2020
DOI: 10.1088/2515-7620/ab7b35
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Objective identification of potentially damaging tropical cyclones over the Western North Pacific

Abstract: An impact-oriented objective windstorm identification algorithm (WiTRACK ), originally developed and well established for studies on extra-tropical storms, is further developed to identify damage and loss related Tropical Cyclones (TC) over the Western North Pacific. Results based on JRA-55 reanalysis data reveal that WiTRACK is able to detect the majority of strong events with hitrates of about 77%/90%/98% for TCs of the three most severe categories. Using economic loss data for China, it is found that especi… Show more

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Cited by 7 publications
(17 citation statements)
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“…Befort et al. (2020) has recently demonstrated the skill of WiTRACK in tracking TCs in the West Pacific, and we apply it here for the first time to Atlantic hurricanes so that the damage potential from both seasons can be compared directly.…”
Section: Resultsmentioning
confidence: 99%
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“…Befort et al. (2020) has recently demonstrated the skill of WiTRACK in tracking TCs in the West Pacific, and we apply it here for the first time to Atlantic hurricanes so that the damage potential from both seasons can be compared directly.…”
Section: Resultsmentioning
confidence: 99%
“…For both European windstorms and TCs, events are classified by identifying and tracking clusters of wind speed exceeding a local threshold. Classification is performed using the algorithm WiTRACK (introduced by Leckebusch et al., 2008, applied in Befort et al., 2020; Kruschke, 2015; Renggli et al., 2011). For the local threshold, the 98th percentile is chosen because of its association with extratropical cyclone‐related damage over Europe (Klawa & Ulbrich, 2003).…”
Section: Methodsmentioning
confidence: 99%
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“…The TIGGE data archive has been used extensively in the study of TC activity forecast (e.g. Vitart et al, 2012;Belanger et al, 2012;Halperin et al, 2013;Majumdar and Torn, 2014;Leonardo and Colle, 2017;Luitel et al, 2018). The TIGGE data archive consists of ∼ 8-15 d ensemble forecast data from 10 numerical weather prediction (NWP) centres with about 11-50 members each.…”
Section: Datamentioning
confidence: 99%