The effect of downscaling techniques on assessing water resources impacts from climate change scenarios

Assessing the impact of climate change on water resources is often based on simulations from global climate models (GCMs) that have been downscaled. Downscaling of GCMs, to improve representation over a limited region, can be done either by use of a regional climate model (RCM) or by statistical downscaling of the GCMs. Although both of these techniques are common, they are seldom compared. This paper investigates the effect of using different downscaling techniques for the assessment of climate change impacts on water resources. The results show that both dynamical and statistical downscaling are useful methods to downscale GCM output. However, when there are orographic influences that affect the local climate, such as mountains, the method of statistical downscaling should be used more carefully.