Global climate models (GCMs) are the primary tools to simulate multi-decadal climate
dynamics and to generate global climate change projections under different future emission …

Two downscaling methods designed for the study of the hydrological impact of climate
change on the Seine basin in France are tested for present climate. First, a multivariate …

Empirical-statistical downscaling (ESD) is a method for estimating how local climatic
variables are affected by large-scale climatic conditions. ESD has been applied to local …

Brands, S., S. Herrera, D. San-Martín, and JM Gutiérrez, 2011a: Validation of the
ENSEMBLES global climate models over southwestern Europe using probability density …

The present study assesses the ability of seven Earth System Models (ESMs) from the
Coupled Model Intercomparison Project Phase 5 to reproduce present climate conditions in …

This paper presents a methodology to downscale monthly precipitation to river basin scale
in Indian context for special report of emission scenarios (SRES) using Support Vector …

In this paper, artificial neural network (ANN) was used for statistically downscale the outputs
of general circulation models (GCMs) to assess future changes of precipitation and mean …

The PIER Program, managed by the California Energy Commission (Energy Commission),
conducts public interest research, development, and demonstration (RD&D) projects to …

The increasing demand for high-resolution climate information has attracted growing
attention to statistical downscaling (SDS) methods, due in part to their relative advantages …

A multivariate statistical downscaling methodology is implemented to generate local
precipitation and temperature series at different sites based on the results from a variable …