(Elsevier, 2021-08-28) Prieto-Herráez, Diego; Frías Paredes, Laura; Cascón, J. Manuel; Lagüela, Susana; Gastón Romeo, Martín; Asensio, María Isabel; Martín Nieto, Ignacio; Fernandes Correia, Pedro Miguel; Laiz-Alonso, Pablo; Carrasco-Díaz, O. F.; Sáez Blázquez, Cristina; Hernández, Erwin; Ferragut, Luis; González-Aguilera, Diego; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
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.
