AbstractEstimation of evapotranspiration, representing a highly sensitive variable to global warming, is often required in water resources and agricultural studies. This study explores the possible effects of climate change on evapotranspiration (ETo) across Iran. The ETo was computed using the Penman‐Monteith Temperature (PMT) method that requires only minimum and maximum temperature (Tmin and Tmax), provided by the NASA Earth Exchange Global Daily Downscaled Projections dataset (NEX‐GDDP) with a 0.25° × 0.25° spatial resolution. Accuracy of the NEX‐GDDP Tmin and Tmax were evaluated against ground truth observations at 41 synoptic weather stations distributed across the country using a set of statistical measures, including the coefficient of determination (R2) and Nash‐Sutcliffe Efficiency (NSE). Similarly, the PMT estimated evapotranspiration based on the NEX‐GDDP Tmin and Tmax (ETo‐GDDP) were statistically evaluated against the ETo computed with observed variables at selected stations (ETo‐obs). Then, at each grid cell, the 45‐years ETo‐GDDP time series was partitioned into three 15‐years subperiods such that the differences between three subperiods were computed and inter‐compared. Furthermore, annual, seasonal, and monthly ETo time series trends of each cell were evaluated using the Mann–Kendall trend test (MK) while the corresponding change rates were estimated using Theil–Sen's slope estimator (TSSE). The results demonstrated a good agreement between ETo‐GDDP and ETo‐obs with R2 greater than 0.8 and NSE greater than 0.7 in 90.2% and 65.8% of the stations, respectively. The maps of differences between the three subperiods showed negligible changes in ETo between 1975–1990 and 1950–1975 subperiods. The spatial patterns of annual and seasonal MK statistics showed a significant increasing trend in most parts of Iran. On seasonal scale, the highest and lowest ETo changes were observed in spring (0.00035–0.0045) and in autumn (0.0005–0.0015), respectively.