Dynamic Downscaling

Dynamic downscaling is a method used in climate science to improve the accuracy of regional weather predictions. It involves using detailed computer models that focus on a specific area and incorporate broader atmospheric information from larger-scale climate models. These regional models simulate local features like mountains and coastlines more precisely, providing finer-scale climate information. Essentially, dynamic downscaling translates general, large-scale climate data into more localized, detailed forecasts, helping us understand regional climate patterns and potential future changes more effectively.