Predictors and prediction skill for marine cold air outbreaks over the Barents Sea ...

Marine cold air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (i) the ability of a seasonal prediction system...

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Main Authors: Polkova, Iuliia, Afargan-Gerstman, Hilla, Domeisen, Daniela, King, Martin P., Ruggieri, Paolo, Athanasiadis, Panos, Dobrynin, Mikhail, Aarnes, Øivin, Kretschmer, Marlene, Baehr, Johanna
Format: Article in Journal/Newspaper
Language:English
Published: ETH Zurich 2021
Subjects:
Online Access:https://dx.doi.org/10.3929/ethz-b-000478568
http://hdl.handle.net/20.500.11850/478568
id ftdatacite:10.3929/ethz-b-000478568
record_format openpolar
spelling ftdatacite:10.3929/ethz-b-000478568 2024-04-28T08:10:27+00:00 Predictors and prediction skill for marine cold air outbreaks over the Barents Sea ... Polkova, Iuliia Afargan-Gerstman, Hilla Domeisen, Daniela King, Martin P. Ruggieri, Paolo Athanasiadis, Panos Dobrynin, Mikhail Aarnes, Øivin Kretschmer, Marlene Baehr, Johanna 2021 application/pdf https://dx.doi.org/10.3929/ethz-b-000478568 http://hdl.handle.net/20.500.11850/478568 en eng ETH Zurich info:eu-repo/semantics/openAccess Creative Commons Attribution Non Commercial No Derivatives 4.0 International https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode cc-by-nc-nd-4.0 Arctic climate Marine cold air outbreak Polar low Seasonal prediction Causal drivers article-journal Text ScholarlyArticle Journal Article 2021 ftdatacite https://doi.org/10.3929/ethz-b-000478568 2024-04-02T12:34:54Z Marine cold air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (i) the ability of a seasonal prediction system to predict MCAOs and (ii) the possibilities to improve predictions through large‐scale causal drivers. Our results show that the seasonal ensemble predictions have high prediction skill for MCAOs over the Nordic Seas for about 20 days starting from November initial conditions. To study causal drivers of MCAOs, we utilize a causal effect network approach applied to the atmospheric reanalysis ERA‐Interim and identify local sea surface temperature and atmospheric circulation patterns over Scandinavia as valuable predictors. Prediction skill for MCAOs is further improved up to 40 days including MCAO predictors in the analysis. ... : Quarterly Journal of the Royal Meteorological Society, 147 (738) ... Article in Journal/Newspaper Arctic Barents Sea Nordic Seas DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic Arctic climate
Marine cold air outbreak
Polar low
Seasonal prediction
Causal drivers
spellingShingle Arctic climate
Marine cold air outbreak
Polar low
Seasonal prediction
Causal drivers
Polkova, Iuliia
Afargan-Gerstman, Hilla
Domeisen, Daniela
King, Martin P.
Ruggieri, Paolo
Athanasiadis, Panos
Dobrynin, Mikhail
Aarnes, Øivin
Kretschmer, Marlene
Baehr, Johanna
Predictors and prediction skill for marine cold air outbreaks over the Barents Sea ...
topic_facet Arctic climate
Marine cold air outbreak
Polar low
Seasonal prediction
Causal drivers
description Marine cold air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (i) the ability of a seasonal prediction system to predict MCAOs and (ii) the possibilities to improve predictions through large‐scale causal drivers. Our results show that the seasonal ensemble predictions have high prediction skill for MCAOs over the Nordic Seas for about 20 days starting from November initial conditions. To study causal drivers of MCAOs, we utilize a causal effect network approach applied to the atmospheric reanalysis ERA‐Interim and identify local sea surface temperature and atmospheric circulation patterns over Scandinavia as valuable predictors. Prediction skill for MCAOs is further improved up to 40 days including MCAO predictors in the analysis. ... : Quarterly Journal of the Royal Meteorological Society, 147 (738) ...
format Article in Journal/Newspaper
author Polkova, Iuliia
Afargan-Gerstman, Hilla
Domeisen, Daniela
King, Martin P.
Ruggieri, Paolo
Athanasiadis, Panos
Dobrynin, Mikhail
Aarnes, Øivin
Kretschmer, Marlene
Baehr, Johanna
author_facet Polkova, Iuliia
Afargan-Gerstman, Hilla
Domeisen, Daniela
King, Martin P.
Ruggieri, Paolo
Athanasiadis, Panos
Dobrynin, Mikhail
Aarnes, Øivin
Kretschmer, Marlene
Baehr, Johanna
author_sort Polkova, Iuliia
title Predictors and prediction skill for marine cold air outbreaks over the Barents Sea ...
title_short Predictors and prediction skill for marine cold air outbreaks over the Barents Sea ...
title_full Predictors and prediction skill for marine cold air outbreaks over the Barents Sea ...
title_fullStr Predictors and prediction skill for marine cold air outbreaks over the Barents Sea ...
title_full_unstemmed Predictors and prediction skill for marine cold air outbreaks over the Barents Sea ...
title_sort predictors and prediction skill for marine cold air outbreaks over the barents sea ...
publisher ETH Zurich
publishDate 2021
url https://dx.doi.org/10.3929/ethz-b-000478568
http://hdl.handle.net/20.500.11850/478568
genre Arctic
Barents Sea
Nordic Seas
genre_facet Arctic
Barents Sea
Nordic Seas
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution Non Commercial No Derivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
cc-by-nc-nd-4.0
op_doi https://doi.org/10.3929/ethz-b-000478568
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