3.1 Temperature

Temperature measurements are performed by two complementary sensors, the slow but highly accurate 102DB1AG temperature sensor (Rosemount, USA) with an accuracy of ±0.1 K and the 102E4AL sensor (Rosemount, USA) with a fast response time and an accuracy of ±0.25 K plus 0.5 % of the temperature to be measured in degrees Celsius. The slow sensor is heatable, but heating was not switched on, as no icing conditions were present during the flights.

The total temperature T_total is derived by applying a recovery factor to the raw measurements to compensate the self-heating effect. From the total temperature in K, the static temperature T_stat in K is derived adiabatically (Stickney et al., 1994):

Here, p_stat is the static pressure, and p_total is the total pressure: the sum of static and dynamic pressure. κ is the heat capacity ratio with a value of 1.4.

The calibration of the temperature sensors is done by applying specific resistance values corresponding to specific temperatures as stated by the manufacturer.

In the PANGAEA data set (Bärfuss et al., 2019a), the static air temperature derived from the fast sensor is provided, after using the slow sensor for quality checking purposes. The parameter is simply called “air temperature”.

3.2 Humidity

For measuring humidity, three different measurement principles are used: a capacitive Vaisala HUMICAP HMP233, Finland; a dew point mirror TP 3-S of Meteolabor, Switzerland; and a Lyman-alpha optical sensor L-6/HMS-2 of Buck Research, USA. The humidity sensors have a joint heatable inlet, and other parameters like temperature and pressure are recorded for the humidity channel as well. The humidity sensors are cleaned and calibrated before each meteorological measurement campaign by applying saturated salt solutions with known relative humidity in an equilibrium state. In the PANGAEA data set, the relative humidity of the dew point mirror is provided as a reference with good accuracy of the absolute values (accuracy of the dew point is specified by the manufacturer as 0.15 K). The temporal resolution is composed of a time < 0.5 s for the condensation process or temperatures above 0 ^∘C, plus a time delay proportional to the magnitude of abrupt changes in the dew point (5 K s⁻¹). The relative humidity of the Lyman-Alpha sensor with much shorter response time is provided for deriving fluctuations.

3.3 Pressure and wind

With the five-hole probe of Rosemount, USA, and pressure transducers of Setra, USA, the static and dynamic pressure as well as the airflow angles are retrieved in the aircraft-fixed coordinate system. All inertial data (position, ground speed and Eulerian angles) were derived from the complementary use of the inertial measurement platform iNAV-RQH-1003 of iMAR, Germany, operated in parallel to the former standard system Lasernav of Honeywell, USA, and a NovAtel GPS OEM6, Canada. These input parameters are then used to calculate the wind vector according to the formulation in Lenschow (1972), whereas the fundamental vector difference equation in geodetic coordinates is

${\mathit{V}}_{w_{\text{g}}}$ denotes the wind vector, ${\mathit{V}}_{K_{\text{g}}}$ the flight path velocity and V_g the velocity of the aircraft with respect to the air.

In the PANGAEA data set, all three components of the wind vector are provided at 100 Hz resolution to derive horizontal wind speed, wind direction and turbulent properties. Further, the air density derived from the static pressure and temperature is given.

3.4 Sea surface temperature

An infrared KT15.82D sensor of Heimann, now Heitronics, Germany, is used to determine the surface temperature. It has an accuracy of ±1.2 K at 20 ^∘C surface temperature and a temporal resolution of 20 Hz. If no clouds are between the sensor and the surface, the surface temperature measurements are not influenced by the atmospheric temperature or humidity distribution. The footprint size is 10 m at a distance of 900 m for the specific system. In the PANGAEA data set, the parameter is called surface temperature.

3.5 Sea surface deflection

The scanning laser system VZ-1000 of Riegl, Austria, is deployed to record the relative sea surface deflection and to derive parameters like the significant wave height.

From the point measurements in the scanner's coordinate system $\left(\begin{array}{c}{v}_{x_{\text{body}}}\\ v_{y_{\text{body}}}\\ v_{z_{\text{body}}}\end{array}\right)$, aircraft attitude corrections using Eulerian angles (Ψ, Θ and Φ) are applied to rotate aircraft-body-fixed coordinates into the geodetic coordinate system (positive directions east, north and up), which then are geolocated by applying the aircraft position $\left(\begin{array}{c}{p}_{x_{\text{body}}}\\ p_{y_{\text{body}}}\\ p_{z_{\text{body}}}\end{array}\right)$ in the following manner:

Subsequently, the surface deflection η is calculated out of the georeferenced point cloud using mean sea level. The system's effective rate of the distance measurements is up to 122 kHz but decreases over water because of specular reflections. Accuracy and resolution along the beam direction are stated to be less than 10 mm, and measurements can be taken up to a distance of 450 m with the settings used during flight campaigns.

