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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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 |
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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 |
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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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38 |
container_issue |
7 |
container_start_page |
3044 |
op_container_end_page |
3057 |
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1766133642147397632 |