## 4 Conclusions  
The high-resolution WRF LES model can capture strong-wind events at Fakken wind park, although the WRF models in general tend to underestimate these high wind speeds. The complex terrain in the region, with several mountains and fjords, creates a challenging wind pattern as mesoscale systems move along the coast. The measured wind speed shows several strong-wind events during 2017, with the longest high-wind-speed events during the autumn and all coming from the south-southeast direction. The strongest event, the Ylva storm, recorded a continuous reading of more than 14 m/s wind speed over 72 h.  
We have shown that the local terrain model improves considerably as the horizontal resolution is increased. This allows for more detailed wind patterns around the island where Fakken wind park is located, most visibly represented as higher and steeper mountains in the innermost domain of our simulations. Note that the use of high-resolution input data from NDTM with 10 m resolution is necessary for LES modelling, as results using LESs with GMTED and 30-arcsecond resolution do not reduce the underestimation of high wind speed compared to the D04 results. The main reason for improved wind and power production estimates in the mesoscale models D01-D04 seems to be the models' ability to create mountains and fjords that both block and channel the wind to this location. The highest resolution in the WRF LES model also provides refined terrain and wind fields, which produce local speed-up effects along the small narrow hill where both the measurement mast and the first rows of turbines at Fakken are located. Increasing the size of the LES domain would include more mountains and fjords, such as the Lyngen Alps, with the potential of increasing the tunnelling effect of the fjords. Comparing measured power production with a basic turbine power modelling approach based on WRF wind speed, we have shown that the WRF LES gives noticeably better results during the Ylva storm event. This indicates that higher-resolution weather models may play an important role in the mapping of wind resources, as well as in wind power forecasting during storms and other extreme wind cases. Although NWM using high-resolution LES mode can give a detailed description of the atmospheric conditions over a wind park without the need for local measurements, the use of WAsP and other specialised software for wind resources assessment plays an important role in the planning of a new wind park. These software solutions provide a generalised description of wind speed and direction with high horizontal resolution without a high computational cost. Turning the tables, WAsP does require trustworthy wind input data from a measurement mast, or well-defined WRF model outputs as in the New European Wind Atlas case [25]. The forecasting abilities in NWM are also useful for wind power forecasting applications, so that both solutions have their pros and cons in the future wind power industry. This research is based on wind field results that are limited to one location and one year of data. The significantly lower RMSE in the LES modelling of the high-wind events is further based on the assumption that the events are statistically independent. This assumption can be misleading given such a limited dataset. The LES model in our case has a single inner domain without sub-filter-scale stress, or SGS filters, a simplified setup that follows the real terrain well but has limitations when it comes to turbulence generation in the model. Future research should include SGS functions and wall functions to improve the turbulence structures in the model and better results along the domain borders. Further understanding of the underestimation of the high wind speeds, in storms and extreme weather, should include longer time series and locations with other wind climates including, for example, diurnal cycles or thermal winds. Futureresearch could also include wind turbine parametrisations and the use of different PBL schemes for the driving outer domains.