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.

References

• Wilby, R.L. and Wigley, T.M.L., (1997) Downscaling general circulation model output: a review of methods and limitations, Progress in Physical Geography, 21, 530–548.
• Wilby, R.L., Dawson, C.W. and Barrow E.M., (2002) SDSM - a decision support tool for the assessment of regional climate change impacts, Environmental Modelling & Software, 17, 147– 159.
• Kim, J.W., Chang, J.T., Baker, N.L., Wilks, D.S., Gates, W.L., 1984. The statistical problem of climate inversion: determination of the relationship between local and large-scale climate. Monthly Weather Review 112, 2069–2077.
• von Storch, H., Zorita, E., Cubasch, U., 1993. Downscaling of global climate change estimates to regional scales: an application to Iberian rainfall in wintertime. Journal of Climate 6, 1161–1171.
• Hessami, M., Quarda, T.B.M.J., Gachon, P., St-Hailaire, A., Selva, F. and Bobee, B., “Evaluation of statistical downscaling method over several regions of eastern Canada”, 57th Canadian water resources association annual congress, 2004.