We consider the impact of climate change on the wind energy resource of Ireland using an ensemble of Regional Climate Model (RCM) simulations. The RCM dynamically downscales the coarse information provided by the Global Climate Models (GCMs) and provides high resolution information, on a subdomain covering Ireland. The RCM used in this work is the Rossby Center’s RCM (RCA3). The RCA3 model is e...

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate ob...

two statistical downscaling models, the non-homogeneous hidden markov model (nhmm) and the statistical down–scaling model (sdsm) were used to generate future scenarios of both mean and extremes in the tarim river basin,which were based on nine combined scenarios including three general circulation models (gcms) (csiro30, echam5,and gfdl21) predictor sets and three special report on emission sce...

This study aims to evaluate effects of two downscaling methods; change-factor and statistical downscaling on therunoff of the Azam-Harat River located at Yazd province (with an arid climate) of Iran, under the A2 emission scenariofor the period of 2010-2039. For this purpose, CGCM3-AR4 model; a rainfall-runoff conceptual model, IHACRES; twodownscaling models, Change Factor and LARS-WG were appl...

Implications of 21st century climate change on the hydrology and water resources of the Colorado River Basin were assessed using a multimodel ensemble approach in which downscaled and bias corrected output from 11 General Circulation Models (GCMs) was used to drive macroscale hydrology and water resources models. Downscaled climate scenarios (ensembles) were used as forcings to the Variable Inf...

Statistical downscaling is the technique of linking large-scale predictors and local-scale predictands through a relationship that assumed to be helpful generate climate change information from global model (GCM) driven future projection. The present study investigates downscaled seasonal annual rainfall scenarios over different locations Western Himalaya Region (WHR) India using common ten GCM...

climate is a complex system which is changing mainly due to the increase of greenhouse gases. because of the importance of climate change and the effects it can have on water resources, in recent years, this topic has been taken into consideration for different basins on earth. the objective of this study is to investigate the effects of climate change and forecasting meteorological variables o...

a methodology is presented for the stochastic generation of daily rainfall which accounts for changes to the climatic inputs. the focus of the study is an example catchment in iran. the methodology addresses the inability of gcms to provide suitable future scenarios for the time and space scales required for a water resource impact assessment for a small catchment. one stochastic model for rain...

This study is intended to examine the past drought and predict future drought scenarios for Arkansas-Red River Basin with comprehensive drought indices ranging from meteorology, hydrometeorology to hydrology. In this proceeding, we present some early results and analysis with the Standardized Precipitation Index (SPI) and the Palmer Drought Severity Index (PDSI). Historical climate data within ...