SDSM, or Statistical Downscaling Model, is a technique used in climate science to refine large-scale climate data into more localized information. It helps researchers and policymakers understand how global climate changes may impact specific regions by providing detailed projections of temperature and precipitation. The model typically combines climate models with historical weather data to create a statistical relationship. This relationship allows for the estimation of local climate variables based on broader climate scenarios, making it a valuable tool for assessing potential impacts on agriculture, water resources, and urban planning.