Abstract
The need to mitigate climate change will boost the demand for renewable
energy and lead to more wind turbines both on- and onshore. In the near
future, the effect these wind farms have on the atmosphere can no longer
be neglected. In numerical weather prediction models wind-farm
parameterisations (WFP) can be used to model the effect of wind farms on
the atmosphere. There are different modelling approaches, but the
parameterisation developed by Fitch et al. (2012) is most used in
previous studies. It models the wind farm as a momentum sink and a
source of power production and turbulent kinetic energy. In this paper,
we have implemented the Fitch et al. (2012) WFP into HARMONIE-AROME, the
numerical weather prediction model that is currently used by at least 11
national weather services in Europe. We used HARMONIE-AROME to make
year-long simulations for 2016 with and without the WFP. The results
were extensively evaluated using lidar, tower and flight measurements at
several locations near wind farms. Including the WFP greatly reduces the
model bias for wind speed near offshore wind farms. Wind farms not only
affect wind, but also temperature and humidity, especially during stable
atmospheric conditions: the enhanced mixing caused by the wind turbines
reduces the stratification of temperature and humidity. Including the
WFP in HARMONIE-AROME results in a more realistic representation of the
atmosphere near wind farms and makes it a more future-proof model for
weather forecasting.