- Title
- Clustering tropical cyclone genesis on ENSO timescales in the southwest Pacific
- Creator
- Tu’uholoaki, Moleni; Espejo, Antonio; Singh, Awnesh; Damlamian, Herve; Wandres, Moritz; Chand, Savin; Mendez, Fernando; Fa’anunu, Ofa
- Date
- 2023
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/196218
- Identifier
- vital:18674
- Identifier
-
https://doi.org/10.1007/s00382-022-06497-6
- Identifier
- ISSN:0930-7575 (ISSN)
- Abstract
- Tropical cyclones (TCs) as a natural hazard pose a major threat and risk to the human population globally. This threat is expected to increase in a warming climate as the frequency of severe TCs is expected to increase. In this study, the influence of different monthly sea surface temperature (SST) patterns on the locations and frequency of tropical cyclone genesis (TCG) in the Southwest Pacific (SWP) region is investigated. Using principal component analysis and k-means clustering of monthly SST between 1970 and 2019, nine statistically different SST patterns are identified. Our findings show that the more prominent ENSO patterns such as the Modoki El Niño (i.e., Modoki I and Modoki II) and Eastern Pacific (EP) El Niño impact the frequency and location of TCG significantly. Our results enhance the overall understanding of the TCG variability and the relationship between TCG and SST configurations in the SWP region. The results of this study may support early warning system in SWP by improving seasonal outlooks and quantification of the level of TC-related risks for the vulnerable Pacific Island communities. © 2022, The Author(s).
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Relation
- Climate Dynamics Vol. 60, no. 11-12 (2023), p. 3353-3368
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- http://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright © 2022, The Author(s)
- Rights
- Open Access
- Subject
- 3701 Atmospheric sciences; 3702 Climate change science; 3708 Oceanography; ENSO types; k-means clustering algorithm; Principal component analysis; Sea surface temperatures; Tropical cyclones
- Full Text
- Reviewed
- Funder
- The first author is funded under the Pacific Excellence for Research and Innovation (PERSI) scholarship of the University of the South Pacific (USP). We acknowledge the Climate and Ocean Support Program in the Pacific (COSPPac) project for funding the publication of this manuscript.
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