Modelagem espaço-temporal de variáveis climatológicas no estado da Bahia: uma abordagem com janelas deslizantes

• Ano de defesa: 2021
• Autor(a) principal: Ferreira, Elvira Catiana de Oliveira Santos
• Orientador(a): Silva Filho, Aloísio Machado da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual de Feira de Santana
• Programa de Pós-Graduação: Mestrado em Modelagem em Ciência da Terra e do Ambiente
• Departamento: DEPARTAMENTO DE CIÊNCIAS BIOLÓGICAS
• País: Brasil
• Palavras-chave em Português: Autocorrelação; Correlação cruzada; Velocidade do vento; Radiação solar
• Palavras-chave em Inglês: Self-correction; Cross correlation; Wind speed; Solar radiation
• Área do conhecimento CNPq: METEOROLOGIA::CLIMATOLOGIA
• Link de acesso: http://tede2.uefs.br:8080/handle/tede/1444

The understanding of climate through the modeling of climatological variables has beensomething recurrent among scientists. In this context, it is possible to find in the literaturestudies that aim to understand the behavior of such variables as a function oftime and/or space. This research aims to characterize the time series of climatic variables,wind speed and solar radiation, of some meteorological stations in Bahia, from dataprovided by the National Institute of Meteorology (INMET) in the period from 2009 to2018. By methodological option, we elected the meteorological stations headquartered inthe municipalities of Barreiras, Feira de Santana, Guanambi, Salvador e Vit´oria da Conquista.To meet the objective, was applied, mainly, the statistical method of analysis oftime series Detrended Fluctuation Analysis (DFA) and the Detrended Cross-Correlation Coeffcient (pDCCA) both with the sliding windows procedure. Our findings identified apredominance of persistent behavior (↵>0,50) and statistically significant in wind speedand solar radiation in the evaluated stations for either a 365 days window (w=365) ora 1000 days window (w=1000). Regarding the level of cross-correlation between wind speed and solar radiation, our results classified the correlations as weak, moderate and strong depending on the season, scale (n) and window (w) evaluated. It is hoped that our findings can be useful in understanding the dynamics of wind and/or solar radiation, as well as in understanding activities related to alternative generation of electricity through solar and/or wind sources, agroclimatic studies, among others.