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A Global Climatology of Extratropical Transition. Part II: Statistical Performance of the Cyclone Phase Space

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  • 1 Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York
  • | 2 Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York
  • | 3 Department of Applied Physics and Applied Mathematics, and Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York
  • | 4 Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania
  • | 5 NASA Goddard Institute for Space Studies, New York, New York
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Abstract

This study analyzes the differences between an objective, automated identification of tropical cyclones (TCs) that undergo extratropical transition (ET), and the designation of ET determined subjectively by human forecasters in best track data in all basins globally. The objective identification of ET is based on the cyclone phase space (CPS), calculated from the Japanese 55-yr Reanalysis (JRA-55) or the ECMWF interim reanalysis (ERA-Interim). The resulting classification into ET storms and non-ET storms underlies the global climatology of ET presented in Part I of this study. Here, the authors investigate how well the CPS classifications agree with those in the best track records calculated from JRA-55 or from ERA-Interim data. According to F1 scores and Matthews correlation coefficients (MCCs), the classification of ET storms in the CPS agrees best with the best track classification in the western North Pacific (MCC > 0.7) and the North Atlantic (MCC > 0.5). In other basins, the correlation between the CPS classification and the best track classification is only slightly higher than that of a random classification. The JRA-55 classification achieves higher performance scores than does the ERA-Interim classification, and the differences are statistically significant in all basins. The lower performance of ERA-Interim is mainly due to a higher false alarm rate, particularly in the eastern North Pacific. Overall, the results show that while the CPS-based classifications are good enough to be useful for many purposes, there is almost certainly room for improvement—in the representation of the storms in reanalyses, in our objective metrics of ET, and in our scientific understanding of the ET process.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-18-0052.1.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article has a companion article which can be found at http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-17-0518.1.

Publisher’s Note: This article was revised on 5 August 2019 in order to correct a typographical error in section 3d.

Corresponding author: Melanie Bieli, mb4036@columbia.edu

Abstract

This study analyzes the differences between an objective, automated identification of tropical cyclones (TCs) that undergo extratropical transition (ET), and the designation of ET determined subjectively by human forecasters in best track data in all basins globally. The objective identification of ET is based on the cyclone phase space (CPS), calculated from the Japanese 55-yr Reanalysis (JRA-55) or the ECMWF interim reanalysis (ERA-Interim). The resulting classification into ET storms and non-ET storms underlies the global climatology of ET presented in Part I of this study. Here, the authors investigate how well the CPS classifications agree with those in the best track records calculated from JRA-55 or from ERA-Interim data. According to F1 scores and Matthews correlation coefficients (MCCs), the classification of ET storms in the CPS agrees best with the best track classification in the western North Pacific (MCC > 0.7) and the North Atlantic (MCC > 0.5). In other basins, the correlation between the CPS classification and the best track classification is only slightly higher than that of a random classification. The JRA-55 classification achieves higher performance scores than does the ERA-Interim classification, and the differences are statistically significant in all basins. The lower performance of ERA-Interim is mainly due to a higher false alarm rate, particularly in the eastern North Pacific. Overall, the results show that while the CPS-based classifications are good enough to be useful for many purposes, there is almost certainly room for improvement—in the representation of the storms in reanalyses, in our objective metrics of ET, and in our scientific understanding of the ET process.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-18-0052.1.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article has a companion article which can be found at http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-17-0518.1.

Publisher’s Note: This article was revised on 5 August 2019 in order to correct a typographical error in section 3d.

Corresponding author: Melanie Bieli, mb4036@columbia.edu

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