The computational cost of dynamical downscaling limits ensemble sizes in regional downscaling efforts. We present a generative-AI approach to greatly expand the scope of such downscaling, enabling fine-scale future changes to be characterised including rare extremes that cannot be addressed by traditional approaches. We test this approach for New Zealand, where heterogenous regional climate effects are anticipated. End-of-cent...