A tool for downscaling weather data from large-grid reanalysis products to finer spatial scales for distributed hydrological applications. (October 2016)

• Record Type: Journal Article
• Authors: Sen Gupta, Avirup; Tarboton, David G.
• Is Part Of: Environmental modelling & software. Volume 84(2016:Oct.)
• Page Start: 50
• Page End: 69
• Publication Date: 2016-10
• Subjects: Downscaling -- Reanalysis data -- Energy balance snowmelt model -- R -- Graphical user interface; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.06.014
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: A downscaling tool was developed to provide sub-daily high spatial resolution surfaces of weather variables for distributed hydrologic modeling from NASA Modern Era Retrospective-Analysis for Research and Applications reanalysis products. The tool uses spatial interpolation and physically based relationships between the weather variables and elevation to provide inputs at the scale of a gridded hydrologic model, typically smaller (∼100 m) than the scale of weather reanalysis data (∼20–200 km). Nash-Sutcliffe efficiency (NSE) measures greater than 0.70 were obtained for direct tests of downscaled daily temperature and monthly precipitation at 173 SNOTEL sites. In an integrated test driving the Utah Energy Balance (UEB) snowmelt model, 80% of these sites gave NSE > 0.6 for snow water equivalent. These findings motivate use of this tool in data sparse regions where ground based observations are not available and downscaled global reanalysis products may be the only option for model inputs. Highlights: Tool to generate downscaled hydrologic model inputs from NASA MERRA reanalyses. Tested directly at 173 SNOTEL sites across the western US (NSE > 0.70). Tested as integrated input to an energy balance snowmelt model (NSE > 0.6). Open source R implementation with user friendly graphical interface. Useful in data sparse regions where ground based observations are not available.