Results 241 to 250 of about 10,908 (283)

Downscaled global 60-meter resolution estimates of irrigation water sources (2000-2015). [PDF]

Sci Data
Hung F, Chiarelli DD, Famiglietti JS, Müller MF.   +3 more
europepmc   +1 more source

Deep learning-based thermal mapping for enhanced urban heat management and cooling energy reduction in Arid Saudi Arabian environments. [PDF]

Sci Rep
Alsharif AM, Almajadiah AM, Alzahrani M, Lagebo ML, Andiye YM.   +4 more
europepmc   +1 more source

IAM-FIRE: A Climate Emulator-Based Framework to Project Wildfire Impacts and Risks for Integrated Assessment Models. [PDF]

Glob Chang Biol
Rouhette T, Van de Ven DJ, Narayan K, Tebaldi C, Perkins O, Haas O, Escobar N.   +6 more
europepmc   +1 more source

China runoff-field forecasting based on cross-scale gating and basin-topology attention. [PDF]

PLoS One
Li A, He X, Yang K, Ge W, Hua J.
europepmc   +1 more source

Regional climate projections using a deep-learning-based model-ranking and downscaling framework: application to European climate zones. [PDF]

Environ Sci Pollut Res Int
Loganathan P, Zea E, Vinuesa R, Otero E.
europepmc   +1 more source

High-resolution water footprints of major crops in China from cities to grids. [PDF]

Sci Rep
Zhao J, Wu L, Wang X, Yu Y, Huang K.
europepmc   +1 more source

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Spatial variability and downscalling of precipitation

Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 2001
Abstract To fully take advantage of regional climate forecast information for agricultural applications, the relationship between regional and station scale precipitation characteristics must be quantified. The spatial variability of precipitation within a region is defined by differences between station and regional standardised values.
F. Rossel, J. Garbrecht
openaire   +1 more source

Joint variable spatial downscaling

Climatic Change, 2011
Joint Variable Spatial Downscaling (JVSD), a new statistical technique for downscaling gridded climatic variables, is developed to generate high resolution gridded datasets for regional watershed modeling and assessments. The proposed approach differs from previous statistical downscaling methods in that multiple climatic variables are downscaled ...
Feng Zhang, Aris P. Georgakakos
openaire   +1 more source

Downscaling spatial structure for the analysis of epidemiological data

Computers, Environment and Urban Systems, 2008
Abstract Many widely accessible forms of socio-economic and public health data have been subjected to some form of spatial aggregation. Polygonal units, such as US Census tabulation areas, political boundaries, transportation analysis zones and ZIP codes, are often used to represent the spatial extent of these data.
Timothy C. Matisziw, Tony H. Grubesic, Hu Wei   +2 more
openaire   +1 more source

Spatial downscaling of European climate data

International Journal of Climatology, 2015
ABSTRACTE‐OBS(European Observations) is a gridded climate data set which contains maximum temperature, minimum temperature, and precipitation on a daily time step. The data can be as fine as 0.25° in resolution and extends over the entire European continent and parts of Africa and Asia.
Adam Moreno, Hubert Hasenauer
openaire   +1 more source