Articles | Volume 5, issue 3
Wind Energ. Sci., 5, 997–1005, 2020
Wind Energ. Sci., 5, 997–1005, 2020

Research article 06 Aug 2020

Research article | 06 Aug 2020

Validation of uncertainty reduction by using multiple transfer locations for WRF–CFD coupling in numerical wind energy assessments

Rolf-Erik Keck and Niklas Sondell

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Cited articles

Copernicus Climate Change Service (C3S): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate, Copernicus Climate Change Service Climate Data Store (CDS), available at:!/home (last access: 1 February 2020), 2017. 
Draxl, C., Hodge, B. M., Clifton, A., and McCaa, J.: Overview and Meteorological Validation of the Wind Integration National Dataset toolkit, USA,, 2015. 
Flores-Maradiaga, A., Benoit, R., and Masson, C.: Enhanced modelling of the stratified atmospheric boundary layer over steep terrain for wind resource assessment, J. Phys. Conf. Ser., 1222, 012005,, 2019 
Giannaros, T. M., Melas, D., and Ziomas, I.: Performance evaluation of the Weather Research and Forecasting (WRF) model for assessing wind resource in Greece, Renew. Energ., 102, 190–198, 2017 
Gopalan, H., Gundling, C., Brown, K., Roget, B., Sitaraman, J., Mirocha, J., and Miller, W.: A coupled mesoscale–microscale framework for wind resource estimation and windfarm aerodynamics, J. Wind Eng. Ind. Aerod., 132, 13–26,, 2014.  
Short summary
A method for performing numerical wind resource assessments in the absence of on-site measurements is presented and validated against field measurements. Numerical wind resource assessment is at least 2 orders of magnitude faster and less expensive than using conventional site measurements. This enables analysis of a larger number of projects and thereby increases the chances of discovering the best available sites. The uncertainty in mean wind speed predictions is found to be about 4 %.