Weather regime dependence of extreme value statistics for summer temperature and precipitation
Extreme Value Theory (EVT) is a useful tool to describe the statistical properties of extreme events. Its underlying assumptions include some form of temporal stationarity in the data. Previous studies have been able to treat long-term trends in datasets, to obtain the time dependence of EVT paramet...
Published in: | Nonlinear Processes in Geophysics |
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00031563 2023-05-15T17:29:53+02:00 Weather regime dependence of extreme value statistics for summer temperature and precipitation Yiou, P. Goubanova, K. Li, Z. X. Nogaj, M. 2008-05 electronic https://doi.org/10.5194/npg-15-365-2008 https://noa.gwlb.de/receive/cop_mods_00031563 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00031517/npg-15-365-2008.pdf https://npg.copernicus.org/articles/15/365/2008/npg-15-365-2008.pdf eng eng Copernicus Publications Nonlinear Processes in Geophysics -- http://www.bibliothek.uni-regensburg.de/ezeit/?2078085 -- http://www.nonlin-processes-geophys.net/ -- http://www.copernicus.org/EGU/npg/npg.htm -- 1607-7946 https://doi.org/10.5194/npg-15-365-2008 https://noa.gwlb.de/receive/cop_mods_00031563 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00031517/npg-15-365-2008.pdf https://npg.copernicus.org/articles/15/365/2008/npg-15-365-2008.pdf https://open-access.net/ uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2008 ftnonlinearchiv https://doi.org/10.5194/npg-15-365-2008 2022-02-08T22:46:40Z Extreme Value Theory (EVT) is a useful tool to describe the statistical properties of extreme events. Its underlying assumptions include some form of temporal stationarity in the data. Previous studies have been able to treat long-term trends in datasets, to obtain the time dependence of EVT parameters in a parametric form. Since there is also a dependence of surface temperature and precipitation to weather patterns obtained from pressure data, we determine the EVT parameters of those meteorological variables over France conditional to the occurrence of North Atlantic weather patterns in the summer. We use a clustering algorithm on geopotential height data over the North Atlantic to obtain those patterns. This approach refines the straightforward application of EVT on climate data by allowing us to assess the role of atmospheric variability on temperature and precipitation extreme parameters. This study also investigates the statistical robustness of this relation. Our results show how weather regimes can modulate the different behavior of mean climate variables and their extremes. Such a modulation can be very different for the mean and extreme precipitation. Article in Journal/Newspaper North Atlantic Niedersächsisches Online-Archiv NOA Nonlinear Processes in Geophysics 15 3 365 378 |
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article Verlagsveröffentlichung Yiou, P. Goubanova, K. Li, Z. X. Nogaj, M. Weather regime dependence of extreme value statistics for summer temperature and precipitation |
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article Verlagsveröffentlichung |
description |
Extreme Value Theory (EVT) is a useful tool to describe the statistical properties of extreme events. Its underlying assumptions include some form of temporal stationarity in the data. Previous studies have been able to treat long-term trends in datasets, to obtain the time dependence of EVT parameters in a parametric form. Since there is also a dependence of surface temperature and precipitation to weather patterns obtained from pressure data, we determine the EVT parameters of those meteorological variables over France conditional to the occurrence of North Atlantic weather patterns in the summer. We use a clustering algorithm on geopotential height data over the North Atlantic to obtain those patterns. This approach refines the straightforward application of EVT on climate data by allowing us to assess the role of atmospheric variability on temperature and precipitation extreme parameters. This study also investigates the statistical robustness of this relation. Our results show how weather regimes can modulate the different behavior of mean climate variables and their extremes. Such a modulation can be very different for the mean and extreme precipitation. |
format |
Article in Journal/Newspaper |
author |
Yiou, P. Goubanova, K. Li, Z. X. Nogaj, M. |
author_facet |
Yiou, P. Goubanova, K. Li, Z. X. Nogaj, M. |
author_sort |
Yiou, P. |
title |
Weather regime dependence of extreme value statistics for summer temperature and precipitation |
title_short |
Weather regime dependence of extreme value statistics for summer temperature and precipitation |
title_full |
Weather regime dependence of extreme value statistics for summer temperature and precipitation |
title_fullStr |
Weather regime dependence of extreme value statistics for summer temperature and precipitation |
title_full_unstemmed |
Weather regime dependence of extreme value statistics for summer temperature and precipitation |
title_sort |
weather regime dependence of extreme value statistics for summer temperature and precipitation |
publisher |
Copernicus Publications |
publishDate |
2008 |
url |
https://doi.org/10.5194/npg-15-365-2008 https://noa.gwlb.de/receive/cop_mods_00031563 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00031517/npg-15-365-2008.pdf https://npg.copernicus.org/articles/15/365/2008/npg-15-365-2008.pdf |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
Nonlinear Processes in Geophysics -- http://www.bibliothek.uni-regensburg.de/ezeit/?2078085 -- http://www.nonlin-processes-geophys.net/ -- http://www.copernicus.org/EGU/npg/npg.htm -- 1607-7946 https://doi.org/10.5194/npg-15-365-2008 https://noa.gwlb.de/receive/cop_mods_00031563 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00031517/npg-15-365-2008.pdf https://npg.copernicus.org/articles/15/365/2008/npg-15-365-2008.pdf |
op_rights |
https://open-access.net/ uneingeschränkt info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/npg-15-365-2008 |
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Nonlinear Processes in Geophysics |
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15 |
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3 |
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365 |
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378 |
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1766125115667382272 |