Significant wave height (SWH) H_s, defined in the spatial domain, is used to describe the sea surface. The approximation $H_{\text{s}}\approx H_{m_{\mathrm{0}}}=\mathrm{4}\cdot {\mathit{\sigma }}_{\mathit{\eta }}$ mentioned in Young (1999) was used, since this simple calculus only depends on the standard deviation σ_η in sea surface deflection. Here, $H_{m_{\mathrm{0}}}$ is 4 times the standard deviation of the sea surface deflection measurements, normally defined in the frequency domain. In this case, it is derived from measurements in the space domain. With a deflection measurement rate of more than 3 kHz over water, this produces stable results in SWH estimation. As a scan pattern, a line scan pattern rectangular to the flight direction was used, which provides a spatial resolution of about 0.5 m × 0.5 m between measurement points perpendicular to and along the flight trajectory. In the PANGAEA data set sea surface deflections η are analysed for standard deviation within a time window of 10 s.

3.6 Cameras

Two downward-looking cameras, one for the visible wavelength range (MV1-D1312-G2 of Photonfocus, Switzerland) and one for the infrared range (A35SC of FLIR, Germany), were deployed in the fuselage to document the sea surface. The images are influenced by sun glint and by varying cloud cover. The exposure time of the visible camera was adapted manually. The retrieval of specific parameters requires additional intensive processing of the images.

The large data sets are available at the Institute of Flight Guidance upon request. They are not included in the database. Further, handheld cameras were used to document the overall impression, clouds and special features. They are not included in the database either.

4.1 Meander at hub height (MEANDER)

To quantify the wakes behind offshore wind parks and determine the wake length, meander flight patterns at hub height perpendicular to the prevailing wind direction were applied (MEANDER). An example is provided in Fig. 4. For these flight patterns, isolated wind parks with a long distance of unobstructed water surface downwind were selected. The flight pattern typically started with a leg 500 m downstream of the last wind turbines. The distance to the next flight legs was set as 10 km. The flight altitude was adapted to the hub height and was either 90 m (Amrumbank West) or 120 m (Godewind). On the way to the wind park and after the meander pattern, vertical soundings from 60 to 550 m, sometimes up to 1000 m, were performed to investigate atmospheric stability. For unstable conditions, the distance between the flight legs perpendicular to the wind direction was shortened. This flight pattern was used for 26 out of the 41 flights.

Results of meander flight patterns have been published in Platis et al. (2018), Siedersleben et al. (2018a) and Cañadillas et al. (2020).

4.2 Vertical cross sections (CROSS)

To quantify the vertical extent of wakes, several cross sections at the same distance downwind of the wind park were flown perpendicular to the wake at different altitudes (CROSS). Typical flight altitudes were 60, 90, 130, 150 and 200 m. On the way to the wind park and back, vertical soundings from 60 to 550 m, sometimes up to 1000 m, were performed to investigate atmospheric stability. Such flight patterns were applied during 8 out of the 41 measurement flights.

Results of the cross-sectional patterns measured on 10 September 2016 have been published in Siedersleben et al. (2018a, b).

4.3 Above wind parks (ABOVE)

To quantify the interaction of the wind parks and the atmospheric boundary layer, a flight pattern with legs upwind of, above and downwind of the wind park was repeated several times (ABOVE, Fig. 5). Individual flight legs had a length of 45 km. The flight pattern was flown at an altitude of 65 m above the top of the rotor blades. On the way to and from the wind park, vertical soundings were performed to obtain information on atmospheric stability.

Such flight patterns were performed during 18 out of the 41 measurement flights.

Results of the flight patterns above wind parks have been published by Siedersleben et al. (2020).

Figure 5Example of the pattern above the wind park to investigate the downward mixing. Flight 39 was performed on 14 September 2017. It started and ended at Wilhelmshaven airport. The black stars indicate individual wind turbines. The colours show the flight altitude. On the way to the wind park and back, vertical climbs and descents were performed to study atmospheric stability.

5.1 Temperature

The temperatures encountered during the WIPAFF flights span a broad range, as the flights were performed during different seasons. The near-surface air temperature varied between 7 and 25 ^∘C (see Fig. 6). Overall, the temperature decreased with altitude. Below 60 m, data are only available during take-off and landing. Therefore, the temperature inversion below 60 m is not a typical feature above the North Sea, and therefore provided as dotted line. The averaged and maximum temperature profiles show a sudden decrease at an altitude of around 500 m and around 950 m. This is probably an artefact from the averaging method, and it is not visible in individual temperature profiles.

