The spatial resolution of many current climate forecasts and scenarios require that new procedures be developed and implemented to provide the spatial and temporal information required for agricultural adaptation studies. Tools are required to facilitate the recalculation of agroclimate resource indices and to use input data with more limited temporal and spatial resolution. Models and indices such as growing degree days, rely on a daily time step which are frequently not available in forecasts of seasonal climate or climate change scenarios. There is growing interest in the potential usefulness of weather generators in climate change studies. Weather generators have been used to downscale large-scale climate change data produced with general circulation models to estimate regional climate changes. They have been used to examine the effect of climate variability on estimates of crop yields from the models. In this paper, the applicability of weather data generators will be examined as a tool to estimate agroclimate resources using indices derived from selected climate change scenarios. The use of weather generators will be assessed in relation to other approaches that have been used. These approaches frequently make use of historical climate data to derive daily values for climate change scenarios or rely on empirical adjustments to account for daily and monthly variability.