Accessibility navigation


High prediction skill of decadal tropical cyclone variability in the North Atlantic and East Pacific in the met office decadal prediction system DePreSys4

Monerie, P.-A. ORCID: https://orcid.org/0000-0002-5304-9559, Feng, X. ORCID: https://orcid.org/0000-0003-4143-107X, Hodges, K. ORCID: https://orcid.org/0000-0003-0894-229X and Toumi, R. (2025) High prediction skill of decadal tropical cyclone variability in the North Atlantic and East Pacific in the met office decadal prediction system DePreSys4. npj Climate and Atmospheric Science, 8. 32. ISSN 2397-3722

[img] Text - Published Version
· Restricted to Repository staff only
· The Copyright of this document has not been checked yet. This may affect its availability.
· Available under License Creative Commons Attribution.

5MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1038/s41612-025-00919-y

Abstract/Summary

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.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:120411
Publisher:Nature Publishing Group

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation