Delineation of the Topoclimates of Eastern Cuba by Local Weather Patterns and Unsupervised Machine Learning
Abstract In this study, the principles of complex climatology were applied to delineate topoclimates in the mountains of eastern Cuba. A regional numerical weather model, driven by reanalysis, was used to obtain temperature patterns at a resolution of 0.6 km. Unsupervised machine learning techniques...
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| Language: | English |
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Sociedade Brasileira de Meteorologia
2025-02-01
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| Series: | Revista Brasileira de Meteorologia |
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| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862025000100202&lng=en&tlng=en |
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| author | Arisleidys Peña-De la Cruz Ricardo Delgado-Téllez Yusmira Savón-Vaciano Mingtao Ding |
| author_facet | Arisleidys Peña-De la Cruz Ricardo Delgado-Téllez Yusmira Savón-Vaciano Mingtao Ding |
| author_sort | Arisleidys Peña-De la Cruz |
| collection | DOAJ |
| description | Abstract In this study, the principles of complex climatology were applied to delineate topoclimates in the mountains of eastern Cuba. A regional numerical weather model, driven by reanalysis, was used to obtain temperature patterns at a resolution of 0.6 km. Unsupervised machine learning techniques were then utilized to identify weather types based on temperature during rainy and less rainy periods, as well as geographical location. This analysis was supplemented with historical precipitation and geographical data to identify 23 topoclimates in the study area. The methods allowed for the estimation of topoclimate identification errors and provided insights into the representativeness of surface meteorological stations for the study area. The results showed that the rainfall distribution of the identified topoclimates was consistent with that of local climate-forming factors and previous research. Furthermore, new insights into the climatological rainfall characteristics of the lower and middle heights of the mountains in eastern Cuba were identified. |
| format | Article |
| id | doaj-art-2574a88fd2964643a6db60f22a137283 |
| institution | Kabale University |
| issn | 1982-4351 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Sociedade Brasileira de Meteorologia |
| record_format | Article |
| series | Revista Brasileira de Meteorologia |
| spelling | doaj-art-2574a88fd2964643a6db60f22a1372832025-02-04T07:41:36ZengSociedade Brasileira de MeteorologiaRevista Brasileira de Meteorologia1982-43512025-02-014010.1590/0102-778640230023Delineation of the Topoclimates of Eastern Cuba by Local Weather Patterns and Unsupervised Machine LearningArisleidys Peña-De la Cruzhttps://orcid.org/0000-0003-3934-5527Ricardo Delgado-Téllezhttps://orcid.org/0000-0002-7475-1064Yusmira Savón-Vacianohttps://orcid.org/0000-0002-9640-8478Mingtao Dinghttps://orcid.org/0000-0003-4839-7337Abstract In this study, the principles of complex climatology were applied to delineate topoclimates in the mountains of eastern Cuba. A regional numerical weather model, driven by reanalysis, was used to obtain temperature patterns at a resolution of 0.6 km. Unsupervised machine learning techniques were then utilized to identify weather types based on temperature during rainy and less rainy periods, as well as geographical location. This analysis was supplemented with historical precipitation and geographical data to identify 23 topoclimates in the study area. The methods allowed for the estimation of topoclimate identification errors and provided insights into the representativeness of surface meteorological stations for the study area. The results showed that the rainfall distribution of the identified topoclimates was consistent with that of local climate-forming factors and previous research. Furthermore, new insights into the climatological rainfall characteristics of the lower and middle heights of the mountains in eastern Cuba were identified.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862025000100202&lng=en&tlng=entopoclimatestropical islandscomplex climatologymachine learningautoorganized networks |
| spellingShingle | Arisleidys Peña-De la Cruz Ricardo Delgado-Téllez Yusmira Savón-Vaciano Mingtao Ding Delineation of the Topoclimates of Eastern Cuba by Local Weather Patterns and Unsupervised Machine Learning Revista Brasileira de Meteorologia topoclimates tropical islands complex climatology machine learning autoorganized networks |
| title | Delineation of the Topoclimates of Eastern Cuba by Local Weather Patterns and Unsupervised Machine Learning |
| title_full | Delineation of the Topoclimates of Eastern Cuba by Local Weather Patterns and Unsupervised Machine Learning |
| title_fullStr | Delineation of the Topoclimates of Eastern Cuba by Local Weather Patterns and Unsupervised Machine Learning |
| title_full_unstemmed | Delineation of the Topoclimates of Eastern Cuba by Local Weather Patterns and Unsupervised Machine Learning |
| title_short | Delineation of the Topoclimates of Eastern Cuba by Local Weather Patterns and Unsupervised Machine Learning |
| title_sort | delineation of the topoclimates of eastern cuba by local weather patterns and unsupervised machine learning |
| topic | topoclimates tropical islands complex climatology machine learning autoorganized networks |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862025000100202&lng=en&tlng=en |
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