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Enz, B.M.* ; Engelmann, J.P. ; Lohmann, U.*

Use of threshold parameter variation for tropical cyclone tracking.

Geosci. Model. Dev. 16, 5093-5112 (2023)
Verlagsversion DOI
Open Access Gold
Creative Commons Lizenzvertrag
Assessing the capacity of numerical models to produce viable tropical cyclones, as well as assessing the climatological behavior of simulated tropical cyclones, requires an objective tracking method. These make use of parameter thresholds to determine whether a detected feature, such as a vorticity maximum or a warm core, is strong enough to indicate a tropical cyclone. The choice of parameter thresholds is generally subjective. This study proposes and assesses the parallel use of many threshold parameter combinations, combining a number of weaker and stronger values. The tracking algorithm succeeds in tracking tropical cyclones within the model data, beginning at their aggregation stage or shortly thereafter and ending when they interact strongly with extratropical flow and transition into extratropical cyclones or when their warm core decays. The sensitivity of accumulated cyclone energy to tracking errors is assessed. Tracking errors include the faulty initial detection and termination of valid tropical cyclones and systems falsely identified as tropical cyclones. They are found to not significantly impact the accumulated cyclone energy. Thus, the tracking algorithm produces an adequate estimate of the accumulated cyclone energy within the underlying data.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Hurricane-type Vortices; Extratropical Transition; Global Climatology; Life-cycle; Warm-core; Circulation; Variability; Dependence; Dynamics; Model
ISSN (print) / ISBN 1991-959X
e-ISSN 1991-959X
Zeitschrift Geoscientific model development
Quellenangaben Band: 16, Heft: 17, Seiten: 5093-5112 Artikelnummer: , Supplement: ,
Verlag Copernicus
Verlagsort Göttingen
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)