Large ensemble assessment of the Arctic stratospheric polar vortex

The stratospheric polar vortex (SPV) is a phenomenon comprising strong westerly winds during winter in both hemispheres. Especially in the Northern Hemisphere (NH) the SPV is highly variable and is frequently disrupted by sudden stratospheric warmings (SSWs). SPV dynamics are relevant because of bot...

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Main Authors: Kuchar, Ales, Öhlert, Maurice, Eichinger, Roland, Jacobi, Christoph
Format: Text
Language:English
Published: 2023
Subjects:
Online Access:https://doi.org/10.5194/egusphere-2023-1831
https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1831/
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spelling ftcopernicus:oai:publications.copernicus.org:egusphere113997 2023-09-26T15:15:11+02:00 Large ensemble assessment of the Arctic stratospheric polar vortex Kuchar, Ales Öhlert, Maurice Eichinger, Roland Jacobi, Christoph 2023-08-21 application/pdf https://doi.org/10.5194/egusphere-2023-1831 https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1831/ eng eng doi:10.5194/egusphere-2023-1831 https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1831/ eISSN: Text 2023 ftcopernicus https://doi.org/10.5194/egusphere-2023-1831 2023-08-28T16:24:16Z The stratospheric polar vortex (SPV) is a phenomenon comprising strong westerly winds during winter in both hemispheres. Especially in the Northern Hemisphere (NH) the SPV is highly variable and is frequently disrupted by sudden stratospheric warmings (SSWs). SPV dynamics are relevant because of both ozone chemistry and its impact on tropospheric dynamics. In this study, we evaluate the capability of climate models to simulate the NH SPV by comparing large ensembles of historical simulations to the ERA5 reanalysis data. For this, we analyze geometric-based diagnostics at 3 pressure levels that describe SPV morphology. Moreover, we assess the ability of the models to simulate SSWs subdivided into SPV split and displacement events. A rank histogram analysis reveals that no model exactly reproduces ERA5 in all diagnostics at all levels. Concerning SPV aspect ratio and centroid latitude, most models are biased to some extent, but the strongest deviations can be found for the kurtosis. Some models underestimate the variability of the SPV area. Assessing the reliability of the ensembles in distinguishing SPV displacement and split events, we find large differences between the model ensembles. In general, SPV displacements are represented better than splits in the simulation ensembles, and high-top models and models with finer vertical resolution perform better. A good performance in representing the geometric-based diagnostics in rank histograms is found to be not necessarily connected to a good performance in simulating displacements and splits. Understanding the biases and improving the representation of SPV dynamics in climate model simulations can help to improve credibility of climate projections, in particular with focus on polar stratospheric dynamics and ozone. Text Arctic Copernicus Publications: E-Journals Arctic
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description The stratospheric polar vortex (SPV) is a phenomenon comprising strong westerly winds during winter in both hemispheres. Especially in the Northern Hemisphere (NH) the SPV is highly variable and is frequently disrupted by sudden stratospheric warmings (SSWs). SPV dynamics are relevant because of both ozone chemistry and its impact on tropospheric dynamics. In this study, we evaluate the capability of climate models to simulate the NH SPV by comparing large ensembles of historical simulations to the ERA5 reanalysis data. For this, we analyze geometric-based diagnostics at 3 pressure levels that describe SPV morphology. Moreover, we assess the ability of the models to simulate SSWs subdivided into SPV split and displacement events. A rank histogram analysis reveals that no model exactly reproduces ERA5 in all diagnostics at all levels. Concerning SPV aspect ratio and centroid latitude, most models are biased to some extent, but the strongest deviations can be found for the kurtosis. Some models underestimate the variability of the SPV area. Assessing the reliability of the ensembles in distinguishing SPV displacement and split events, we find large differences between the model ensembles. In general, SPV displacements are represented better than splits in the simulation ensembles, and high-top models and models with finer vertical resolution perform better. A good performance in representing the geometric-based diagnostics in rank histograms is found to be not necessarily connected to a good performance in simulating displacements and splits. Understanding the biases and improving the representation of SPV dynamics in climate model simulations can help to improve credibility of climate projections, in particular with focus on polar stratospheric dynamics and ozone.
format Text
author Kuchar, Ales
Öhlert, Maurice
Eichinger, Roland
Jacobi, Christoph
spellingShingle Kuchar, Ales
Öhlert, Maurice
Eichinger, Roland
Jacobi, Christoph
Large ensemble assessment of the Arctic stratospheric polar vortex
author_facet Kuchar, Ales
Öhlert, Maurice
Eichinger, Roland
Jacobi, Christoph
author_sort Kuchar, Ales
title Large ensemble assessment of the Arctic stratospheric polar vortex
title_short Large ensemble assessment of the Arctic stratospheric polar vortex
title_full Large ensemble assessment of the Arctic stratospheric polar vortex
title_fullStr Large ensemble assessment of the Arctic stratospheric polar vortex
title_full_unstemmed Large ensemble assessment of the Arctic stratospheric polar vortex
title_sort large ensemble assessment of the arctic stratospheric polar vortex
publishDate 2023
url https://doi.org/10.5194/egusphere-2023-1831
https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1831/
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source eISSN:
op_relation doi:10.5194/egusphere-2023-1831
https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1831/
op_doi https://doi.org/10.5194/egusphere-2023-1831
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