As wind turbines extract energy from the wind, they leave regions of lower speed air in their wakes. For offshore wind farms, wakes are responsible for the largest single loss of energy production. Considerable effort is therefore being put to the analysis and modelling of wake effects [1
]. Normally, the wakes are invisible, discernible only through the reduced production of downstream turbines caught in the wakes. But in recent years, wakes have been visualized and put under quantitative scrutiny (both onshore and offshore) through the deployment of remote sensing methods such as lidars [10
], radars [13
] and synthetic aperture radar [14
However, direct visual observation of wakes in a wind farm remains rare. For this reason, two photographs taken on 12 February 2008 at the Horns Rev 1 offshore wind farm have become quite renowned, to the point where they have become the quintessential illustration of wind farm wakes. Even though the Horns Rev 1 photographs do not provide quantitative information about the flow field in the wakes, they do offer a dramatic illustration of the wake expansion, and of the turbulent nature of the flow in the wakes. Analysis of the images and of the meteorological conditions at the time revealed that the atmosphere was convective and that the wakes were captured by the re-condensation of fog. This process was triggered by the lifting and cooling of warm super-saturated air from the lower part of the rotor area by the swirling motion of the air in the wakes themselves [16
]. The wind speed was low, only marginally above the cut-in speed of the wind turbines.
In this paper we examine new photographs of wind farm wakes, this time taken at Horns Rev 2 on 25 January 2016 at 12.45 UTC. In contrast to the well-known picture from 2008 with unstable conditions at Horns Rev 1, the Horns Rev 2 photographs are of wakes under stable atmospheric conditions. Thus the Horns Rev 1 and Horns Rev 2 wake photographs provide a visual insight on wakes for a broad range of atmospheric conditions. Studies show that wakes in stably stratified atmospheric boundary layer [18
] differ materially from wakes in neutral and unstable conditions [20
]. From the wind farm wake analysis we are able to improve our understanding of the diverse physical processes in the atmosphere. It is important in regard to siting and planning of offshore wind farms [6
]. The topic has high relevance due to the ambitious plans on adding much more offshore wind power capacity in EU-27 and other countries worldwide [23
The description of the wind farm and presentation of the photos are presented in Section 2
. The meteorological conditions observed from meteorological ground-based instruments and satellites, described in Section 3
, are collected and combined (Section 4
). Such measurements form the basis for interpreting the local weather prevailing at Horns Rev 2 on 25 January 2016. The synoptic weather conditions are characterized from radiosonde data and atmospheric mesoscale modelling using the Weather Research & Forecasting (WRF) model (Section 5
). The wind farm production data, an engineering wake model and large eddy simulation (LES) outputs for the wind farm wake dynamics are used to interpret the wind farm wakes seen in the photos (Section 6
). A discussion on the key findings is presented in Section 7
and the main conclusions are summarized in Section 8
4. Data Presentation
Ocean surface winds at 10 m are observed from ASCAT at 10:26 UTC and 21:03 UTC. The wind field for the morning retrieval is shown in Figure 4
a. The general wind direction is from the southwest. The wind speed is lower near the coast, in particular in the northern part of the region, than further offshore. Near the Horns Rev 2 wind farm the wind direction is 217° and the wind speed is 7.8 m/s in the morning pass. In the evening retrieval, the wind direction is 214° and the wind speed is 10.9 m/s.
The sea surface temperature in the region observed from the regional multi-sensor SST climate data record from DMI is shown in Figure 4
b. A strong horizontal gradient in temperature ranging from 7 °C in the west to below 3 °C near the coast of Jutland is noticed. In the vicinity of the Horns Rev 2 wind farm the temperature is 5.2 °C. Hourly satellite SST retrievals from SEVIRI are not available some hours prior to and during the time of the obtained photos. This indirectly verifies that it was overcast. In such conditions no warming of the sea surface is to be expected [31
Time-series of lidar measurements on wind speed and direction at hub height from Horns Rev 2 are shown in Figure 5
; the instantaneous 10-m ASCAT wind retrievals are also presented for reference.
