General Circulation Models (GCMs) Downscaling Techniques and Uncertainty Modeling for Climate Change Impact Assessment

Abstract

Scientific literature on the assessment and projection of climate change impacts suggests that the rapidly changing climate conditions are causing far-reaching consequences on natural resources and agricultural production. Atmospheric general circulation models (GCMs) have been widely used to simulate the present climate and to predict future climatic change at the globalscale. However, the assessment and projection of climate change at regional and national scales requires high resolution and consistent climate data to ensure that the scale and accuracy of results will enable planning for adaptation. This data can be obtained by downscaling the simulated output from GCMs using the appropriate predictors. However, this process is characterized by uncertainty due projections generated with multiple GCMs. This paper provides a summary of research developments in the use of GCMs for the assessment and projection of climate change impacts. The different techniques which have been used to downscale GCM output for compatibility with regional and watershed models, their advantages and deficiencies are also discussed. Modeling approaches to address GCM uncertainties and uncertain future scenarios are discussed.