Estimation of the maximum annual number of North Atlantic tropical cyclones using climate models

Article


Lavender, Sally L., Walsh, Kevin J. E., Caron, Louis-Philippe, King, Malcolm, Monkiewicz, Sam, Guishard, Mark, Zhang, Qiong and Hunt, barrie. 2018. "Estimation of the maximum annual number of North Atlantic tropical cyclones using climate models." Science Advances. 4 (8), pp. 1-8. https://doi.org/10.1126/sciadv.aat6509
Article Title

Estimation of the maximum annual number of North Atlantic tropical cyclones using climate models

ERA Journal ID211335
Article CategoryArticle
AuthorsLavender, Sally L. (Author), Walsh, Kevin J. E. (Author), Caron, Louis-Philippe (Author), King, Malcolm (Author), Monkiewicz, Sam (Author), Guishard, Mark (Author), Zhang, Qiong (Author) and Hunt, barrie (Author)
Journal TitleScience Advances
Journal Citation4 (8), pp. 1-8
Article Number6509
Number of Pages8
Year2018
Place of PublicationUnited States
ISSN2375-2548
Digital Object Identifier (DOI)https://doi.org/10.1126/sciadv.aat6509
Web Address (URL)https://advances.sciencemag.org/content/4/8/eaat6509
Abstract

Using millennia-long climate model simulations, favorable environments for tropical cyclone formation are examined to determine whether the record number of tropical cyclones in the 2005 Atlantic season is close to the maximum possible number for the present climate of that basin. By estimating both the mean number of tropical cyclones and their possible year-to-year random variability, we find that the likelihood that the maximum number of storms in the Atlantic could be greater than the number of events observed during the 2005 season is less than 3.5%. Using a less restrictive comparison between simulated and observed climate with the internal variability accounted for, this probability increases to 9%; however, the estimated maximum possible number of tropical cyclones does not greatly exceed the 2005 total. Hence, the 2005 season can be used as a risk management benchmark for the maximum possible number of tropical cyclones in the Atlantic.

Keywordshurricanes; maximum likelihood estimation; risk management; storms; tropics; climate model simulations; internal variability; North Atlantic; random variability; tropical cyclone; climate models
ANZSRC Field of Research 2020370108. Meteorology
370202. Climatology
Byline AffiliationsCommonwealth Scientific and Industrial Research Organisation (CSIRO), Australia
University of Melbourne
Barcelona Supercomputing Centre, Spain
Bermuda Institute of Ocean Sciences, Bermuda
Stockholm University, Sweden
Institution of OriginUniversity of Southern Queensland
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