Downscaling

In numerical modeling, downscaling refers to techniques that take output from the model and add information at scales smaller than the grid spacing. Global climate models (GCMs) are run at coarse spatial resolution (typically of the order 50,000 square kilometres (19,000 sq mi)) and are unable to resolve important sub-grid scale features such as clouds and topography. As a result GCMs can not be used for local impact studies. To overcome this problem downscaling methods are developed to obtain local-scale surface weather from regional-scale atmospheric variables that are provided by GCMs. In 1997, Wilby and Wigley divided downscaling into four categories: regression methods, weather pattern-based approaches, stochastic weather generators and limited-area modeling. Among these approaches regression methods are preferred because of its ease of implementation and low computation requirements.

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