@Article{CorreiaFoSoOlSaLyZeCu:2022:SpTeCh,
               author = "Correia Filho, Washington Luiz F{\'e}lix and Souza, Pedro 
                         Henrique de Almeida and Oliveira-J{\'u}nior, Jos{\'e} Francisco 
                         de and Santiago, Dimas de Barros and Lyra, Gustavo Bastos and 
                         Zeri, Marcelo and Cunha-Zeri, Gisleine da Silva",
          affiliation = "{Universidade Federal de Alagoas (UFAL)} and {Universidade Federal 
                         de Alagoas (UFAL)} and {Universidade Federal de Alagoas (UFAL)} 
                         and {Universidade Federal de Campina Grande (UFCG)} and 
                         {Universidade Federal Fluminense (UFF)} and {Centro Nacional de 
                         Monitoramento e Alertas de Desastres Naturais (CEMADEN)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "The wind regime over the Brazilian Southeast: Spatial and temporal 
                         characterization using multivariate analysis",
              journal = "International Journal of Climatology",
                 year = "2022",
               volume = "42",
               number = "3",
                pages = "1767--1788",
             keywords = "applied statistics, climate variability, mesoscale circulations, 
                         meteorological systems, wind regime.",
             abstract = "The characterization of spatial and temporal patterns of wind is 
                         essential to several sectors, including energy, urban climate, and 
                         applied meteorology. However, few studies describe the regional 
                         characteristics of the wind regime over the Brazilian Southeast 
                         (SEB), the most developed and populated part of the country. The 
                         objectives of the current work were (a) to assess the spatial 
                         patterns of the wind regime using cluster analysis (CA) and (b) to 
                         apply principal components analysis (PCA) to investigate which 
                         meteorological systems influence the spatial and temporal patterns 
                         of the wind regime. The dataset consisted of wind speed and 
                         direction from 70 automatic weather stations with records from 
                         2008 to 2019. According to the CA method, four groups of 
                         homogeneous wind speed (G1G4) were identified; G4 presented the 
                         highest magnitudes of wind speed (wind speed >5 m·s\&.",
                  doi = "https://doi.org/10.1002/joc.7334",
                  url = "http://dx.doi.org/https://doi.org/10.1002/joc.7334",
                 issn = "0899-8418",
                label = "self-archiving-INPE-MCTIC-GOV-BR",
             language = "en",
           targetfile = "2022_CORREIA_the wind regime over the Brazilian Southeast_Spatial 
                         and temporal characterization using multivariate analysis.pdf",
        urlaccessdate = "01 jun. 2024"
}