For a large fraction of the day in question, the wind direction is such that the lidar is in the wake of the wind farm. Consequently, we need another reference to estimate the freestream wind speed. We use the ten-minute mean wind speed recorded by the turbine nacelle anemometers. This is retrieved from the wind farm Supervisory Control and Data Acquisition system (SCADA). For southwestern winds turbine A07 would be a good candidate for measuring the undisturbed inflow. However, at the time of the photographs this turbine was stopped for maintenance. Instead, we use its neighbors A06 and B07, taking the maximum nacelle anemometer wind speed between the two as the proxy for the freestream wind speed, also shown in Figure 5
. The freestream wind speed is generally above the wind speed measured by the lidar, as expected when the lidar is in the wake.
Similarly, for those wind directions, the turbulence intensity is elevated at the lidar location at hub-height, as evidenced by Figure 6
. This is a consequence of the increased turbulence in the wind turbine wakes, which sweep over the lidar for most of the day, with the exception of the late afternoon/early evening. The ambient turbulence intensity ranges from 3% to 5% in un-waked conditions, while during waked conditions at the time of the photos the turbulence intensity is ~8%. We illustrate this in Figure 6
by calculating the wind directions, where the lidar is in the wake of at least one wind turbine. We use the Park wake model [33
] with a linear wake expansion parameter of 0.04, which is appropriate for offshore sites [6
Air temperatures (observed at 26 m at the transformer platform) decrease from around 10 °C to 6 °C between 9:00 and late afternoon. The pressure drops linearly from 1016 hPa to 1008 hPa on 25 January 2016 between 9:00 and 24:00 UTC as shown in Figure 7
. The virtual potential temperature, calculated from the air temperature, pressure and the relative humidity, shows a similar variation. The satellite-based SST value of 5.2 °C shows a colder surface than the air mass above. From the combined information of satellite-based SST and air temperatures it is found that the atmospheric stratification is stable.
The atmospheric conditions in the vertical dimension at and around the time of the photos are further investigated. The vertical variability in horizontal wind speed (wind shear), wind direction (wind veer) and turbulence intensity observed from the lidar at the time of the photos is shown in Figure 8
. The lidar data are listed in Appendix Table A1
and meteorological data in Table A2
. The lidar data show a wind speed increase with height, wind turning clockwise with height while the turbulence intensity decreases with height. It can be noted that the wind turbine hub-height is 68 m and the rotor diameter is 93 m; thus, blade tips extend from 21.5 m to 114.5 m above mean sea level. The data characterize the atmospheric boundary layer from hub-height to around 200 m above mean sea level.
5. Weather Conditions and Meso-Scale Modelling
The synoptic weather conditions are interpreted based on satellite cloud cover observations, weather forecast, radiosonde data and WRF model results. Several satellites observed the cloud cover over the region in the late morning on 25 January 2016. Figure 9
shows a combined cloud cover product, from ECMWF [34
], at 13:00 UTC. Horns Rev is overcast, as also visible in the photos (Figure 2
c,d). As interpreted from the ECMWF weather forecast [35
], there was a passage of a warm front. A warm air mass was advected from the southwest, associated with a high pressure over central Europe and a low pressure over eastern north Atlantic. Radiosonde data are available at Norderney [36
]; an island in the Wadden Sea around 200 km SSW of Horns Rev. The radiosonde data show strong veering (not presented) in the lowest 3 km, indicative of strong warm advection, consistent with the warm front. The veering is consistent with the observed change in wind direction at the wind farm (Figure 8
). The cloud cover at Norderney is similar to that at Horns Rev (Figure 9
For the numerical weather prediction simulations we use the WRF model [37
]. WRF has ability to model a stable stratified marine boundary layer according to [38
]. The model domain is shown in Figure 10
. The outer and lower boundaries are forced by ERA-Interim [39
] and the SST is from DMI’s high resolution data [29
]. For the surface layer description, we used the Mellor-Yamada-Nakanishi-Niino (MYNN) surface layer scheme that applies Monin-Obukhov similarity theory [40
]. Nudging only takes place in the outer domain. In the vertical direction, we defined in total 70 vertical levels, 23 of which are in the first 500 m. For the turbulence mixing in the vertical direction, we used the MYNN 2.5 planetary boundary layer scheme [41
]. Then, the innermost domain is run twice, once without and once with the Horns Rev 1 and 2 wind farms. The wind farms are parametrized by the Explicit Wake Parametrisation (EWP) [42
]. A 36-h spin-up period prior to 25 January 2016 at 13:00 UTC, i.e., 15 min after the photos are taken, is applied.
