# The NEWA Ferry Lidar Experiment: Measuring Mesoscale Winds in the Southern Baltic Sea
## 5 Comparison with Mesoscale Model Data  
For the measurements in the Ferry Lidar Experiment, the ship lidar system had traversed distances of up to 6 km in one 10-min interval. This distance corresponds to the mesoscale in meteorological observations [22], which suggests relating the ship lidar measurements to the output data of an NWP model having a similar scale. A corresponding initial comparison of the ship lidar measurements with mesoscale model data is presented in this section.  
We have used the same model which is used to generate the wind atlas within the NEWA project, namely the Weather Research and Forecasting Model (WRF) [23]. In detail, we used an offshore optimized setup (similar to the setup used in Reference [24]) that was intensively tested in a case study phase for the Wind Atlas generation. Figure 8 shows the model domains centered around the Southern Baltic Sea. WRF time series were generated with a temporal resolution of 30 min and on a 3 km \(\times\) 3 km grid; further details of the simulations are given in Table 2. Note that the temporal resolution here does not refer to an average but an instantaneous value every 30 min.  
In order to compare the ship lidar measurements with the WRF simulations, the measurement data are mapped onto the WRF grid, and for each 10-min interval, the \"closest\" WRF output value was selected. For a further description of this mapping procedure see Reference [27].  
Figure 9 shows the results of the comparison for the period already referred to in the preceding data plots. The mesoscale data were interpolated from the terrain following the hybrid pressure coordinates to 100 m at every time step. Both for the horizontal wind speed and direction, the two time series showed a very similar course. Deviations seem to be in the order of, and not larger than, the scatter, i.e., the deviations between individual data points, in typical WRF-to-met-mast comparisons offshore [9].  
\begin{table}
\begin{tabular}{l l} \hline \hline WRF Model Version & 3.8.1 \\ \hline _Atmospheric Boundary Condition_ & ERA Interim [25] \\ \hline _Sea Surface Temperatures_ & OSTIA [26] \\ \hline _Land Use Data_ & USGS \\ \hline _Horizontal Resolution_ & D01 (27 km), D02 (9 km), D03 (3 km) \\ \hline _Nesting_ & 1-way \\ \hline _Vertical Resolution_ & 62 levels—with 20 below 1000 m \\ \hline _Microphysics_ & WSM 5-class scheme \\ \hline _Planetary Boundary Layer Scheme (PBL) Scheme_ & MYNN (Level 2.5) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Details of WRF simulations.  
Figure 8: Model domains of WRF runs used for comparison.  
Larger deviations are observed for the periods where the ship lies in the harbor (cf. also Figure 5) and could easily be explained by the existence of relevant microscale effects that are not included in the mesoscale model. Further offshore these effects are obviously negligible.  
To further quantify the observed deviations, we have derived bias and root-mean-square-error (RMSE) values for the deviations in horizontal wind speed and wind direction between the Ferry Lidar and WRF data (see Table 3). For this evaluation, the \"harbor effects\" were excluded by considering only the data with a longitude coordinate larger than 10.4\({}^{\circ}\) and below 20.0\({}^{\circ}\).  
The comparison indicates that the 4-day period selected for demonstration indeed shows a better performance than the overall dataset. A deeper analysis may reveal that the agreement varies with the location of the measurement in combination with the wind direction due to the prevailing site effects that were existent at some locations over the track. A corresponding filtering should be applied when further working with the dataset and, in particular, when setting up a benchmark study.