simon 2020-04-01 text https://eprints.lancs.ac.uk/id/eprint/138304/ https://eprints.lancs.ac.uk/id/eprint/138304/1/Modelling_the_spatial_extent_and_severity_of_extreme_European_windstorms_Oct19.pdf https://doi.org/10.1111/rssc.12391 en eng https://eprints.lancs.ac.uk/id/eprint/138304/1/Modelling_the_spatial_extent_and_severity_of_extreme_European_windstorms_Oct19.pdf Sharkey, Paul and Tawn, Jonathan and Brown, Simon (2020) Modelling the spatial extent and severity of extreme European windstorms. Journal of the Royal Statistical Society: Series C (Applied Statistics), 69 (2). pp. 223-250. ISSN 0035-9254 creative_commons_attribution_noncommercial_4_0_international_license Journal Article PeerReviewed 2020 ftulancaster https://doi.org/10.1111/rssc.12391 2023-08-03T22:37:02Z Windstorms are a primary natural hazard affecting Europe that are commonly linked to substantial property and infrastructural damage and are responsible for the largest spatially aggregated financial losses. Such extreme winds are typically generated by extratropical cyclone systems originating in the North Atlantic and passing over Europe. Previous statistical studies tend to model extreme winds at a given set of sites, corresponding to inference in an Eulerian framework. Such inference cannot incorporate knowledge of the life cycle and progression of extratropical cyclones across the region and is forced to make restrictive assumptions about the extremal dependence structure. We take an entirely different approach which overcomes these limitations by working in a Lagrangian framework. Specifically, we model the development of windstorms over time, preserving the physical characteristics linking the windstorm and the cyclone track, the path of local vorticity maxima, and make a key finding that the spatial extent of extratropical windstorms becomes more localized as its magnitude increases irrespective of the location of the storm track. Our model allows simulation of synthetic windstorm events to derive the joint distributional features over any set of sites giving physically consistent extrapolations to rarer events. From such simulations improved estimates of this hazard can be achieved in terms of both intensity and area affected. Article in Journal/Newspaper North Atlantic Lancaster University: Lancaster Eprints Journal of the Royal Statistical Society: Series C (Applied Statistics) 69 2 223 250 |
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Lancaster University: Lancaster Eprints |
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English |
description |
Windstorms are a primary natural hazard affecting Europe that are commonly linked to substantial property and infrastructural damage and are responsible for the largest spatially aggregated financial losses. Such extreme winds are typically generated by extratropical cyclone systems originating in the North Atlantic and passing over Europe. Previous statistical studies tend to model extreme winds at a given set of sites, corresponding to inference in an Eulerian framework. Such inference cannot incorporate knowledge of the life cycle and progression of extratropical cyclones across the region and is forced to make restrictive assumptions about the extremal dependence structure. We take an entirely different approach which overcomes these limitations by working in a Lagrangian framework. Specifically, we model the development of windstorms over time, preserving the physical characteristics linking the windstorm and the cyclone track, the path of local vorticity maxima, and make a key finding that the spatial extent of extratropical windstorms becomes more localized as its magnitude increases irrespective of the location of the storm track. Our model allows simulation of synthetic windstorm events to derive the joint distributional features over any set of sites giving physically consistent extrapolations to rarer events. From such simulations improved estimates of this hazard can be achieved in terms of both intensity and area affected. |
format |
Article in Journal/Newspaper |
author |
Sharkey, Paul Tawn, Jonathan Brown, Simon |
spellingShingle |
Sharkey, Paul Tawn, Jonathan Brown, Simon Modelling the spatial extent and severity of extreme European windstorms |
author_facet |
Sharkey, Paul Tawn, Jonathan Brown, Simon |
author_sort |
Sharkey, Paul |
title |
Modelling the spatial extent and severity of extreme European windstorms |
title_short |
Modelling the spatial extent and severity of extreme European windstorms |
title_full |
Modelling the spatial extent and severity of extreme European windstorms |
title_fullStr |
Modelling the spatial extent and severity of extreme European windstorms |
title_full_unstemmed |
Modelling the spatial extent and severity of extreme European windstorms |
title_sort |
modelling the spatial extent and severity of extreme european windstorms |
publishDate |
2020 |
url |
https://eprints.lancs.ac.uk/id/eprint/138304/ https://eprints.lancs.ac.uk/id/eprint/138304/1/Modelling_the_spatial_extent_and_severity_of_extreme_European_windstorms_Oct19.pdf https://doi.org/10.1111/rssc.12391 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
https://eprints.lancs.ac.uk/id/eprint/138304/1/Modelling_the_spatial_extent_and_severity_of_extreme_European_windstorms_Oct19.pdf Sharkey, Paul and Tawn, Jonathan and Brown, Simon (2020) Modelling the spatial extent and severity of extreme European windstorms. Journal of the Royal Statistical Society: Series C (Applied Statistics), 69 (2). pp. 223-250. ISSN 0035-9254 |
op_rights |
creative_commons_attribution_noncommercial_4_0_international_license |
op_doi |
https://doi.org/10.1111/rssc.12391 |
container_title |
Journal of the Royal Statistical Society: Series C (Applied Statistics) |
container_volume |
69 |
container_issue |
2 |
container_start_page |
223 |
op_container_end_page |
250 |
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1775353304440635392 |