Downscaling results. Original CRU data at 0.5 x 0.5 degrees (right). At right, the same CRU data downscaled to 2 x 2 km.
The goal of downscaling is to create locally accurate climate information starting from global scale data.
In other words, we add value to global scale data by placing it in the context of observed local climatological conditions, improving the spatial and temporal resolutions along the way. SNAP applies dynamical and statistical (delta) downscaling methods to climate data.
Dynamical downscaling uses a physically based weather forecasting model to produce higher time and space resolution data from coarser General Circulation Model (GCM) data.
Statistical (delta) downscaling adds the difference (delta) between a historical period and a modeled value to a known historical climatology.
While it is possible to downscale all available GCM datasets, SNAP provides climate data for the top 5 models for the Alaska and Arctic regions from the Coupled Model Intercomparison Project (CMIP) for both the CMIP3 and CMIP5 global modeling efforts.
We offer downscaled projections for each model, as well as for the average of all 5 models.