Abstract
General Circulation (Climate) Models (GCMs) from different research centers of the world provide future replicates of various meteorological variables up to years 2100 at rather coarse mesh nodes of about 250 km apart from each other. These models are based on the physically dynamic equations of energy, momentum and mass conservation in addition to the state equation of gases. Hence, an arena of equations requires simultaneous solution by considering global initial and boundary conditions. It is necessary to downscale the GCM results at coarse nodes to locally smaller scales so as to match the historical data sequences to scenario series. Such downscaling procedures are necessary for climate change impact effect assessments including vulnerability, mitigation and adaptation works at finer scales. Various methods have been suggested so far in the literature for downscaling and still new ones are expected to come in the future. It is the main purpose of this paper to provide the critical review of available methods and then to suggest a regional dependence function based on the point cumulative semivariogram technique.
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