Crop models are sensitivi by the climatic spatial scale for performing thesimulation. Several crop simulation studies use mesoescale climate database (20-50 km), where topography is neglected. We develop a method to select the optimal climate grid cell resolution (OCGR) based on winter wheat (Triticum aestivum L) yield simulations in complex topographical zones (CTZ) and flat topographical zones (FTZ) in the Araucan a Region of Chile (37 35' and 39 degrees 37' S - 73 degrees 31' and 71.31' W). The OCGR was estimated from the simulated crop yield (CERES-DSSAT) using a semivariogram to compute the distance, which minimize yield differences with respect to its neighbors. Climate variables were obtained from DGF-PRECIS (25 km) downscaled to a fine resolution of 1 km through Precipitation characterization with Auto-Searched Orographic and Atmospheric (PCASOA). Climate variables were calibrated and validated from 56 in-situ meteorological stations between 1961 and 1991 and the yield was validated from field experiments. The crop simulation presented no significant differences (3.0 +/- 0.3-3.0 +/- 0.1 Mg ha(-1)) compared to field experiments. Increasing the resolution improves the crop simulation reducing the RSME from 0.8 to 0.32 Mg ha(-1) The OCGR estimated averaged < 7 km for CTZ, whereas it was > 25 km for FTZ. Our approach can be applied for similar crops and complex topographical zones.