<p>Climate is a key driver of most environmental processes; consequently, climatic data are essential for analytical and modeling studies in environmental disciplines such as agriculture, ecology, hydrology, and water resources. However, the scarcity of high-quality, long-term climatic observations remains a major challenge in many parts of the world, limiting the reliability of environmental assessments and modeling efforts. Recent studies have demonstrated that gridded climate datasets can serve as dependable alternatives to in situ measurements. In this study, the accuracy of the high-resolution (~ 1&#xa0;km) gridded climate dataset CHELSA, which provides a comprehensive suite of climatic variables, was evaluated across Iran at a monthly time step. Monthly observations from 77 synoptic stations for the period 1995–2014, corresponding to the historical baseline defined in the IPCC Sixth Assessment Report, were compared with CHELSA-derived values. The results indicate that CHELSA performs strongly for maximum and minimum temperatures, precipitation, and solar radiation, with normalized root mean square error (<i>NRMSE</i>) values of 5.2%, 6.9%, 5.2%, and 10.4%, respectively. For potential evapotranspiration, CHELSA exhibited moderate error (<i>NRMSE</i> = 21.6%), whereas relative humidity and wind speed showed comparatively higher errors, with <i>NRMSE</i> values of 53.1% and 55.8%, respectively. The errors in relative humidity and potential evapotranspiration could be further reduced through additional bias-correction procedures. Overall, CHELSA proved to be a reliable, high-resolution climate dataset suitable for climate-dependent applications in regions with limited meteorological observations. Further studies are warranted to evaluate CHELSA performance across a broader range of climatic and environmental conditions worldwide.</p>