The Wind Regime over the Brazilian Southeast: Spatial and Temporal Characterization Using Multivariate Analysis

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 (G1-G4) were identified; G4 presented the highest magnitudes of wind speed (wind speed >5 m center dot s(-1), with maxima of 7.2 m center dot s(-1)). Seasonal well-defined minima (March-June) and maxima (July-October) were observed only for G2 and G3. The systems South Atlantic Subtropical Anticyclone (SASA), Frontal Systems (FS), and the South Atlantic Convergence Zone (SACZ) influenced these groups. In addition, the mesoscale meteorological systems likely influence other groups such as breezes from land/sea (G1, G3, and G4), lakes (G2 and G3), and valley/mountain (G2 and G3). The topography had a strong influence on G3, mainly due to the mountain ranges of Mantiqueira and Serra do Mar and Paraiba River valley. Dominant wind directions were E, N/NE, and NW, associated with SASA, in addition to S and SE/SW, influenced by FS and SACZ. The wind speed range of 1.4-3.9 m center dot s(-1) was dominant in all groups, except for G4 (range of 2.4-5.5 m center dot s(-1)). According to PCA analysis, two PCs are enough to explain the wind pattern in the SEB with 69.9% of the total variance explained. The surface roughness accounted for 29% of the total variance explained in PC1. The latitude (37.6%) and distance to the coast (30.8%) are the most important variables for PC2. Region's physiography and meteorological systems strongly influenced the wind regime over the Brazilian Southeast. The assessment of wind regime variability presented in this work is expected to support public policies on renewable energy applications, air pollution, and climate change mitigation.