Improving maps of daily air temperature considering the effects of topography: Data from Esprito Santo, Brazil (2007-2020)

Mapping air temperature is essential for climate studies and its application in environmental, forest, and agri-cultural sciences, among others. This study aimed to spatialize daily air temperature data, creating a database corrected by the effect of relief. This study was performed in the state of Espirito Santo, Southeastern Brazil, which has an altitude range of 2892 m from the coast to the highest point in Serra do Capara ' o. Meteorological data were collected from 22 meteorological stations. The potential temperature equation and adiabatic lapse rate were used to estimate air temperature considering the effect of relief. These methods were compared with the inverse distance weighting (IDW) interpolator to evaluate the gain obtained by including topographic infor-mation in the temperature estimation. The performance of methods was evaluated by cross-validation, using the coefficient of determination (R2), bias, and mean absolute error (MAE). The method with the best performance in the spatialization of air temperature data was obtained by adjusting the temperature data for the same altitude condition, using the environmental lapse rate (-6.5 degrees C km-1) and the IDW interpolator to spatialize data. Finally, interpolated temperature values were adjusted for the original terrain altitude (-6.5 degrees C km-1), using the altitude existing in each pixel of a digital elevation model. This method provided a gain of 51% in the reduction of MAE values compared with the IDW interpolator, which does not consider the effect of relief. It was used to spatialize daily air temperature data (maximum, average, and minimum) for the entire territory of Espirito Santo, Brazil, with 500-m spatial resolution.