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oai:gredos.usal.es:10366/1498312025-04-30T19:49:19Zcom_10366_138150com_10366_4512com_10366_3823com_10366_4644com_10366_4576com_10366_4137com_10366_4055com_10366_3946com_10366_4283com_10366_4200com_10366_4359com_10366_4349col_10366_138151col_10366_4645col_10366_4138col_10366_4284col_10366_4360

Prieto Herráez, Diego Frías-Paredes, Laura Cascón Barbero, José Manuel Lagüela López, Susana Gastón Romeo, Martín Asensio Sevilla, María Isabel Martín Nieto, Ignacio Fernandes Correia, P.M. Laiz Alonso, Pablo Carrasco Díaz, O.F. Sáez Blázquez, Cristina Hernández, E. Ferragut Canalsd, L. González Aguilera, Diego 2022-05-24T11:03:13Z 2022-05-24T11:03:13Z 2021 Prieto Herráez, D,... et al. (2021). Local wind speed forecasting based on WRF-HDWind coupling. Atmospheric Research, 248, pp. 105219 0169-8095 http://hdl.handle.net/10366/149831 10.1016/j.atmosres.2020.105219 [EN] Wind speed forecasts obtained by Numerical Weather Prediction models are limited for fine interpretation in heterogeneous terrain, in which different roughnesses and orographies occur. This limitation is derived from the use of low-resolution and grid-box averaged data. In this paper a dynamical downscaling method is presented to increase the local accuracy of wind speed forecasts. The proposed method divides the wind speed forecasting into two steps. In the first one, the mesoscale model WRF (Weather Research and Forecasting) is used for getting wind speed forecasts at specific points of the study domain. On a second stage, these values are used for feeding the HDWind microscale model. HDWind is a local model that provides both a high-resolution wind field that covers the entire study domain and values of wind speed and direction at very located points. As an example of use of the proposed method, we calculate a high-resolution wind field in an urban-interface area from Badajoz, a South-West Spanish city located near the Portugal border. The results obtained are compared with the values read by a weathervane tower of the Spanish State Meteorological Agency (AEMET) in order to prove that the microscale model improves the forecasts obtained by the mesoscale model. eng http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional Wind speed forecasting WRF HDWind Dynamical downscaling Local wind adjustment Local wind speed forecasting based on WRF-HDWind coupling info:eu-repo/semantics/article