High prediction skill of decadal tropical cyclone variability in the North Atlantic and East Pacific in the met office decadal prediction system DePreSys4
File(s)
Published version
Author(s)
Monerie, Paul-Arthur
Feng, Xiangbo
Hodges, Kevin
Toumi, Ralf
Type
Journal Article
Abstract
The UK Met Office decadal prediction system DePreSys4 shows skill in predicting the number of tropical cyclones (TCs) and TC track density over the eastern Pacific and tropical Atlantic Ocean on the decadal timescale (up to ACC = 0.93 and ACC = 0.83, respectively, as measured by the anomaly correlation coefficient—ACC). The high skill in predicting the number of TCs is related to the simulation of the externally forced response, with internal climate variability also allowing the improvement in prediction skill. The Skill is due to the model’s ability to predict the temporal evolution of surface temperature and vertical wind shear over the eastern Pacific and tropical Atlantic Ocean. We apply a signal-to-noise calibration framework and show that DePreSys4 predicts an increase in the number of TCs over the eastern Pacific and the tropical Atlantic Ocean in the next decade (2023–2030), potentially leading to high economic losses.
Date Issued
2025-01-25
Date Acceptance
2025-01-15
Citation
npj Climate and Atmospheric Science, 2025, 8
ISSN
2397-3722
Publisher
Nature Portfolio
Journal / Book Title
npj Climate and Atmospheric Science
Volume
8
Copyright Statement
© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
10.1038/s41612-025-00919-y
Publication Status
Published
Article Number
32
Date Publish Online
2025-01-25