How to identify weather patterns associated with occurrences of extreme events in models (D1.1)

Meridional transport of heat by transient atmospheric eddies is a key component of the energy budget of the Arctic and high latitude regions. While transport in the mid-latitudes is known to be modulated by large-scale low frequency flow regimes, little is known about the link between heat flux in t...

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Main Author: Ruggieri, Paolo
Format: Report
Language:unknown
Published: 2019
Subjects:
Online Access:https://zenodo.org/record/3769844
https://doi.org/10.5281/zenodo.3769844
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spelling ftzenodo:oai:zenodo.org:3769844 2023-05-15T15:02:00+02:00 How to identify weather patterns associated with occurrences of extreme events in models (D1.1) Ruggieri, Paolo 2019-11-05 https://zenodo.org/record/3769844 https://doi.org/10.5281/zenodo.3769844 unknown info:eu-repo/grantAgreement/EC/H2020/727852/ doi:10.5281/zenodo.3769843 https://zenodo.org/communities/blue-actionh2020 https://zenodo.org/record/3769844 https://doi.org/10.5281/zenodo.3769844 oai:zenodo.org:3769844 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/report publication-deliverable 2019 ftzenodo https://doi.org/10.5281/zenodo.376984410.5281/zenodo.3769843 2023-03-11T04:04:34Z Meridional transport of heat by transient atmospheric eddies is a key component of the energy budget of the Arctic and high latitude regions. While transport in the mid-latitudes is known to be modulated by large-scale low frequency flow regimes, little is known about the link between heat flux in the polar cap and mid-latitude circulation regimes. Recent studies suggest that heat and moisture transport into polar regions happens in bursts that are associated with propagation of storms and atmospheric blocking. While the picture is evolving, a systematic assessment is still lacking. We investigate the modulation of transient, poleward atmospheric eddy heat flux induced by the variability of the atmospheric circulation in the North Atlantic sector. Heat transport is defined by meridional advection of moist static energy, and the circulation anomalies are diagnosed with a widely used clustering technique, a jet latitude index and a blocking index. The analysis is carried out for the extra tropics in the Northern Hemisphere but special emphasis is given to heat transport crossing the 70 ◦N latitude circle. Results are based on an atmospheric reanalysis for a total of 38 extended cold seasons. Establishing quantitative relationships between circulation regimes and poleward heat transport by transient eddies can help understand linkages between mid-latitudes and the Arctic, and evaluate how they are represented in coupled GCMs. In principle, it can help exploit predictability on a sub- seasonal time scale. The relationship between extreme events of strong heat flux and circulation regimes is also assessed and the analysis indicates a fundamental role of blocking in the North Atlantic sector. The presented empirical relationship between heat flux variability and extreme events can serve as a powerful tool for predictability analysis, but also for the evaluation of model variability. The Blue-Action project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant ... Report Arctic North Atlantic Zenodo Arctic
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description Meridional transport of heat by transient atmospheric eddies is a key component of the energy budget of the Arctic and high latitude regions. While transport in the mid-latitudes is known to be modulated by large-scale low frequency flow regimes, little is known about the link between heat flux in the polar cap and mid-latitude circulation regimes. Recent studies suggest that heat and moisture transport into polar regions happens in bursts that are associated with propagation of storms and atmospheric blocking. While the picture is evolving, a systematic assessment is still lacking. We investigate the modulation of transient, poleward atmospheric eddy heat flux induced by the variability of the atmospheric circulation in the North Atlantic sector. Heat transport is defined by meridional advection of moist static energy, and the circulation anomalies are diagnosed with a widely used clustering technique, a jet latitude index and a blocking index. The analysis is carried out for the extra tropics in the Northern Hemisphere but special emphasis is given to heat transport crossing the 70 ◦N latitude circle. Results are based on an atmospheric reanalysis for a total of 38 extended cold seasons. Establishing quantitative relationships between circulation regimes and poleward heat transport by transient eddies can help understand linkages between mid-latitudes and the Arctic, and evaluate how they are represented in coupled GCMs. In principle, it can help exploit predictability on a sub- seasonal time scale. The relationship between extreme events of strong heat flux and circulation regimes is also assessed and the analysis indicates a fundamental role of blocking in the North Atlantic sector. The presented empirical relationship between heat flux variability and extreme events can serve as a powerful tool for predictability analysis, but also for the evaluation of model variability. The Blue-Action project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant ...
format Report
author Ruggieri, Paolo
spellingShingle Ruggieri, Paolo
How to identify weather patterns associated with occurrences of extreme events in models (D1.1)
author_facet Ruggieri, Paolo
author_sort Ruggieri, Paolo
title How to identify weather patterns associated with occurrences of extreme events in models (D1.1)
title_short How to identify weather patterns associated with occurrences of extreme events in models (D1.1)
title_full How to identify weather patterns associated with occurrences of extreme events in models (D1.1)
title_fullStr How to identify weather patterns associated with occurrences of extreme events in models (D1.1)
title_full_unstemmed How to identify weather patterns associated with occurrences of extreme events in models (D1.1)
title_sort how to identify weather patterns associated with occurrences of extreme events in models (d1.1)
publishDate 2019
url https://zenodo.org/record/3769844
https://doi.org/10.5281/zenodo.3769844
geographic Arctic
geographic_facet Arctic
genre Arctic
North Atlantic
genre_facet Arctic
North Atlantic
op_relation info:eu-repo/grantAgreement/EC/H2020/727852/
doi:10.5281/zenodo.3769843
https://zenodo.org/communities/blue-actionh2020
https://zenodo.org/record/3769844
https://doi.org/10.5281/zenodo.3769844
oai:zenodo.org:3769844
op_rights info:eu-repo/semantics/openAccess
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op_doi https://doi.org/10.5281/zenodo.376984410.5281/zenodo.3769843
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