Features and Processes Influencing the Evolution and Forecast Skill of Strong Low-Skill Arctic Cyclones

Kevin A. Biernat Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York

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Lance F. Bosart Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York

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Daniel Keyser Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York

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Abstract

Strong Arctic cyclones (ACs) characterized by low forecast skill of intensity, hereafter referred to as strong low-skill ACs, may pose challenges to human activities in the Arctic. The purpose of this study is to increase understanding of features and processes influencing the evolution and forecast skill of the intensity of strong low-skill ACs. Features and processes influencing the evolution of strong low-skill ACs are examined by constructing AC-centered composites for strong low-skill ACs and by conducting a synoptic–dynamic analysis of a representative strong low-skill AC that occurred during August 2016, hereafter referred to as AC16. Features and processes influencing the forecast skill of the intensity of strong low-skill ACs are examined by utilizing the ensemble-based sensitivity analysis (ESA) technique for AC16. The composite analysis for the strong low-skill ACs and the synoptic–dynamic analysis of AC16 suggest that tropopause polar vortices (TPVs), TPV–AC interactions, baroclinic processes, and latent heating influence the evolution of the strong low-skill ACs and AC16. The ESA suggests that the forecast skill of the intensity of AC16 is sensitive to the amplitude of an upper-tropospheric trough and the strength of an embedded TPV west of AC16, and the amplitude of an upper-tropospheric ridge east of AC16. The ESA also suggests that the forecast skill of the intensity of AC16 is sensitive to the amplitude of a 1000–500-hPa thickness trough and of a 1000–500-hPa thickness ridge in the vicinity of AC16, and the positions of regions of latent heating associated with AC16.

© 2025 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kevin A. Biernat, kevin.a.biernat@gmail.com

Abstract

Strong Arctic cyclones (ACs) characterized by low forecast skill of intensity, hereafter referred to as strong low-skill ACs, may pose challenges to human activities in the Arctic. The purpose of this study is to increase understanding of features and processes influencing the evolution and forecast skill of the intensity of strong low-skill ACs. Features and processes influencing the evolution of strong low-skill ACs are examined by constructing AC-centered composites for strong low-skill ACs and by conducting a synoptic–dynamic analysis of a representative strong low-skill AC that occurred during August 2016, hereafter referred to as AC16. Features and processes influencing the forecast skill of the intensity of strong low-skill ACs are examined by utilizing the ensemble-based sensitivity analysis (ESA) technique for AC16. The composite analysis for the strong low-skill ACs and the synoptic–dynamic analysis of AC16 suggest that tropopause polar vortices (TPVs), TPV–AC interactions, baroclinic processes, and latent heating influence the evolution of the strong low-skill ACs and AC16. The ESA suggests that the forecast skill of the intensity of AC16 is sensitive to the amplitude of an upper-tropospheric trough and the strength of an embedded TPV west of AC16, and the amplitude of an upper-tropospheric ridge east of AC16. The ESA also suggests that the forecast skill of the intensity of AC16 is sensitive to the amplitude of a 1000–500-hPa thickness trough and of a 1000–500-hPa thickness ridge in the vicinity of AC16, and the positions of regions of latent heating associated with AC16.

© 2025 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kevin A. Biernat, kevin.a.biernat@gmail.com
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