The WRF model results compare well with radiosonde data on temperature and relative humidity (Figure 11
The modelled boundary layer height is around 240 m at the inversion. The radiosonde measurements at Norderney show a 400 m thick temperature inversion directly above the cold sea surface. The modelled temperature gradients in the first 400 m are similar. However, the temperature stratification is slightly different in the model. Instead of an inversion layer with a constant temperature lapse rate, it simulates a mixed layer in the first 200 m, which is capped by a steep inversion.
WRF results include vertical profiles from 0 to 600 m of wind speed, turbulent kinetic energy (TKE), temperature and liquid water content. The results at Horns Rev are presented in Figure 12
for calculations without and with the wind farms included in WRF. The profiles present an average over the Horns Rev 2 wind farm. As expected, compared to the freestream wind speed conditions from the simulations without the wind farm, the wind speed reduces when the wind farm is included. The TKE increases above hub-height and decreases below hub-height, due to an increased and decreased TKE shear production, respectively. The temperature profile—a mixed layer capped by a strong inversion—looks very similar to that at Norderney. The simulations show liquid water content of around 0.1 g/kg at hub-height.
The difference in liquid water content between the simulation without and with wind farms in the horizontal plane at hub-height is shown in Figure 13
. We find reduced liquid water content of up-to around 0.03 g/kg in the wake of the wind farm that extends in the North-East direction, which is caused by the mixing in of warm air from aloft. This reduction of the liquid water content corresponds to the tendency in dissolving the fog layer at the end of and behind the Horns Rev 2 wind farm in the photos.
The photos taken on 25 January 2016 at 12:45 UTC demonstrate that wind turbines influence the atmosphere. Upwind of the wind farm at the front row of turbines the fog layer is less than 20 m deep. The undisturbed fog is located below the lower tip of blades. This shallow fog layer is cold water advection fog of maritime origin [47
]. The warm saturated air mass was advected from the southwest, where the SST was higher than at Horns Rev. A strong gradient in SST in the region with colder water near the coast enhanced the favorable conditions for the generation of cold water advection fog. The air temperature at Horns Rev is around 8 °C and the sea around 5 °C, thus stable atmospheric stratification prevail, with a shallow layer of fog above the ocean surface; this resulted in this new wake visualization case.
For stable conditions strong clockwise wind veering is expected in the surface layer [48
]. The waked lidar data from hub height to 200 m shows around 17° veering. The wind direction observed at 10 m from ASCAT is consistent with around 5° veering compared to lidar hub height data. Also the Norderney radiosonde data confirms strong veering.
For stable conditions strong shear is expected in the surface layer [49
]. At the waked lidar position the wind speed at hub height is 11 m/s and at 200 m 18 m/s, while the freestream wind speed at the front turbines is 13 m/s. Satellite data at 10 m height shows around 2 m/s lower wind speeds than the lidar data. The satellite wind speeds are representative at 10 m above the surface, assuming neutral atmospheric stratification. The atmospheric stratification in this case is stable, thus, an underestimation of the 10 m wind speed is to be expected. Yet the combined picture of local winds at Horns Rev confirms strong wind shear. The ambient turbulence intensity is low (~3%) also indicative of stable conditions.