Figure 6Average temperature profile (black) and range of temperatures (minimum: blue; maximum: red) encountered during the 41 WIPAFF measurement flights. Additionally, the averaged profiles of flight 7 (magenta), flight 15 (cyan) and flight 31 (yellow) are included. As altitudes below 60 m altitude were only performed during take-off and landing, i.e. above land and not above the North Sea, the profiles are provided as dotted lines.

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5.2 Stability

Atmospheric stability is strongly related to season and wind direction. In spring and summer, the water surface warms relatively slowly, whereas atmospheric temperatures above land are subject to a strong diurnal cycle. Therefore, flow from land to sea during daytime very frequently results in stable conditions. For northerly wind directions, the air temperature is typically similar to the water surface temperature, so unstable or neutral conditions prevail. A rough overview of all conditions is indicated in Fig. 7. In the mean profile of the potential temperature, a clear increase is observed for the altitude interval 60 to 100 m. Also up to the altitude of 200 m, in the range of the rotor blades, an overall small increase in potential temperature with height is observed. The decreases in average and maximum potential temperatures with height at around 500 and 950 m are probably artefacts form the averaging method and are not visible in the profiles of individual flights.

Figure 7Average stability conditions (black) and range of stability (minimum: blue; maximum: red) encountered during the 41 WIPAFF measurement flights. Additionally, the averaged profiles of flight 7 (magenta), flight 15 (cyan) and flight 31 (yellow) are included. As altitudes below 60 m altitude were only performed during take-off and landing, i.e. above land and not above the North Sea, the profiles are provided as dotted lines.

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As stability typically changes with distance to the coast and with the diurnal cycle, the categorization of the flights according to one specific stability parameter is difficult and needs thorough discussion, which is addressed in Platis et al. (2019) and will be subject to another publication. The exact altitude of the temperature inversion in relation to the rotor geometry plays a crucial role in the modification of temperature and humidity profiles in the wake areas (Siedersleben et al., 2018b).

Table 2Overview of the WIPAFF measurement flights 21–41 containing the same information as in Table 1. The same abbreviations are used in as in Table 1.

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5.3 Wind speed

During the flights, wind speed at hub height varied between 2 and 17 m s⁻¹. The typical cut-in speed at which offshore wind turbines start producing power is around 3 m s⁻¹. The rated speed for offshore wind turbines is typically designed as 12 m s⁻¹, and the cut-out speed, where wind turbines are shut down, is at 25 m s⁻¹. The wind speed typically increases more strongly with altitude for stable conditions. An overview of all wind speed profiles encountered during the flights is shown in Fig. 8. The strong increase in wind speed from the surface to 50 m is an artefact as these altitudes were only sampled during take-off and landing.

5.4 Wind direction

Measurement flights were performed for mean wind directions at hub height between 80 and 330^∘. Wind directions from NW were always associated with unstable or neutral atmospheric stability. This wind sector was investigated mainly for comparison. The main focus was on stable conditions, and therefore wind from land.

Figure 8Average wind speed profile (black) and range of wind speed (minimum: blue; maximum: red) encountered during the 41 WIPAFF measurement flights. Additionally, the averaged profiles of flight 7 (magenta), flight 15 (cyan) and flight 31 (yellow) are included. As altitudes below 60 m altitude were only performed during take-off and landing, i.e. above land and not above the North Sea, the profiles are provided as dotted lines.

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5.5 Humidity

The profiles of humidity varied strongly depending on stability. For unstable conditions, an enhanced water vapour mixing ratio directly above the water surface was present. For stable conditions, humidity was often increased at higher altitudes, which in most cases is most likely caused by advection of air masses with a higher water vapour mixing ratio. Depending on the altitude of the temperature inversion in relation to the altitude of the rotor blades, humidity was either increased or decreased in the wake (Siedersleben et al., 2018b). As the relative humidity is temperature dependent, profiles of the water vapour mixing ratio are shown in Fig. 9. The water vapour mixing ratio varied between 2 and 14 g kg⁻¹. For the mean profile, a sharp decrease in the mixing ratio with altitude is present at around 500 m. This corresponds to the altitude with a change of stability as indicated by the potential temperature and an increase in the wind speed, indicating the mean altitude of the marine atmospheric boundary layer.

For completeness and for interpretation of the data, the prevailing cloud conditions based on visual observations are indicated in Tables 1 and 2.

Figure 9Average profile of water vapour mixing ratio (black) and range of mixing ratio (minimum: blue; maximum: red) encountered during the 41 WIPAFF measurement flights. Additionally, the averaged profiles of flight 7 (magenta), flight 15 (cyan) and flight 31 (yellow) are included. As altitudes below 60 m altitude were only performed during take-off and landing, i.e. above land and not above the North Sea, the profiles are provided as dotted lines.

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