## 3 Results and Discussion
### Strong-Wind Events  
The 10 high-wind events identified in Figure 6 correspond to 19 daily simulations of the WRF model. The LES model uses the mesoscale model as input in a one-way nesting, and the WRF modelling is therefore rerun for these days, now with all five domains active. The mean wind speed values during the strong-wind events shown in Table 2 clearly show how WRF underestimates the wind speed for the low-resolution model. Increasing the resolution from D01 to LES does improve the wind speed results, but the mean wind speed is still clearly lower than the measured wind speed during these strong-wind events. The same tendency of improvement with higher-resolution models can be seen in STD and RMSE, while the correlation coefficient R clearly drops as resolution increases. The statistical significance for RMSE and R was checked using the leave-one-out method, and the minimum and maximum of these statistics are included in Table 2. Assuming that the events are statistically independent, the low RMSE for LES is significantly lower than D03 and D04. A similar decrease in RMSE can be seen going from D01/D02 to D03/D04, while both pairs of domains have some overlap in their values. Regarding correlation, the D03 model has the highest R value, but the statistical spread is quite wide and overlapping for all model domains. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Time Series** & **Mean** & **STD** & **RMSE [min, max]** & **R [min, max]** \\ \hline Meas, events & 20.1 & 4.41 & & \\ WRF D01 & 10.4 & 3.76 & 10.13 [9.81, 10.31] & 0.78 [0.60, 0.81] \\ WRF D02 & 10.7 & 3.98 & 9.77 [9.39, 9.93] & 0.78 [0.58, 0.81] \\ WRF D03 & 13.3 & 5.61 & 7.41 [7.18, 7.61] & 0.86 [0.72, 0.89] \\ WRF D04 & 12.9 & 4.85 & 7.76 [7.55, 7.95] & 0.82 [0.64, 0.85] \\ WRF LES & 16.1 & 6.06 & 5.42 [5.20, 5.61] & 0.80 [0.63, 0.85] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Mean, STD, RMSE and R for measured and modelled wind speeds for 10 strong-wind events during 2017. Figure 7: Normalised histograms for measured and modelled wind speeds for the year 2017. The measured wind speed during the Ylva storm event starting on 22 November is shown as the black line in Figure 8. The wind speed is around 15-20 m/s during the first 30 h, then it increases to 30-35 m/s before it slowly drops down again to the 90 th percentile. The two WRF models with the lowest resolution have a wind speed that during the Ylva storm starts at 5 m/s, increases to approximately 18 m/s by 24 November, and then drops again to 5 m/s. The overall shape of the wind speed follows the measurement, but the wind speed is significantly lower in these WRF models. As we increase the resolution in the WRF model, the modelled wind speeds also increase. For the LES models, this means an overall shape that starts lower than the measurement at around 10 m/s as the start of the event, increases to the measured 30-35 m/s range during the most intense part of the storm, and follows the decreasing measured wind speeds quite well as the storm passes. The legend in Figure 8 shows the RMSE values for the different model resolutions when only considering the Ylva storm event. The LES model can represent strong wind speeds during the event quite well and thus shows clearly lower RMSE results compared to the lower-resolution models. Increasing the resolution in the WRF models has a visible effect on the variability of the wind speeds, as the D01 result is quite smooth with slower variations than the high-resolution models. The high frequency variations in the LES model might explain the lower linear correlation to the measurements, since the timing for these variations does not necessarily match the measurements, although the standard deviations for these time series are similar. Figure 9 shows the WRF model D01 sea level pressure on 23 November at 20:20, where the maximum wind speed of 35.1 m/s was measured, together with modelled wind speed barbs close to the surface indicating wind speed and direction.