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We evaluated the performance of the Thornthwaite (ThW) method using two gridded climate datasets to estimate monthly average daily potential evapotranspiration (PET). The PET estimated from two gridded series were compared to PET and to reference evapotranspiration (ETo) determined, respectively, through the ThW and Penman-Monteith model parameterized on Food and Agriculture Organization–Irrigation and Drainage paper No 56 (PM-FAO56) using data from weather stations. The PET by ThM was based on monthly air temperature series (1961–2010) from two gridded datasets (Global Historical Climatology Network-GHCN and University of Delaware-UDel) and 21 weather stations of the National Institute of Meteorology (INMET) located in Southeastern Brazil. The ETo PM-FAO56 used monthly climate series (1961–2010) on sunshine duration, air temperature, relative humidity, and wind speed from weather stations of the INMET. The PET estimated using UDel gridded series was better overall performance than the GHCN series. Differences in altitude, latitude, and longitude were the main geographic factors determining the performance of the PET estimates using gridded climate series. Depending on the factors, some locations require bias correction, especially locations more than 10 km away from the grid point. The gridded datasets are an alternative for locations without climatic series data or with low-quality non-continuous data series. [ABSTRACT FROM AUTHOR]

The study of climatic variables in large scales with surface meteorological stations is limited due to the low density of these stations in many regions, possible sources of errors related to missing data, and uncertainties about the calibration sensors. Global gridded data (GD) systems can minimize these problems. Thus, studies that validate GDs with "ground truth" are important for several applications such as climate change. The objective of this study was to compare long series of surface data with 10-day estimates of average air temperature (T) and precipitation (P) using data from the European Center for Medium-Range Weather Forecast (ECMWF) and the National Aeronautics and Space Administration (NASA) for important agricultural locations in the states of Minas Gerais and São Paulo in Brazil. Despite the different spatial resolutions between ECMWF and NASA, the purpose of this paper was to evaluate the two data sources as they are readily available. The GD performance was evaluated by linear regression analysis. Analyses were performed for each meteorological variable for entire years and separated by seasons. The estimates of T from both ECMWF and NASA systems were accurate with the minimum Willmott concordance index (d) and RMSEp of 0.86, 0.37 °C, respectively, and precision with R2 0.61. The estimates of P had a minimum R2, d, and RMSEp of 0.48, 0.79, 2.15 °C respectively. The decreasing orders of (R2) were autumn > winter > spring > summer for T and winter > autumn > spring > summer for P, varying from 0.93 to 0.61 for T and from 0.77 to 0.48 for P. [ABSTRACT FROM AUTHOR]