Climate models serve as good guesses of how humans affect the climate, but they cannot explore all possible future scenarios of interest. We develop a method that can serve as a fast and cheap stand-in to evaluate likely changes in variables like surface temperature and relative humidity at a regional scale in arbitrary future climates. Crucially, our method captures relationships between different geographic areas and predicts both average values and likely ranges using a unified framework.