Statistical Downscaling of Daily Wind Speed Variations

Empirical Downscaling of Wind Speed Probability Distributions

Sub-daily Statistical Downscaling of Meteorological Variables Using Neural Networks

A new open source neural network temporal downscaling model is described and tested using CRU-NCEP reanalysis and CCSM3 climate model output. We downscaled multiple meteorological variables in tandem from monthly to sub-daily time steps while also retaining consistent correlations between variables. We found that our feed forward, error backpropagation approach produced synthetic 6 hourly meteo...

evaluating the performance of artificial neural network model in downscaling daily temperature, precipitation and wind speed parameters

numerous studies yet have been carried out on downscaling of the large-scale climate data usingboth dynamical and statistical methods to investigate the hydrological and meteorological impacts of climatechange on different parts of the world. this study was also conducted to investigate the capability of feedforwardneural network with error back-propagation algorithm to downscale the provincial...

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...

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, ...