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In the regional climate model simulations the winter precipitation projection has the highest uncertainty (Bartholy et al. 2011).
The results demonstrate that this combined approach significantly improves the downscaling procedure in terms of precipitation projection.
The increased precipitation indicated by RH in the present study has been also indicated by Tolika et al. (2012) for precipitation projection with RCA-ECHAM4.
Analysis of the CGCM3.1 downscaled precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change.
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CP-based downscaling procedures are very promising in increasing the reliability of such future precipitation projections.
Compared with the temperature differences resulting from different GCM models, much greater divergence exists for precipitation due to opposite signs of future precipitation projections from varied GCM models.
As for rainfall trend, the IPCC AR4 total annual precipitation projections suggest increases by about 0.2 0.4 percent per year particularly along the coastline where projects sites locate.
We analyzed precipitation projections for the Koshi river basin in Nepal using outputs from 10 General Circulation Models (GCMs) under three emission scenarios (B1, A1B and A2).
The precipitation projections for three future periods, i.e. 2020s, 2055s and 2090s, are presented using empirical Probability Density Functions (PDFs) for each physiographic region.
Precipitation projections are more complex to interpret than temperature projections because the GCMs often do not agree on whether precipitation will increase or decrease at specific locations, much less agree on the magnitude of that change.
The three GCMs showed increases in maximum and minimum temperature, but precipitation projections varied among GCMs.
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