Evaluation of Precipitation Forecast of System: Numerical Tools for Hurricane Forecast

Heavy rainfall events, typically associated with tropical cyclones (TCs), provoke intense flooding, consequently causing severe losses to life and property. Therefore, the amount and distribution of rain associated with TCs must be forecasted precisely within a reasonable time to guarantee the prote...

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Published in:Advances in Meteorology
Main Authors: José C. Fernández-Alvarez, Albenis Pérez-Alarcon, Alfo J. Batista-Leyva, Oscar Díaz-Rodríguez
Format: Article in Journal/Newspaper
Language:English
Published: Hindawi Limited 2020
Subjects:
Online Access:https://doi.org/10.1155/2020/8815949
https://doaj.org/article/114308a1c86a408493d0b3eb45d97a0c
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spelling ftdoajarticles:oai:doaj.org/article:114308a1c86a408493d0b3eb45d97a0c 2023-05-15T17:33:47+02:00 Evaluation of Precipitation Forecast of System: Numerical Tools for Hurricane Forecast José C. Fernández-Alvarez Albenis Pérez-Alarcon Alfo J. Batista-Leyva Oscar Díaz-Rodríguez 2020-01-01T00:00:00Z https://doi.org/10.1155/2020/8815949 https://doaj.org/article/114308a1c86a408493d0b3eb45d97a0c EN eng Hindawi Limited http://dx.doi.org/10.1155/2020/8815949 https://doaj.org/toc/1687-9309 https://doaj.org/toc/1687-9317 1687-9309 1687-9317 doi:10.1155/2020/8815949 https://doaj.org/article/114308a1c86a408493d0b3eb45d97a0c Advances in Meteorology, Vol 2020 (2020) Meteorology. Climatology QC851-999 article 2020 ftdoajarticles https://doi.org/10.1155/2020/8815949 2022-12-31T07:59:29Z Heavy rainfall events, typically associated with tropical cyclones (TCs), provoke intense flooding, consequently causing severe losses to life and property. Therefore, the amount and distribution of rain associated with TCs must be forecasted precisely within a reasonable time to guarantee the protection of lives and goods. In this study, the skill of the Numerical Tool for Hurricane Forecast (NTHF) for determining rainfall pattern, average rainfall, rainfall volume, and extreme amounts of rain observed during TCs is evaluated against Tropical Rainfall Measuring Mission (TRMM) data. A sample comprising nine systems formed in the North Atlantic basin from 2016 to 2018 is used, where the analysis begins 24 h before landfall. Several statistical indices characterising the abilities of the NTHF and climatology and persistence model for rainfalls (R-CLIPER) for forecasting rain as measured by the TRMM are calculated at 24, 48, and 72 h forecasts for each TC and averaged. The model under consideration presents better forecasting skills than the R-CLIPER for all the attributes evaluated and demonstrates similar performances compared with models reported in the literature. The proposed model predicts the average rainfall well and presents a good description of the rain pattern. However, its forecast of extreme rain is only applicable for 24 h. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Advances in Meteorology 2020 1 16
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Meteorology. Climatology
QC851-999
spellingShingle Meteorology. Climatology
QC851-999
José C. Fernández-Alvarez
Albenis Pérez-Alarcon
Alfo J. Batista-Leyva
Oscar Díaz-Rodríguez
Evaluation of Precipitation Forecast of System: Numerical Tools for Hurricane Forecast
topic_facet Meteorology. Climatology
QC851-999
description Heavy rainfall events, typically associated with tropical cyclones (TCs), provoke intense flooding, consequently causing severe losses to life and property. Therefore, the amount and distribution of rain associated with TCs must be forecasted precisely within a reasonable time to guarantee the protection of lives and goods. In this study, the skill of the Numerical Tool for Hurricane Forecast (NTHF) for determining rainfall pattern, average rainfall, rainfall volume, and extreme amounts of rain observed during TCs is evaluated against Tropical Rainfall Measuring Mission (TRMM) data. A sample comprising nine systems formed in the North Atlantic basin from 2016 to 2018 is used, where the analysis begins 24 h before landfall. Several statistical indices characterising the abilities of the NTHF and climatology and persistence model for rainfalls (R-CLIPER) for forecasting rain as measured by the TRMM are calculated at 24, 48, and 72 h forecasts for each TC and averaged. The model under consideration presents better forecasting skills than the R-CLIPER for all the attributes evaluated and demonstrates similar performances compared with models reported in the literature. The proposed model predicts the average rainfall well and presents a good description of the rain pattern. However, its forecast of extreme rain is only applicable for 24 h.
format Article in Journal/Newspaper
author José C. Fernández-Alvarez
Albenis Pérez-Alarcon
Alfo J. Batista-Leyva
Oscar Díaz-Rodríguez
author_facet José C. Fernández-Alvarez
Albenis Pérez-Alarcon
Alfo J. Batista-Leyva
Oscar Díaz-Rodríguez
author_sort José C. Fernández-Alvarez
title Evaluation of Precipitation Forecast of System: Numerical Tools for Hurricane Forecast
title_short Evaluation of Precipitation Forecast of System: Numerical Tools for Hurricane Forecast
title_full Evaluation of Precipitation Forecast of System: Numerical Tools for Hurricane Forecast
title_fullStr Evaluation of Precipitation Forecast of System: Numerical Tools for Hurricane Forecast
title_full_unstemmed Evaluation of Precipitation Forecast of System: Numerical Tools for Hurricane Forecast
title_sort evaluation of precipitation forecast of system: numerical tools for hurricane forecast
publisher Hindawi Limited
publishDate 2020
url https://doi.org/10.1155/2020/8815949
https://doaj.org/article/114308a1c86a408493d0b3eb45d97a0c
genre North Atlantic
genre_facet North Atlantic
op_source Advances in Meteorology, Vol 2020 (2020)
op_relation http://dx.doi.org/10.1155/2020/8815949
https://doaj.org/toc/1687-9309
https://doaj.org/toc/1687-9317
1687-9309
1687-9317
doi:10.1155/2020/8815949
https://doaj.org/article/114308a1c86a408493d0b3eb45d97a0c
op_doi https://doi.org/10.1155/2020/8815949
container_title Advances in Meteorology
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