Modelling serial clustering and inter‐annual variability of European winter windstorms based on large‐scale drivers

Winter windstorms are known to be among the most dangerous and loss intensive natural hazards in Europe. In order to gain a better understanding of their variability and driving mechanisms, this study analyses the temporal variability which is often referred to as serial or seasonal clustering. This...

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Published in:International Journal of Climatology
Main Authors: Walz, Michael A., Befort, Daniel J., Kirchner‐Bossi, Nicolas Otto, Ulbrich, Uwe, Leckebusch, Gregor C.
Format: Text
Language:English
Published: John Wiley & Sons, Ltd. 2018
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6473506/
https://doi.org/10.1002/joc.5481
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spelling ftpubmed:oai:pubmedcentral.nih.gov:6473506 2023-05-15T17:34:43+02:00 Modelling serial clustering and inter‐annual variability of European winter windstorms based on large‐scale drivers Walz, Michael A. Befort, Daniel J. Kirchner‐Bossi, Nicolas Otto Ulbrich, Uwe Leckebusch, Gregor C. 2018-03-23 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6473506/ https://doi.org/10.1002/joc.5481 en eng John Wiley & Sons, Ltd. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6473506/ http://dx.doi.org/10.1002/joc.5481 © 2018 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. CC-BY Research Articles Text 2018 ftpubmed https://doi.org/10.1002/joc.5481 2019-04-28T00:25:04Z Winter windstorms are known to be among the most dangerous and loss intensive natural hazards in Europe. In order to gain a better understanding of their variability and driving mechanisms, this study analyses the temporal variability which is often referred to as serial or seasonal clustering. This is realized by developing a statistical model relating the winter storm counts to known teleconnection patterns affecting European weather and climate conditions (e.g., North Atlantic Oscillation [NAO], Scandinavian pattern [SCA], etc.). The statistical model is developed via a stepwise Poisson regression approach that is applied to windstorm counts and large‐scale indices retrieved from the ERA‐20C reanalysis. Significant large‐scale drivers accountable for the inter‐annual variability of storms for several European regions are identified and compared. In addition to the SCA and the NAO which are found to be the essential drivers for most areas within the European domain, other teleconnections (e.g., East Atlantic pattern) are found to be more significant for the inter‐annual variability in certain regions. Furthermore, the statistical model allows an estimation of the expected number of storms per winter season and also whether a season has the characteristic of being what we define an active or inactive season. The statistical model reveals high skill particularly over British Isles and central Europe; however, even for regions with less frequent storm events (e.g., southern and eastern Europe) the model shows adequate positive skill. This feature could be of specific interest for the actuarial sector. Text North Atlantic North Atlantic oscillation PubMed Central (PMC) International Journal of Climatology 38 7 3044 3057
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Research Articles
spellingShingle Research Articles
Walz, Michael A.
Befort, Daniel J.
Kirchner‐Bossi, Nicolas Otto
Ulbrich, Uwe
Leckebusch, Gregor C.
Modelling serial clustering and inter‐annual variability of European winter windstorms based on large‐scale drivers
topic_facet Research Articles
description Winter windstorms are known to be among the most dangerous and loss intensive natural hazards in Europe. In order to gain a better understanding of their variability and driving mechanisms, this study analyses the temporal variability which is often referred to as serial or seasonal clustering. This is realized by developing a statistical model relating the winter storm counts to known teleconnection patterns affecting European weather and climate conditions (e.g., North Atlantic Oscillation [NAO], Scandinavian pattern [SCA], etc.). The statistical model is developed via a stepwise Poisson regression approach that is applied to windstorm counts and large‐scale indices retrieved from the ERA‐20C reanalysis. Significant large‐scale drivers accountable for the inter‐annual variability of storms for several European regions are identified and compared. In addition to the SCA and the NAO which are found to be the essential drivers for most areas within the European domain, other teleconnections (e.g., East Atlantic pattern) are found to be more significant for the inter‐annual variability in certain regions. Furthermore, the statistical model allows an estimation of the expected number of storms per winter season and also whether a season has the characteristic of being what we define an active or inactive season. The statistical model reveals high skill particularly over British Isles and central Europe; however, even for regions with less frequent storm events (e.g., southern and eastern Europe) the model shows adequate positive skill. This feature could be of specific interest for the actuarial sector.
format Text
author Walz, Michael A.
Befort, Daniel J.
Kirchner‐Bossi, Nicolas Otto
Ulbrich, Uwe
Leckebusch, Gregor C.
author_facet Walz, Michael A.
Befort, Daniel J.
Kirchner‐Bossi, Nicolas Otto
Ulbrich, Uwe
Leckebusch, Gregor C.
author_sort Walz, Michael A.
title Modelling serial clustering and inter‐annual variability of European winter windstorms based on large‐scale drivers
title_short Modelling serial clustering and inter‐annual variability of European winter windstorms based on large‐scale drivers
title_full Modelling serial clustering and inter‐annual variability of European winter windstorms based on large‐scale drivers
title_fullStr Modelling serial clustering and inter‐annual variability of European winter windstorms based on large‐scale drivers
title_full_unstemmed Modelling serial clustering and inter‐annual variability of European winter windstorms based on large‐scale drivers
title_sort modelling serial clustering and inter‐annual variability of european winter windstorms based on large‐scale drivers
publisher John Wiley & Sons, Ltd.
publishDate 2018
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6473506/
https://doi.org/10.1002/joc.5481
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6473506/
http://dx.doi.org/10.1002/joc.5481
op_rights © 2018 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.
This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
op_rightsnorm CC-BY
op_doi https://doi.org/10.1002/joc.5481
container_title International Journal of Climatology
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container_issue 7
container_start_page 3044
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