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Abstract The demand for meteorological gridded datasets has increased within the last few years to inform studies such those in climate, weather, and agriculture. These studies require those data to be readily usable in standard formats with continuous spatial and temporal coverage. Since 2016, Brazil has a daily gridded meteorological data set with spatial resolution of 0.25° × 0.25° from January 1, 1980 to December 31, 2013 which was well received by the community. The main objective of this work is to improve the Brazilian meteorological data set. We do this by increasing the resolution of the minimum and maximum temperature (Tmax and Tmin) gridded interpolations from 0.25° × 0.25° to 0.1° × 0.1° by incorporating data on topographic relief, and increasing the time period covered (January 1, 1961–July 31, 2020). Besides Tmax and Tmin, we also gridded precipitation (pr), solar radiation (Rs), wind speed (u2), and relative humidity (RH) using observed data from 11,473 rain gauges and 1,252 weather stations. By means of ranked cross‐validation statistics, we selected the best interpolation among inverse distance weighting and angular distance weighting methods. We determined that interpolations for Tmax and Tmin are improved by using the elevation of a query point, that accounts for topographic relief, and a temperature lapse rate. Even though this new version has ≈25 years more data relative to the previous one, statistics from cross‐validation were similar. To allow researchers to assess the performance of the interpolation relative to station data in the area, we provide two types of gridded controls.
Xavier et al. (Mon,) studied this question.