Crop models are being used to estimate the impacts of climate change projections in the agricultural sector. The monthly GCM projections have to be downscaled to daily values to be used as input for crop models. Several methods have being proposed: the delta change method, weather generators, geospatial weather generators and bootstrapping. This paper compares the performance of these methods in several counties of Iowa. The study area was selected for three reasons: The importance of cropping corn in the region, because climate has changed in the last decades, and because it is projected a severe climate change in the region. The paper uses Reanalysis data as retrospective projected climate from a GCM. The methods are used to downscaled the monthly values to daily values and used in the CERES-Maize model to compare the impact in corn production. These results are compared to their corresponding observed data at weather station level in order to measure the predictability skills of each method.