Dynamical proxies of North Atlantic predictability and extremes
International audience Atmospheric flows are characterized by chaotic dynamics and recurring large-scale patterns . These two characteristics point to the existence of an atmospheric attractor defined by Lorenz as: ``the collection of all states that the system can assume or approach again and again...
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ftunivnantes:oai:HAL:hal-01340301v1 2023-05-15T17:34:26+02:00 Dynamical proxies of North Atlantic predictability and extremes Faranda, Davide Messori, Gabriele Yiou, Pascal Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Department of Meteorology Stockholm (MISU) Stockholm University Bolin Centre for Climate Research ERC grant No 338965-A2C2 2017 https://hal.science/hal-01340301 https://hal.science/hal-01340301/document https://hal.science/hal-01340301/file/ExtremeDim_SR.pdf https://hal.science/hal-01340301/file/ExtendedData.pdf https://doi.org/10.1038/srep41278 en eng HAL CCSD Nature Publishing Group info:eu-repo/semantics/altIdentifier/doi/10.1038/srep41278 hal-01340301 https://hal.science/hal-01340301 https://hal.science/hal-01340301/document https://hal.science/hal-01340301/file/ExtremeDim_SR.pdf https://hal.science/hal-01340301/file/ExtendedData.pdf doi:10.1038/srep41278 info:eu-repo/semantics/OpenAccess ISSN: 2045-2322 EISSN: 2045-2322 Scientific Reports https://hal.science/hal-01340301 Scientific Reports, 2017, ⟨10.1038/srep41278⟩ [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an] [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] info:eu-repo/semantics/article Journal articles 2017 ftunivnantes https://doi.org/10.1038/srep41278 2023-02-08T10:08:16Z International audience Atmospheric flows are characterized by chaotic dynamics and recurring large-scale patterns . These two characteristics point to the existence of an atmospheric attractor defined by Lorenz as: ``the collection of all states that the system can assume or approach again and again, as opposed to those that it will ultimately avoid". The average dimension $D$ of the attractor corresponds to the number of degrees of freedom sufficient to describe the atmospheric circulation. However, obtaining reliable estimates of $D$ has proved challenging . Moreover, $D$ does not provide information on transient atmospheric motions, which lead to weather extremes . Using recent developments in dynamical systems theory , we show that such motions can be classified through instantaneous rather than average properties of the attractor. The instantaneous properties are uniquely determined by instantaneous dimension and stability. Their extreme values correspond to specific atmospheric patterns, and match extreme weather occurrences. We further show the existence of a significant correlation between the time series of instantaneous stability and dimension and the mean spread of sea-level pressure fields in an operational ensemble weather forecast at steps of over two weeks. We believe this method provides an efficient and practical way of evaluating and informing operational weather forecasts. Article in Journal/Newspaper North Atlantic Université de Nantes: HAL-UNIV-NANTES Scientific Reports 7 1 |
institution |
Open Polar |
collection |
Université de Nantes: HAL-UNIV-NANTES |
op_collection_id |
ftunivnantes |
language |
English |
topic |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an] [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] |
spellingShingle |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an] [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] Faranda, Davide Messori, Gabriele Yiou, Pascal Dynamical proxies of North Atlantic predictability and extremes |
topic_facet |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an] [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] |
description |
International audience Atmospheric flows are characterized by chaotic dynamics and recurring large-scale patterns . These two characteristics point to the existence of an atmospheric attractor defined by Lorenz as: ``the collection of all states that the system can assume or approach again and again, as opposed to those that it will ultimately avoid". The average dimension $D$ of the attractor corresponds to the number of degrees of freedom sufficient to describe the atmospheric circulation. However, obtaining reliable estimates of $D$ has proved challenging . Moreover, $D$ does not provide information on transient atmospheric motions, which lead to weather extremes . Using recent developments in dynamical systems theory , we show that such motions can be classified through instantaneous rather than average properties of the attractor. The instantaneous properties are uniquely determined by instantaneous dimension and stability. Their extreme values correspond to specific atmospheric patterns, and match extreme weather occurrences. We further show the existence of a significant correlation between the time series of instantaneous stability and dimension and the mean spread of sea-level pressure fields in an operational ensemble weather forecast at steps of over two weeks. We believe this method provides an efficient and practical way of evaluating and informing operational weather forecasts. |
author2 |
Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Department of Meteorology Stockholm (MISU) Stockholm University Bolin Centre for Climate Research ERC grant No 338965-A2C2 |
format |
Article in Journal/Newspaper |
author |
Faranda, Davide Messori, Gabriele Yiou, Pascal |
author_facet |
Faranda, Davide Messori, Gabriele Yiou, Pascal |
author_sort |
Faranda, Davide |
title |
Dynamical proxies of North Atlantic predictability and extremes |
title_short |
Dynamical proxies of North Atlantic predictability and extremes |
title_full |
Dynamical proxies of North Atlantic predictability and extremes |
title_fullStr |
Dynamical proxies of North Atlantic predictability and extremes |
title_full_unstemmed |
Dynamical proxies of North Atlantic predictability and extremes |
title_sort |
dynamical proxies of north atlantic predictability and extremes |
publisher |
HAL CCSD |
publishDate |
2017 |
url |
https://hal.science/hal-01340301 https://hal.science/hal-01340301/document https://hal.science/hal-01340301/file/ExtremeDim_SR.pdf https://hal.science/hal-01340301/file/ExtendedData.pdf https://doi.org/10.1038/srep41278 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
ISSN: 2045-2322 EISSN: 2045-2322 Scientific Reports https://hal.science/hal-01340301 Scientific Reports, 2017, ⟨10.1038/srep41278⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1038/srep41278 hal-01340301 https://hal.science/hal-01340301 https://hal.science/hal-01340301/document https://hal.science/hal-01340301/file/ExtremeDim_SR.pdf https://hal.science/hal-01340301/file/ExtendedData.pdf doi:10.1038/srep41278 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1038/srep41278 |
container_title |
Scientific Reports |
container_volume |
7 |
container_issue |
1 |
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1766133278577786880 |