# The NEWA Ferry Lidar Experiment: Measuring Mesoscale Winds in the Southern Baltic Sea
## 1 Introduction  
The consortium of the New European Wind Atlas (NEWA [1]) project is currently creating a later publicly available and freely accessible wind atlas covering essentially the countries of the European Union and Turkey. The coverage further includes offshore areas up to 100 km from shore and the complete North and Baltic Sea. The basis of the atlas is a model chain, also developed within the project, comprising mesoscale and microscale flow models that are run to generate the wind time series and statistics making up the atlas. Mesoscale time series data, which represent the largest part of the atlas, will be available with a spatial resolution of 3 km \(\times\) 3 km and for a length of 30 years. The microscale resolution will be finer than 100 m \(\times\) 100 m, but here only limited statistics will be provided. The third outcome of the project, besides the wind atlas and model chain, is an experimental database comprising the data from a number of quite unique flow experiments that have been conducted within the project. The NEWA experiments vary not only in their locations but also in the assessed types of terrains and associated flow phenomena, their durations, and the level and complexity of involved equipment and resulting data volume [2]. Common to all experiments within NEWA is the application of Doppler lidar technology to supplement, and in some cases also completely replace, meteorological towers. This is not by chance, but indicates the breakthrough of a technology that has been continuously developed further for the wind industry within the last 10-15 years [3]. The sites of the NEWA experiments are distributed over the coverage of the later wind atlas (see Figure 1). It is important to emphasize that the experimental data are not integrated in the wind atlas. Instead of supplementing the model data, they are used to test and validate the involved models in dedicated benchmark studies. Each experiment has been defined with a specific focus [2], including a double ridge as in the Perdigao experiment (Portugal) [4], a complex steep terrain with a complex mesoscale flow in Alaiz (Spain), a flow over forested rolling hills in Hornamossen (Sweden), a single forested hill near Kassel (Germany), or a near-shore wind flow in RUNE (Denmark) [5]. The Ferry Lidar Experiment is the only offshore experiment within NEWA. Its name originates from its setup: a vertically scanning Doppler lidar is placed on a ferry boat to measure the wind along the ferry route, covering several hundreds of kilometers within one day and travelling back and forth for a period of several months. This rather simple setup is designed for studying mesoscale effects that are, in particular, far-offshore pre-dominant. For distances greater than 30 km from shore and at heights relevant for wind energy exploitation (i.e., greater than about 50 m) microscale effects due to e.g., breaking sea waves do not play an important role [6]. Comparisons with data of meteorological (met) masks show that mesoscale models are capable of resolving the most important features of the marine atmospheric boundary layer and compare well with the in-situ measurements of a mast [7; 8]. In this sense, it is common practice to validate and verify the data simulated with a mesoscale model (as, e.g., the known Numerical Weather Prediction (NWP) models) against data from offshore met masts [9]. In most cases, this is a fair comparison, just because of the absence of relevant microscale terrain effects impacting the mast measurements for the height ranges of interest. It has to be kept in mind, however, that an NWP data point is representative for an area of several square kilometers and not just a single spot; this may lead to some smoothing in the simulated data in comparison to spot-like mast measurements. As a second discrepancy, NWP models typically do not give averaged data representative of a certain time interval but instead instantaneous values, e.g., every 10 or 30 min.