A year-long evaluation of a wind-farm parameterisation in HARMONIE-AROME

Abstract

The need to mitigate climate change will boost the demand for renewable energy and lead to more wind turbines both onand 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.