Search Results - subject:"Statistical Downscaling"

On the suitability of a Convolutional Neural Network based RCM-Emulator for fine spatio-temporal precipitation

Doury, Antoine; Somot, Samuel; Gadat, Sébastien - 2024

Persistent link: https://www.econbiz.de/10014450927

Regional climate model emulator based on deep learning : concept and first evaluation of a novel hybrid downscaling approach

Corre, Lola; Doury, Antoine; Gadat, Sébastien; Ribes, … - 2021

Persistent link: https://www.econbiz.de/10012596548

Climate Change and Hydrological Response in the Trans-State Oologah Lake Watershed–Evaluating Dynamically Downscaled NARCCAP and Statistically Downscaled CMIP3 Simulations with VIC Model

Qiao, Lei; Hong, Yang; McPherson, Renee; Shafer, Mark; … - In: Water Resources Management 28 (2014) 10, pp. 3291-3305

Statistically and dynamically downscaled climate projections are the two important data sources for evaluation of climate change and its impact on water availability, water quality and ecosystems. Though bias correction helps to adjust the climate model output to behave more similarly to...

Persistent link: https://www.econbiz.de/10010998232

Statistically downscaled climate change projections of surface temperature over Northern Italy for the periods 2021–2050 and 2070–2099

Tomozeiu, R.; Agrillo, G.; Cacciamani, C.; Pavan, V. - In: Natural Hazards 72 (2014) 1, pp. 143-168

–2050 and 2070–2099 against 1961–1990. A statistical downscaling technique, applied to the ENSEMBLES-Stream1 and CIRCE global …

Persistent link: https://www.econbiz.de/10010846947

An analytical comparison of four approaches to modelling the daily variability of solar irradiance using meteorological records

Huang, Jing; Troccoli, Alberto; Coppin, Peter - In: Renewable Energy 72 (2014) C, pp. 195-202

error around 40%. While the approach of statistical downscaling from a large spatial domain has been applied for other …

Persistent link: https://www.econbiz.de/10010930882

Basin Scale Water Resources Systems Modeling Under Cascading Uncertainties

Rehana, S.; Mujumdar, P. - In: Water Resources Management 28 (2014) 10, pp. 3127-3142

Global change in climate and consequent large impacts on regional hydrologic systems have, in recent years, motivated significant research efforts in water resources modeling under climate change. In an integrated future hydrologic scenario, it is likely that water availability and demands will...

Persistent link: https://www.econbiz.de/10010794147

Equidistance Quantile Matching Method for Updating IDFCurves under Climate Change

Srivastav, Roshan; Schardong, Andre; Simonovic, Slobodan - In: Water Resources Management 28 (2014) 9, pp. 2539-2562

Recent increase in intensity and frequency of catastrophic hydrologic events is shown to be a major threat to the global economy. These major events have been strongly linked to climate change and are expected to become worse in the future. The intensity-duration-frequency (IDF) curves quantify...

Persistent link: https://www.econbiz.de/10010794292

Hydrological Impacts of Warmer and Wetter Climate in Troutlake and Sturgeon River Basins in Central Canada

Choi, Woonsup; Kim, Sung; Lee, Mark; Koenig, Kristina; … - In: Water Resources Management 28 (2014) 15, pp. 5319-5333

investigated. Several statistical downscaling methods are used to generate temperature and precipitation scenarios from the third …

Persistent link: https://www.econbiz.de/10011151769

Responses of rice yield, irrigation water requirement and water use efficiency to climate change in China: Historical simulation and future projections

Wang, Weiguang; Yu, Zhongbo; Zhang, Wei; Shao, Quanxi; … - In: Agricultural Water Management 146 (2014) C, pp. 249-261

a statistical downscaling method (SDSM). The results exhibit a significant decline in rice yield was identified by 49 …

Persistent link: https://www.econbiz.de/10011047775

Statistical Downscaling of River Runoff in a Semi Arid Catchment

Samadi, S.; Carbone, Gregory; Mahdavi, M.; Sharifi, F.; … - In: Water Resources Management 27 (2013) 1, pp. 117-136

Linear and non-linear statistical ‘downscaling’ study is applied to relate large-scale climate information from a … modeled outcomes from a General Circulation Model (GCM), HadCM3, along with two downscaling techniques, Statistical … Downscaling Model (SDSM) and Artificial Neural Network (ANN), to determine how future streamflow may change in a semi arid …

Persistent link: https://www.econbiz.de/10010997970