Downscaling GCMs using the Smooth Support Vector Machine method to predict daily precipitation in the Hanjiang Basin

@article{Chen2010DownscalingGU,
  title={Downscaling GCMs using the Smooth Support Vector Machine method to predict daily precipitation in the Hanjiang Basin},
  author={Hua Chen and Jing Guo and Wei Xiong and Shenglian Guo and Chong-Yu Xu},
  journal={Advances in Atmospheric Sciences},
  year={2010},
  volume={27},
  pages={274-284}
}
General circulation models (GCMs) are often used in assessing the impact of climate change at global and continental scales. However, the climatic factors simulated by GCMs are inconsistent at comparatively smaller scales, such as individual river basins. In this study, a statistical downscaling approach based on the Smooth Support Vector Machine (SSVM) method was constructed to predict daily precipitation of the changed climate in the Hanjiang Basin. NCEP/NCAR reanalysis data were used to… CONTINUE READING

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