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between large-scale predictor variables and the surface weather variables at
alocalsite.
Further studies are planned to compare the performance of these two
models using data from other sites with different climatic conditions. In
addition, the performance of these two models should be evaluated using
data from GCMs in order to be able to assess the reliability of generated
future climate scenarios for a local site.
References
1. B. Yarnal, A. C. Comrie, B. Frakes and D. P. Brown, Developments and
prospects in synoptic climatology. International Journal of Climatology 21
(2001) 1923-1950.
2. LO. Mearns, I. Bogardi, I. Matyasovszky and M. Palecki, Comparison of cli-
mate change scenarios generated from regional climate model experiments
and statistical downscaling, Journal of Geophysical Research
104
(1999)
6603-6621.
3. W. J. Gutowski, Jr., R. L. Wilby, L. E. Hay, C. J. Anderson, R. W. Arritt,
M. P. Clark, G. H. Leavesley, Z. Pan, R. Da Silva and E. S. Takle, Statistical
and dynamical downscaling of global model output for US national assessment
hydrological analyses, Proceedings of the 11th Symposium on Global Change
Studies , Long Beach, CA, January 9-14, 2000.
4. C.-Y. Xu, From GCMs to river flow: A review of downscaling methods and
hydrologic modeling approaches. Progress in Physical Geography 23 , 2 (1999)
229-249.
5. C. Prudhomme, N. Reynard and S. Crooks, Downscaling of global climate
models for flood frequency analysis: Where are we now? Hydrological Processes
16
(2002) 1137-1150.
6. R. L. Wilby, C. W. Dawson and E. M. Barrow, SDSM - A decision support
tool for the assessment of regional climate change impacts. Environmental
Modelling and Software
(2002) 147-159.
7. M. A. Semenov and E. M. Barrow, Use of stochastic weather generator in the
development of climate change scenarios, Climatic Change 35 (1997) 397-414.
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