Classificação climática aplicada ao Bioma Cerrado
Ano de defesa: | 2019 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Uberlândia
Brasil Programa de Pós-graduação em Geografia |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | https://repositorio.ufu.br/handle/123456789/26606 http://dx.doi.org/10.14393/ufu.te.2019.2199 |
Resumo: | Climate classification is considered a basic study for aiding environmental and economic planning, defining the climate on several regions. The classification models allow a synthetic understanding of the main characteristics of a region. This thesis proposes a new approach to the mapping of climatic units to the Brazilian Cerrado nuclear area, considering the average temperature of the coldest month, the number of dry months, the influence of atmospheric systems and their effects on rainfall, the occurrence of cold fronts and possibility of frost. The proposed climate classification system has a hierarchy divided into Domains, Subdomains, Types, Subtypes and Meso/Topoclimas. To determine the climatic units, data from 456 rainfall collection stations of the National Water Agency (ANA), 41 stations of the National Institute of Meteorology (INMET) were used. The CHELSA algorithm was used to delimit the isotherms of the air temperature maps, with a better distribution of the data in regions with no seasons. Four climatic domains were identified in the study area: Equatorial, Tropical, Mild Tropical and Subtropical; these are subdivided into climatic subdomains (with number of dry months) and climatic types (location in Brazilian territory). The definition of the climatic units of the Cerrado provides important subsidies for new regional studies in climatology (climatology of detail). This new climate classification system is improved due to the large amount of historical data, and can be used in environmental, didactic and agricultural analysis. |