dc.contributor.author | Tu'uholoaki, Moleni | |
dc.contributor.author | Espejo Hermosa, Antonio | |
dc.contributor.author | Singh, Awnesh | |
dc.contributor.author | Damlamian, Herve | |
dc.contributor.author | Wandres, Moritz | |
dc.contributor.author | Chand, Savin | |
dc.contributor.author | Méndez Incera, Fernando Javier | |
dc.contributor.author | Fa'anunu, Ofa | |
dc.contributor.other | Universidad de Cantabria | es_ES |
dc.date.accessioned | 2023-06-27T14:10:59Z | |
dc.date.available | 2023-06-27T14:10:59Z | |
dc.date.issued | 2023-06 | |
dc.identifier.issn | 0930-7575 | |
dc.identifier.issn | 1432-0894 | |
dc.identifier.uri | https://hdl.handle.net/10902/29392 | |
dc.description.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. | es_ES |
dc.description.sponsorship | The first author is funded under the Pacific Excellence for Research and Innovation (PERSI) scholarship of the University of the South Pacific (USP). | es_ES |
dc.format.extent | 16 p. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer | es_ES |
dc.rights | © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.source | Climate Dynamics, 2023, 60(11-12), 3353-3368 | es_ES |
dc.subject.other | ENSO types | es_ES |
dc.subject.other | Sea surface temperatures | es_ES |
dc.subject.other | K-means clustering algorithm | es_ES |
dc.subject.other | Principal component analysis | es_ES |
dc.subject.other | Tropical cyclones | es_ES |
dc.title | Clustering tropical cyclone genesis on ENSO timescales in the Southwest Pacific | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.publisherVersion | https://doi.org/10.1007/s00382-022-06497-6 | es_ES |
dc.rights.accessRights | openAccess | es_ES |
dc.identifier.DOI | 10.1007/s00382-022-06497-6 | |
dc.type.version | publishedVersion | es_ES |