Downscaling is the collective term for the methods used to regionalize information from Global Climate Model (GCM) at a coarser spatial resolution and create a higher spatial resolution data or a fine spatial scale data (ground station). Its purpose is to bring the GCM model data in closer agreement with the station level data.
Downscaling techniques can be divided into two broad categories: dynamical and statistical. Dynamical downscaling refers to the use of high-resolution regional simulations to dynamically extrapolate the effects of large-scale climate processes to regional or local scales of interest. Statistical downscaling encompasses the use of various statistics-based techniques to determine relationships between large-scale climate patterns resolved by GCMs and observed local climate responses. These relationships are applied to GCM results to transform climate model outputs into statistically refined products.