EXPLORING CLIMATIC PATTERNS AMONG BRAZILIAN CAPITALS

This study aims to examine the patterns of climatic variables and delineate climatically homogeneous regions among Brazilian capitals using Principal Component Analysis (PCA) and clustering techniques. Annual climate data from 26 state capitals and the Federal District of Brazil were analyzed, covering the period from 1958 to 2022, representing different regions of the country. The PCA results revealed that the first three principal components accounted for 91.8% of the total data variability. Four climatically homogeneous regions were identified: the East region, the Northeast region, the North region and another region that comprises the rest of the country. Cluster Analysis (CA) also confirmed the formation of four homogeneous groups among municipalities based on climatic variables. The analysis of spatial distribution showed significant variations in annual climate variables between Brazilian capitals, with maximum values observed for maximum and minimum temperatures, precipitation, wind speed, relative humidity, evapotranspiration and soil moisture. These findings contribute to a deeper understanding of climate variability in Brazilian capitals and provide a basis for future studies on climate dynamics and regional impacts. Keywords: Principal Component Analysis, Cluster Analysis, Multivariate Analysis; Biplot

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Publication Details

Journal
Mercator
Published
2024-10-28
DOI
https://doi.org/10.4215/rm2024.e23028
Citations
4
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
1.13
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article

EXPLORING CLIMATIC PATTERNS AMONG BRAZILIAN CAPITALS

Elias Silva de Medeiros, Amaury de Souza
4 citations
Mercator
Land Use and Ecosystem Services
1.13
article

EXPLORING CLIMATIC PATTERNS AMONG BRAZILIAN CAPITALS

Elias Silva de Medeiros, Amaury de Souza
article en
4 citations

Abstract

This study aims to examine the patterns of climatic variables and delineate climatically homogeneous regions among Brazilian capitals using Principal Component Analysis (PCA) and clustering techniques. Annual climate data from 26 state capitals and the Federal District of Brazil were analyzed, covering the period from 1958 to 2022, representing different regions of the country. The PCA results revealed that the first three principal components accounted for 91.8% of the total data variability. Four climatically homogeneous regions were identified: the East region, the Northeast region, the North region and another region that comprises the rest of the country. Cluster Analysis (CA) also confirmed the formation of four homogeneous groups among municipalities based on climatic variables. The analysis of spatial distribution showed significant variations in annual climate variables between Brazilian capitals, with maximum values observed for maximum and minimum temperatures, precipitation, wind speed, relative humidity, evapotranspiration and soil moisture. These findings contribute to a deeper understanding of climate variability in Brazilian capitals and provide a basis for future studies on climate dynamics and regional impacts. Keywords: Principal Component Analysis, Cluster Analysis, Multivariate Analysis; Biplot

MercatorVol. 23(2024)
Universidade Federal de Mato Grosso do Sul (BR), Universidade Federal de Lavras (BR)
Climate action
Openalex Percentile: Top 23%
Land Use and Ecosystem Services
1.13
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EXPLORING CLIMATIC PATTERNS AMONG BRAZILIAN CAPITALS — Elias Silva de Medeiros, Amaury de Souza · Mercator (2024) | TGRS Research Map | TGRS