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Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters
In this report, the development of a Dynamical Statistical Analog Ensemble Forecast model for landfalling typhoon disasters (LTDs) and some applications over coastal China are described. This model consists of the following four elements: (i) obtaining the forecast track of a target landfalling typh...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533520/ https://www.ncbi.nlm.nih.gov/pubmed/37758776 http://dx.doi.org/10.1038/s41598-023-43415-0 |
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author | Wu, Caiming Ren, Fumin Zhang, Da-Lin Zhu, Jing McBride, John Leonard Chen, Yuxu |
author_facet | Wu, Caiming Ren, Fumin Zhang, Da-Lin Zhu, Jing McBride, John Leonard Chen, Yuxu |
author_sort | Wu, Caiming |
collection | PubMed |
description | In this report, the development of a Dynamical Statistical Analog Ensemble Forecast model for landfalling typhoon disasters (LTDs) and some applications over coastal China are described. This model consists of the following four elements: (i) obtaining the forecast track of a target landfalling typhoon, (ii) constructing its generalized initial value (GIV), (iii) identifying its analogs based on the GIV, and (iv) assembling typhoon disasters of the analogs. Typhoon track, intensity, and landfall date are introduced in GIV at this early development stage. The pre-assessment results show that the mean threat scores of two important damage levels of LTDs reach 0.48 and 0.55, respectively. Of significance is that most of the damage occurs near the typhoon centers around the time of landfall. These results indicate the promising performance of the model in capturing the main damage characteristics of typhoon disasters, which would help coastal community mitigate damage from destructive typhoons. |
format | Online Article Text |
id | pubmed-10533520 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105335202023-09-29 Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters Wu, Caiming Ren, Fumin Zhang, Da-Lin Zhu, Jing McBride, John Leonard Chen, Yuxu Sci Rep Article In this report, the development of a Dynamical Statistical Analog Ensemble Forecast model for landfalling typhoon disasters (LTDs) and some applications over coastal China are described. This model consists of the following four elements: (i) obtaining the forecast track of a target landfalling typhoon, (ii) constructing its generalized initial value (GIV), (iii) identifying its analogs based on the GIV, and (iv) assembling typhoon disasters of the analogs. Typhoon track, intensity, and landfall date are introduced in GIV at this early development stage. The pre-assessment results show that the mean threat scores of two important damage levels of LTDs reach 0.48 and 0.55, respectively. Of significance is that most of the damage occurs near the typhoon centers around the time of landfall. These results indicate the promising performance of the model in capturing the main damage characteristics of typhoon disasters, which would help coastal community mitigate damage from destructive typhoons. Nature Publishing Group UK 2023-09-27 /pmc/articles/PMC10533520/ /pubmed/37758776 http://dx.doi.org/10.1038/s41598-023-43415-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wu, Caiming Ren, Fumin Zhang, Da-Lin Zhu, Jing McBride, John Leonard Chen, Yuxu Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters |
title | Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters |
title_full | Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters |
title_fullStr | Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters |
title_full_unstemmed | Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters |
title_short | Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters |
title_sort | development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533520/ https://www.ncbi.nlm.nih.gov/pubmed/37758776 http://dx.doi.org/10.1038/s41598-023-43415-0 |
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