STATISTICAL DOWNSCALING OF PRECIPITATION WITH A FORMATTED REGRESSION FRAME

Statistical downscaling of precipitation

Papers published in Hydrology and Earth System Sciences Discussions are under open-access review for the journal Hydrology and Earth System Sciences Abstract Global Circulation Models (GCMs) are a major tool used for future projections of climate change using different emission scenarios. However, for assessing the hydrological impacts of climate change at the watershed and the regional scale, ...

Automated regression-based statistical downscaling tool

Many impact studies require climate change information at a finer resolution than that provided by Global Climate Models (GCMs). In the last 10 years, downscaling techniques, both dynamical (i.e. Regional Climate Model) and statistical methods, have been developed to obtain fine resolution climate change scenarios. In this study, an automated statistical downscaling (ASD) regression-based appro...

Statistical downscaling of precipitation through nonhomogeneous stochastic weather typing

We present a novel statistical downscaling method that provides accurate and relatively transparent simulations of local-scale precipitation characteristics. The method combines large-scale upper-air circulation with surface precipitation fields, and is based on a nonhomogeneous stochastic weather typing approach. Here we applay the method to downscale precipitation at 37 rain gauges in the sta...

Performance evaluation of artificial neural networks in statistical downscaling of monthly precipitation (Case study: Minab watershed)

Downscaling of daily precipitation

Downscaling of daily precipitation with a stochastic weather generator for the subtropical region in South China Y. D. Chen, X. Chen, C.-Y. Xu, and Q. Shao Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, Hong Kong, China State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China Department of Geosci...