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Given the importance of climate for society at different scales, such as local, regional, and global scales, the analysis of trends of climatic elements improves the assessment of projections and variations, aiding in the design of policies focused on processes of adaptation to and mitigation of the effects of climate change. The aim of this study was to detect mean air temperature trends in the SertAo Paraibano mesoregion in Brazil by constructing temperature series with observed data provided by the Brazilian National Institute of Meteorology (INMET) collected in the localities of Patos and SAo Goncalo and with data estimated using Estima_T software to study the spatial and temporal distribution of the mean air temperature of seven localities in the SertAo Paraibano mesoregion: agua Branca, Aguiar, Coremas, Patos, Princesa Isabel, SAo Goncalo, and Teixeira. The temperature series with observed and estimated data were compared, showing the variability of using temperature estimates to overcome the lack of meteorological stations in the study area. Descriptive analysis shows low data dispersion in relation to the annual mean values and, therefore, low variability. The monthly mean temperature pattern was similar in all localities and December was always the warmest month, whereas July was the coldest, both in the estimated and observed data series. The non-parametric Mann-Kendall test indicated that estimated series show trends of significant increases in mean air temperature, in annual, biannual, quarterly, and monthly periods, in all localities. Sen's slope results indicate significant increases in temperature from 0.008 to 0.011 degrees C/year.