Networks analysis of Brazilian climate data based on the DCCA cross-correlation coefficient

decades (https://portal.inmet.gov.br/). An advantage of the method used in this study, when compared to the average values of INMET in the period between 01/01/1991 and 31/12/2020, is the self-affinity of the scale. While INMET computes the mean variables from month to month, the DFA computes hour-to-hour variations for small, medium, and large scales. The contributions not only raise the possibility of discussions associated with scientific communi- cation but can also be useful to understand and collaborate with various economic activities, agribusiness, the energy generation sector (hydraulic, wind, and/or solar), sports activities and leisure, and, above all, urban planning, among others. Regarding the cross-correlation coefficient ρDCCA, we observed the influence of the correla- tion by region. Important aspects were verified by three characteristic behaviors in the scale and variation in the fluctuation by region. This type of correlation study was also verified by Fig 8. Network representation of the environmental variable air temperature, considering the 27 Brazilian state capitals as vertices and the edges defined by the DCCA cross-correlation coefficient between pairs of Brazilian state capitals. Only edges associated with the top 10% DCCA cross-correlation coefficients between objects were depicted. The five colors in the vertices correspond to the state capitals in each of the five Brazilian regions. Box sizes of 13–one day, 1261–97 days, and 3328–256 days are depicted, from left to right. https://doi.org/10.1371/journal.pone.0290838.g008

Fig 9. Network representation of the environmental variable relative air humidity, considering the 27 Brazilian state capitals as vertices and the edges defined by the DCCA cross-correlation coefficient between pairs of Brazilian state capitals. Only edges associated with the top 10% DCCA cross-correlation coefficients between objects were depicted. The five colors in the vertices correspond to the state capitals in each of the five Brazilian regions. Box sizes of 13–one day, 1261–97 days, and 3328–256 days are depicted, from left to right. https://doi.org/10.1371/journal.pone.0290838.g009 PLOS ONE Networks analysis of Brazilian climate data based on the DCCA cross-correlation coefficient PLOS ONE | https://doi.org/10.1371/journal.pone.0290838 September 15, 2023 14 / 18