Improving analogues-based detection & attribution approaches for hurricanes

Abstract This paper presents a proof of concept for a new analogue-based framework for the detection and attribution of hurricane-related hazards. This framework addresses two important limitations of existing analogue-based methodologies: the lack of observed similar events, and the unsuitability of the distance metrics for hurricanes. To do so, we use a track-based metric, and we make use of synthetic tracks catalogues. We show that our method allows for selecting a sufficient number of suitable analogues, and we apply it to nine hurricane cases. Our analysis does not reveal any robust changes in wind hazards, translation speed, seasonality, or frequency over recent decades, consistent with current literature. This framework provides a reliable alternative to traditional analogue-based methods in the case of hurricanes, complementing and potentially enhancing efforts in addressing extreme weather event attribution.

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Publication Details

Journal
Environmental Research Letters
Published
2025-01-16
DOI
https://doi.org/10.1088/1748-9326/adaa8d
Citations
2
Primary Topic
Tropical and Extratropical Cyclones Research
Type
article
Field-Weighted Citation Impact
2.60

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article

Improving analogues-based detection & attribution approaches for hurricanes

Jonathan Lin, Stella Bourdin, Pradeebane Vaittinada Ayar, Chia‐Ying Lee et al.
2 citations
Environmental Research Letters
Tropical and Extratropical Cyclones Research
2.60
article

Improving analogues-based detection & attribution approaches for hurricanes

Jonathan Lin, Stella Bourdin, Pradeebane Vaittinada Ayar, Chia‐Ying Lee, Suzana J. Camargo, Mathieu Vrac, Davide Faranda
article en
2 citations

Abstract

Abstract This paper presents a proof of concept for a new analogue-based framework for the detection and attribution of hurricane-related hazards. This framework addresses two important limitations of existing analogue-based methodologies: the lack of observed similar events, and the unsuitability of the distance metrics for hurricanes. To do so, we use a track-based metric, and we make use of synthetic tracks catalogues. We show that our method allows for selecting a sufficient number of suitable analogues, and we apply it to nine hurricane cases. Our analysis does not reveal any robust changes in wind hazards, translation speed, seasonality, or frequency over recent decades, consistent with current literature. This framework provides a reliable alternative to traditional analogue-based methods in the case of hurricanes, complementing and potentially enhancing efforts in addressing extreme weather event attribution.

Environmental Research LettersVol. 20(2)
Lamont-Doherty Earth Observatory (US), Cornell University (US), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), University of Oxford (GB), Laboratoire des Sciences du Climat et de l'Environnement (FR), CEA Paris-Saclay (FR)
National Science Foundation, Sight Research UK, European Commission, European Cooperation in Science and Technology, Agence Nationale de la Recherche, Centre National de la Recherche Scientifique, Université Paris-Saclay, Horizon 2020 Framework Programme, Natural Environment Research Council, Institut national des sciences de l'Univers, Division of Atmospheric and Geospace Sciences, H2020 Marie Skłodowska-Curie Actions
Climate action
Openalex Percentile: Top 15%
Tropical and Extratropical Cyclones Research
2.60
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