Climate data are essential for most simulation models and analytical studies in the fields of hydrology, ecology, and other environmental sciences. In many regions of the world, the absence of long-term and high-quality measured climate data has proven a major limitation to the application of simulation models and carrying out analytical studies. Recent studies indicate that gridded climate data could provide a reliable alternative to measured climate data. The accuracy of a new global gridded climate dataset (i.e., TerraClimate) was evaluated under different climate types across Iran. With a very high spatial resolution (~ 4 km), TerraClimate provides a monthly gridded climate dataset, offering a wide range of climate variables. Monthly climate data, collected from 40 weather stations in Iran between 1984 and 2018, were compared to data from TerraClimate. TerraClimate showed a very strong performance for solar radiation and maximum and minimum temperatures, with normalized root mean square error (NRMSE) values of 5.8%, 3.4%, and 4.9%, respectively. For precipitation, the accuracy was slightly lower with an overall NRMSE of 8.3%. The performances of TerraClimate for vapor pressure and wind speed were relatively weak, with NRMSE values of 12.9% and 25.1%, respectively. Overall, TerraClimate provided dependable data — particularly for monthly solar radiation, maximum and minimum temperatures, and precipitation — over the study area. Further studies over a more diverse set of environments are important to confirm and extend the present findings.

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