Temperature plays a critical role for plant development and growth, and maximum and minimum temperature are two of the key inputs for the application of crop simulation models. The lack of good observed weather data is a challenging issue in many agricultural regions. Recent studies have used gridded weather data as an alternative to observed weather data for application in agricultural systems modeling. The aim of this study was to identify the most appropriate gridded temperature data (GTD) to be applied in crop simulation modeling. Therefore, nine global GTDs were evaluated for rainfed and irrigated wheat production for six sites across Iran using the Cropping System Model (CSM)-NWheat model. The GTDs included AgCFSR, AgERA5, AgMERRA, CPC, GLDAS, NCEP RII, PGF, POWER, and S14FD. The observed data from the weather stations located in the selected sites were used to evaluate the GTDs. To increase the robustness of the final results, six different rainfed and irrigated wheat cultivars were considered for modeling. Results showed that AgCFSR, AgMERRA, PGF, and AgERA5 had the best performance, while NCEP and GLDAS had the weakest performance. Using AgCFSR and AgERA5, grain yield was simulated with NRMSE ≤ 11.5% and NSE ≥ 0.7. The overall performance of AgCFSR, AgMERRA, and PGF was better that for AgERA5; however, these three GTDs are not recommended for agricultural modeling applications, especially if current weather data are needed. AgCFSR and AgMERRA are only available until 2010, and PGF is available until 2016. Therefore, AgERA5 can be recommended for temperature-related agricultural simulations for the study area in Iran and similar environmental regions, due to its overall performance compared to the observed temperature data and with availability since 1979 to present. Further studies are necessary to assess differences in performance for various environments.

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