In general, there is an overall agreement of evidence between the synoptic weather conditions, the satellite observations, the in situ observations and the WRF model outputs. This agreement leads to a confidence in having provided a consistent description of the conditions under which these new, spectacular images of wind turbine wakes emerged.
The turbines in the front row produce at rated power (2300 kW) as the freestream wind is at rated speed (~13 m/s). The wind direction is such that only few downstream turbines are in full wake. Interestingly, the wind direction is not homogenous over the wind farm according to the SCADA data. In the southern row of turbines the wind directions vary. It is found that the Park wake model provides better agreement to power production data using multiple simulations of inflow wind direction than one simulation. Thus the general assumption of homogenous, stationary flow for the entire wind farm is not fulfilled as required by the wake model [33
], and a piecewise model effort therefore is necessary in this case.
During stable conditions long, narrow wind wakes are to be expected [18
]. From inspection of the photos the fog cones downstream of the front row of turbines are slightly larger than one rotor diameter at a distance of several rotor diameters downwind. The separation distance between turbines C07 and D06 is 11.4 rotor diameters (1058 m), and the direction between these turbines is 216°. Due to the curved wind farm layout different distances are found between turbines. The question though is to which degree the fog cones and the wind turbine wakes are related. Model results from LES, including a temperature scheme, indicated condensation in the near wake. It is found that warm near-saturated air above a colder sea is condensed to fog in the near wake. This occurs when the dew-point temperature is reached primarily in the lower part and in the left side of the wake, when seen from behind. The LES results provide a novel and good comparison to the visually observed fog cones of the full scale wind turbine wakes.
Clearing of the fog is noticed in the far wind farm wake region in the photos. The ocean is visible as well as several turbines and a service ship (near turbine L03). The WRF model results on liquid water content at hub-height, without and with the wind farm, show a tendency in dissolving the fog layer downstream of the wind farms (Figure 13
). The process is caused by mixing of warm air from aloft to the surface. The horizontal extend of the clearing of fog in the photos is hard to outline but seems to last very long. The results from WRF show drying effects due to the wind farms more than 100 km downwind and also persist over land, in Jutland.
Previous studies [3
] have documented that large wind farms on land impact the atmospheric conditions such that increased land surface temperatures (LST) are observed in stable stratification, typically during nighttime. This has been explained from downward mixing of warm air from aloft. Similar results for offshore wind farms have not been published (to our knowledge). Yet stable conditions occur offshore. According to [2
] stable conditions prevail at Horns Rev around 20% to 25% of the time for westerly flow and around 35% of the time for easterly flow. Thus there is potential for atmospheric processes of downward mixing of warmer air potentially heating the ocean surface during stable stratification.
Satellite-based SST can be retrieved with an accuracy of 0.1 K while satellite-based LST has a target accuracy of 1 K [53
]. The reasons for this difference in accuracy of SST vs. LST are due to the ocean being approximately homogenous and isothermal with relatively low temporal variation and with emissivity near black body, while most land surfaces are heterogeneous and non-isothermal with high temporal variation and with emissivity of grey body. Emissivity on land varies with vegetation cover, surface moisture and viewing angle and generally, an uncertainty of 1% in emissivity will result in about 0.5 K error in the LST [53
]. Thus from the perspective of the SST retrieval accuracy it would be feasible to quantify wake-induced warming effects offshore. In fact, only the relative difference within the wake influenced regions versus neighboring non-disturbed regions would need to be compared as in the land-based studies [3
]. However, due to the higher heat capacity of water and the continuous mixing by wind and ocean currents, such downward mixing of warmer air would need to be persistent in order to have a significant effect, and be measurable. At the time of the photos it is overcast, thus an investigation at suitable resolution cannot be performed.
