A methodology for attributing severe extratropical cyclones to climate change based on reanalysis data: the case study of storm Alex 2020
Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France a...
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| Autor*in: |
Ginesta, Mireia [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Climate dynamics - Springer Berlin Heidelberg, 1986, 61(2022), 1-2 vom: 13. Nov., Seite 229-253 |
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| Übergeordnetes Werk: |
volume:61 ; year:2022 ; number:1-2 ; day:13 ; month:11 ; pages:229-253 |
| Links: |
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| DOI / URN: |
10.1007/s00382-022-06565-x |
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OLC2143973462 |
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| 520 | |a Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex’s map by selecting those with the lowest Euclidean distance from Alex. We term these “analogues” of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. | ||
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10.1007/s00382-022-06565-x doi (DE-627)OLC2143973462 (DE-He213)s00382-022-06565-x-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Ginesta, Mireia verfasserin (orcid)0000-0002-6916-9475 aut A methodology for attributing severe extratropical cyclones to climate change based on reanalysis data: the case study of storm Alex 2020 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex’s map by selecting those with the lowest Euclidean distance from Alex. We term these “analogues” of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. Extratropical explosive cyclones Extreme event attribution Climate change Analogues Yiou, Pascal aut Messori, Gabriele aut Faranda, Davide aut Enthalten in Climate dynamics Springer Berlin Heidelberg, 1986 61(2022), 1-2 vom: 13. Nov., Seite 229-253 (DE-627)129932728 (DE-600)382992-3 (DE-576)015479005 0930-7575 nnns volume:61 year:2022 number:1-2 day:13 month:11 pages:229-253 https://doi.org/10.1007/s00382-022-06565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_62 GBV_ILN_154 GBV_ILN_2018 GBV_ILN_4277 AR 61 2022 1-2 13 11 229-253 |
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10.1007/s00382-022-06565-x doi (DE-627)OLC2143973462 (DE-He213)s00382-022-06565-x-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Ginesta, Mireia verfasserin (orcid)0000-0002-6916-9475 aut A methodology for attributing severe extratropical cyclones to climate change based on reanalysis data: the case study of storm Alex 2020 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex’s map by selecting those with the lowest Euclidean distance from Alex. We term these “analogues” of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. Extratropical explosive cyclones Extreme event attribution Climate change Analogues Yiou, Pascal aut Messori, Gabriele aut Faranda, Davide aut Enthalten in Climate dynamics Springer Berlin Heidelberg, 1986 61(2022), 1-2 vom: 13. Nov., Seite 229-253 (DE-627)129932728 (DE-600)382992-3 (DE-576)015479005 0930-7575 nnns volume:61 year:2022 number:1-2 day:13 month:11 pages:229-253 https://doi.org/10.1007/s00382-022-06565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_62 GBV_ILN_154 GBV_ILN_2018 GBV_ILN_4277 AR 61 2022 1-2 13 11 229-253 |
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10.1007/s00382-022-06565-x doi (DE-627)OLC2143973462 (DE-He213)s00382-022-06565-x-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Ginesta, Mireia verfasserin (orcid)0000-0002-6916-9475 aut A methodology for attributing severe extratropical cyclones to climate change based on reanalysis data: the case study of storm Alex 2020 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex’s map by selecting those with the lowest Euclidean distance from Alex. We term these “analogues” of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. Extratropical explosive cyclones Extreme event attribution Climate change Analogues Yiou, Pascal aut Messori, Gabriele aut Faranda, Davide aut Enthalten in Climate dynamics Springer Berlin Heidelberg, 1986 61(2022), 1-2 vom: 13. Nov., Seite 229-253 (DE-627)129932728 (DE-600)382992-3 (DE-576)015479005 0930-7575 nnns volume:61 year:2022 number:1-2 day:13 month:11 pages:229-253 https://doi.org/10.1007/s00382-022-06565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_62 GBV_ILN_154 GBV_ILN_2018 GBV_ILN_4277 AR 61 2022 1-2 13 11 229-253 |
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10.1007/s00382-022-06565-x doi (DE-627)OLC2143973462 (DE-He213)s00382-022-06565-x-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Ginesta, Mireia verfasserin (orcid)0000-0002-6916-9475 aut A methodology for attributing severe extratropical cyclones to climate change based on reanalysis data: the case study of storm Alex 2020 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex’s map by selecting those with the lowest Euclidean distance from Alex. We term these “analogues” of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. Extratropical explosive cyclones Extreme event attribution Climate change Analogues Yiou, Pascal aut Messori, Gabriele aut Faranda, Davide aut Enthalten in Climate dynamics Springer Berlin Heidelberg, 1986 61(2022), 1-2 vom: 13. Nov., Seite 229-253 (DE-627)129932728 (DE-600)382992-3 (DE-576)015479005 0930-7575 nnns volume:61 year:2022 number:1-2 day:13 month:11 pages:229-253 https://doi.org/10.1007/s00382-022-06565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_62 GBV_ILN_154 GBV_ILN_2018 GBV_ILN_4277 AR 61 2022 1-2 13 11 229-253 |
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10.1007/s00382-022-06565-x doi (DE-627)OLC2143973462 (DE-He213)s00382-022-06565-x-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Ginesta, Mireia verfasserin (orcid)0000-0002-6916-9475 aut A methodology for attributing severe extratropical cyclones to climate change based on reanalysis data: the case study of storm Alex 2020 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex’s map by selecting those with the lowest Euclidean distance from Alex. We term these “analogues” of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. Extratropical explosive cyclones Extreme event attribution Climate change Analogues Yiou, Pascal aut Messori, Gabriele aut Faranda, Davide aut Enthalten in Climate dynamics Springer Berlin Heidelberg, 1986 61(2022), 1-2 vom: 13. Nov., Seite 229-253 (DE-627)129932728 (DE-600)382992-3 (DE-576)015479005 0930-7575 nnns volume:61 year:2022 number:1-2 day:13 month:11 pages:229-253 https://doi.org/10.1007/s00382-022-06565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_62 GBV_ILN_154 GBV_ILN_2018 GBV_ILN_4277 AR 61 2022 1-2 13 11 229-253 |
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a methodology for attributing severe extratropical cyclones to climate change based on reanalysis data: the case study of storm alex 2020 |
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A methodology for attributing severe extratropical cyclones to climate change based on reanalysis data: the case study of storm Alex 2020 |
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Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex’s map by selecting those with the lowest Euclidean distance from Alex. We term these “analogues” of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex’s map by selecting those with the lowest Euclidean distance from Alex. We term these “analogues” of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Abstract Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for severe extratropical cyclones, and test it on storm Alex. Alex was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and identifies changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period (1950–1984) and a factual period (1986–2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closest to Alex’s map by selecting those with the lowest Euclidean distance from Alex. We term these “analogues” of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues display an increase in the eddy kinetic energy in their growth phase, with poleward-shifted backward tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual period are closer to Alex than in the counterfactual period. These changes collectively point to high-impact storms like Alex having become more common in a changing climate. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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