Large-Scale Drivers and Seasonal Predictability of Extreme Wind Speeds Over the North Atlantic and Europe
As extreme wind speeds are responsible for large socioeconomic losses in the European domain, a skillful prediction would be of great benefit for disaster prevention as well as the actuarial community. Here we evaluate the patterns of atmospheric variability and the seasonal predictability of extrem...
Published in: | Journal of Geophysical Research: Atmospheres |
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American Geophysical Union (AGU)
2018
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Online Access: | http://hdl.handle.net/1959.4/unsworks_55027 https://unsworks.unsw.edu.au/bitstreams/bac3e0d8-3dd2-4e71-aae9-e7c6db6a3351/download https://doi.org/10.1029/2017JD027958 |
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ftunswworks:oai:unsworks.library.unsw.edu.au:1959.4/unsworks_55027 2024-05-19T07:44:55+00:00 Large-Scale Drivers and Seasonal Predictability of Extreme Wind Speeds Over the North Atlantic and Europe Walz, MA Donat, MG Leckebusch, GC 2018-10-27 application/pdf http://hdl.handle.net/1959.4/unsworks_55027 https://unsworks.unsw.edu.au/bitstreams/bac3e0d8-3dd2-4e71-aae9-e7c6db6a3351/download https://doi.org/10.1029/2017JD027958 unknown American Geophysical Union (AGU) http://purl.org/au-research/grants/arc/DE150100456 http://hdl.handle.net/1959.4/unsworks_55027 https://unsworks.unsw.edu.au/bitstreams/bac3e0d8-3dd2-4e71-aae9-e7c6db6a3351/download https://doi.org/10.1029/2017JD027958 open access https://purl.org/coar/access_right/c_abf2 CC-BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/ free_to_read urn:ISSN:2169-897X urn:ISSN:2169-8996 Journal of Geophysical Research: Atmospheres, 123, 20, 11-535 13 Climate Action anzsrc-for: 0401 Atmospheric Sciences anzsrc-for: 0406 Physical Geography and Environmental Geoscience journal article http://purl.org/coar/resource_type/c_6501 2018 ftunswworks https://doi.org/10.1029/2017JD027958 2024-04-24T00:28:52Z As extreme wind speeds are responsible for large socioeconomic losses in the European domain, a skillful prediction would be of great benefit for disaster prevention as well as the actuarial community. Here we evaluate the patterns of atmospheric variability and the seasonal predictability of extreme wind speeds (e.g., >95th percentile) in the European domain in the dynamical seasonal forecast system European Centre for Medium-Range Weather Forecasts (ECMWF) System 4 and compare to the predictability using a statistical prediction model. Further we compare the seasonal forecast system with ECMWF Re-Analysis (ERA)-Interim in order to advance the understanding of the large-scale conditions that generate extreme winds. The dominant mean sea level pressure patterns of atmospheric variability show distinct differences between reanalysis and System 4 as most patterns in System 4 are extended downstream in comparison to ERA-Interim. This dissimilar manifestation of the patterns across the two models leads to substantially different drivers associated with the generation of extreme winds: While the prominent pattern of the North Atlantic Oscillation could be identified as the main driver in the reanalysis, extreme winds in System 4 appear to be related to different large-scale atmospheric pressure patterns. Thus, our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world. This circumstance is likely related to the unrealistic representation of the atmospheric patterns driving these extreme winds. Hence, our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric variability. Article in Journal/Newspaper North Atlantic North Atlantic oscillation UNSW Sydney (The University of New South Wales): UNSWorks Journal of Geophysical Research: Atmospheres 123 20 |
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UNSW Sydney (The University of New South Wales): UNSWorks |
op_collection_id |
ftunswworks |
language |
unknown |
topic |
13 Climate Action anzsrc-for: 0401 Atmospheric Sciences anzsrc-for: 0406 Physical Geography and Environmental Geoscience |
spellingShingle |
13 Climate Action anzsrc-for: 0401 Atmospheric Sciences anzsrc-for: 0406 Physical Geography and Environmental Geoscience Walz, MA Donat, MG Leckebusch, GC Large-Scale Drivers and Seasonal Predictability of Extreme Wind Speeds Over the North Atlantic and Europe |
topic_facet |
13 Climate Action anzsrc-for: 0401 Atmospheric Sciences anzsrc-for: 0406 Physical Geography and Environmental Geoscience |
description |
As extreme wind speeds are responsible for large socioeconomic losses in the European domain, a skillful prediction would be of great benefit for disaster prevention as well as the actuarial community. Here we evaluate the patterns of atmospheric variability and the seasonal predictability of extreme wind speeds (e.g., >95th percentile) in the European domain in the dynamical seasonal forecast system European Centre for Medium-Range Weather Forecasts (ECMWF) System 4 and compare to the predictability using a statistical prediction model. Further we compare the seasonal forecast system with ECMWF Re-Analysis (ERA)-Interim in order to advance the understanding of the large-scale conditions that generate extreme winds. The dominant mean sea level pressure patterns of atmospheric variability show distinct differences between reanalysis and System 4 as most patterns in System 4 are extended downstream in comparison to ERA-Interim. This dissimilar manifestation of the patterns across the two models leads to substantially different drivers associated with the generation of extreme winds: While the prominent pattern of the North Atlantic Oscillation could be identified as the main driver in the reanalysis, extreme winds in System 4 appear to be related to different large-scale atmospheric pressure patterns. Thus, our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world. This circumstance is likely related to the unrealistic representation of the atmospheric patterns driving these extreme winds. Hence, our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric variability. |
format |
Article in Journal/Newspaper |
author |
Walz, MA Donat, MG Leckebusch, GC |
author_facet |
Walz, MA Donat, MG Leckebusch, GC |
author_sort |
Walz, MA |
title |
Large-Scale Drivers and Seasonal Predictability of Extreme Wind Speeds Over the North Atlantic and Europe |
title_short |
Large-Scale Drivers and Seasonal Predictability of Extreme Wind Speeds Over the North Atlantic and Europe |
title_full |
Large-Scale Drivers and Seasonal Predictability of Extreme Wind Speeds Over the North Atlantic and Europe |
title_fullStr |
Large-Scale Drivers and Seasonal Predictability of Extreme Wind Speeds Over the North Atlantic and Europe |
title_full_unstemmed |
Large-Scale Drivers and Seasonal Predictability of Extreme Wind Speeds Over the North Atlantic and Europe |
title_sort |
large-scale drivers and seasonal predictability of extreme wind speeds over the north atlantic and europe |
publisher |
American Geophysical Union (AGU) |
publishDate |
2018 |
url |
http://hdl.handle.net/1959.4/unsworks_55027 https://unsworks.unsw.edu.au/bitstreams/bac3e0d8-3dd2-4e71-aae9-e7c6db6a3351/download https://doi.org/10.1029/2017JD027958 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
urn:ISSN:2169-897X urn:ISSN:2169-8996 Journal of Geophysical Research: Atmospheres, 123, 20, 11-535 |
op_relation |
http://purl.org/au-research/grants/arc/DE150100456 http://hdl.handle.net/1959.4/unsworks_55027 https://unsworks.unsw.edu.au/bitstreams/bac3e0d8-3dd2-4e71-aae9-e7c6db6a3351/download https://doi.org/10.1029/2017JD027958 |
op_rights |
open access https://purl.org/coar/access_right/c_abf2 CC-BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/ free_to_read |
op_doi |
https://doi.org/10.1029/2017JD027958 |
container_title |
Journal of Geophysical Research: Atmospheres |
container_volume |
123 |
container_issue |
20 |
_version_ |
1799484809619177472 |