Nonetheless, the case study pictures from Horns Rev and the WRF model results indicate the drying effect within the far wake of an offshore wind farm. These results are novel and indicative of the same atmospheric processes taking place at large land-based wind farm during stable conditions.
The wind farm wake photos from 12 February 2008 tell a much different story about the atmospheric flow and wind farm wake conditions than this new case from 2016. On that day in 2008 warm water advection fog occurred [16
]. The fog layer was very shallow upwind of the turbines. The cold humid air above warmer sea was re-condensed to fog in the wake by upward mixing of saturated air. The atmospheric stratification was unstable, the turbulence intensity was high and winds were very weak, near the cut in wind speed of ~4 m/s. Most front row wind turbines and a few others were in operation with very low production (~80 kW out of 2000 kW rated power) while the majority of turbines were stopped due to low winds. From visual inspection of the photos from 2008 a bumpy convective appearance of fog is seen with wide wakes. In contrast, the photos from 2016 show fog in narrow wakes with a smooth appearance. The two situations can be characterized from dispersion theory as looping plume pattern in unstable conditions and fanning plume pattern in stable conditions [54
] (pp. 322–327).
Some similarities between the two photo cases with fog in wind farms are: (i) a shallow undisturbed fog layer near the sea surface upwind of the turbines; (ii) fog plumes emerging at hub-height due to wind turbine rotation; and (iii) high level clouds that allow just enough sunshine coming through to outline clear sunlit and shaded regions of the curvature of fog downwind of the turbines.
In summary, the wind farm wake case at Horns Rev on 12 February 2008 [17
] is highly contrasting to the case on 25 January 2016. The differences are: wind speed near cut in vs. rated speed; few turbines in operation vs. most turbines in operation; unstable vs. stable atmospheric stratification; and cold humid air above a warm sea surface causing warm water advection fog vs. warm humid air above a cold sea surface causing cold water advection fog. Within the near wakes the 2008 case is explained by warm humid air up-drafted from below in the counter-rotating swirl. The condensation appears to take place where high axial velocity and high TKE exist. In contrast, in the 2016 case the fog in the near wake occurs, where the temperature reaches the dew-point, which seems to be homogenously distributed at the lower parts and in the left of the wake. Furthermore, the 2016 case is highly interesting as in the far wake region the photos reveal clearing of the fog further into the farm. This is explained from mixing of warm air from aloft that dispersed the fog. This result is obtained using the WRF model with inclusion of the wind farm and without wind farm, to quantify the drying effect. Key data for the two cases are summarized in Table 1
The photos of foggy conditions from Horns Rev 2 wind farm on 25 January 2016 show an exceptional case of cold water advection fog and stable conditions. Due to the stable stratification the wakes are long and narrow with a smooth appearance. The wind speed is near rated speed (~13 m/s) thus most turbines produce at rated capacity. The fog in the near wake is caused by upward moving air parcels from the shallow fog layer, and the air reaches the dew point temperature in the lower and left parts of the wind farm wake, thus fog emerges in a cone-shape wake structure downwind of the turbines. The conclusion is based on LES modelling of the wake dynamics, which have been used to elucidate on the fog generation through a simple temperature and phase-transition scheme. Hence, LES results and visually observed fog cones are compared directly for the first time.
The wake photos from Horns Rev 1 wind farm on 12 February 2008 are by all means presenting an opposing situation. The fog is warm water advection fog and the atmosphere is unstable. The wind speed is near the cut in wind speed (~4 m/s) and most turbines are idle and only front row turbines and few others operate with very low production. The wind turbine wakes cause condensation in wake regions with high TKE and the wakes are seen to be broad with a convective appearance.
Finally, the photos from 2016 show clearing of the fog in the far wake. The physical processes involved in this are modelled from WRF without and with a parametrization for the wind farm included, and the difference in liquid water content show that a drying effect appear downwind of the wind farms for more than 100 km. Thus the photos confirm this drying process, which for the first time is visualized and modelled for an offshore wind farm.