The Høvsøre tall wind profile experiment – a description1
of wind profile observations in the atmospheric boundary2
layer3
Alfredo Pena ([email protected]), Rogier Floors and Sven-Erik Gryning4
DTU Wind Energy, Risø Campus, Technical University of Denmark,5
Frederiksborgvej 399, 4000 Roskilde, Denmark6
Abstract. We present an analysis of data from a nearly one-year measurement7
campaign performed at Høvsøre, Denmark. Høvsøre is a coastal farmland area, where8
the terrain is flat. Within the easterly sector upstream of the site, the terrain is9
nearly homogenous. This topography and conditions provide a good basis for the10
analysis of vertical wind speed profiles under a wide range of atmospheric stability,11
turbulence, and forcing conditions. One of the objectives of the campaign was to12
serve as a benchmark for flow over flat terrain models.13
The observations consist of combined wind lidar and sonic anemometer mea-14
surements at a meteorological mast. The sonic measurements cover the first 100 m15
and the wind lidar started measuring at 100 m every 50 m in the vertical. Results16
of the analysis of the observations of the horizontal wind speed components in the17
range 10–1200 m and surface turbulence fluxes are illustrated in detail combined18
with forcing conditions derived from mesoscale model simulations.19
Ten different cases are here presented. The observed wind profiles approach well20
the simulated gradient and geostrophic winds close to the simulated boundary-layer21
height during both barotropic and baroclinic conditions, respectively, except for a22
low-level jet case as expected. The simulated winds are also presented for complete-23
ness and show good agreement with the measurements, generally underpredicting24
the turning of the wind in both barotropic and baroclinic cases.25
Keywords: Atmospheric boundary layer, Baroclinity, Geostrophic wind, Sonic mea-26
surements, Turbulence fluxes, Wind lidar, Wind profile27
1. Introduction28
There are several type of models for the prediction of the wind and its29
related parameters in the atmospheric boundary layer (ABL) ranging30
from the mesoscale, e.g. the advanced Weather Research and Fore-31
casting (WRF) model (Skamarock et al., 2008), to the microscale,32
e.g. the Wind Atlas Analysis and Application Program (WAsP) model33
(Mortensen et al., 2007). Particularly, the microscale models have been34
developed to improve the wind predictions over complex, forested, and35
heterogeneous terrain. However, these assume near-neutral stability36
and barotropic conditions in most cases, which might be far from the37
actual conditions at many sites where wind predictions are important,38
c© 2013 Kluwer Academic Publishers. Printed in the Netherlands.
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2 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
and thus they become highly uncertain, especially above the surface39
layer.40
Understanding of the change of the horizontal wind velocity compo-41
nents with height and, therefore, of the turning of the wind in the ABL42
under different surface, wind, and forcing conditions is essential for the43
parametrization of atmospheric processes and the improvement of both44
microscale and mesoscale models, e.g. via the planetary boundary layer45
(PBL) parametrizations. This understanding can be partly achieved46
through the analysis of wind measurements in the ABL.47
Observations of the wind velocity components in the ABL are how-48
ever scarce and in many cases controversial as the instrumentations49
used in the experiments were inaccurate (radiosondes and similar tech-50
niques in most cases), the assumptions for the analysis of the measure-51
ments were too simplistic, and the surface and forcing conditions were52
not always measured. To the authors’ knowledge, there are only three53
experiments particularly designed for the analysis of the ABL winds.54
The first is the Leipzig experiment, initially described by Mildner55
(1932), which has been used extensively as a benchmark for numerical56
and analytical flow models. The data commonly used are actually the57
results from the reanalysis performed by Lettau (1950), who assumed a58
neutral and barotropic atmosphere to reconstruct the vertical profiles59
of wind and turbulent exchange coefficient, although the conditions60
were probably stable and the upwind flow inhomogeneous (Riopelle and61
Stubley, 1988; Bergmann, 2006). There is also controversy on the sur-62
face roughness and the boundary-layer height values of the experiment63
(Lettau, 1962; Hess, 2004).64
The second is the O’Neill experiment, performed in Nebraska and65
designed by Lettau (Lettau and Davidson, 1957), who tried to avoid66
some of the problems inherent to the Leipzig experiment such as ter-67
rain heterogeneity and unknown atmospheric stability conditions. The68
ABL winds were however measured using both balloons, radiosondes,69
and airplanes, although Lettau already anticipated that ground-based70
methods were needed for accurate measurements (Lettau, 1990). This71
experiment is not popular among modellers.72
The last is the Wangara experiment, performed in Australia in 196773
(Clarke et al., 1971). Hourly double-theodolite observations of pilot bal-74
loons were performed at different stations over 40 days under different75
surface, stability, and forcing conditions. However, as pointed out by76
Clarke and Hess (1974), thermal winds were not accurately estimated,77
and the surface friction velocity and heat flux had to be indirectly78
estimated from a drag-coefficient method and wind and temperature79
profiles, respectively.80
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.2
The Høvsøre tall wind profile experiment 3
In wind energy, there is now an understanding of the importance of81
accurate wind-speed measurements and the observation of the vertical82
wind shear for wind and load predictions. However, there is very little83
knowledge about the influence of (and the mechanisms controlling)84
the turning of the wind, the boundary-layer height, and baroclinity85
on wind turbines and structures. The Tall Wind Profile experiment,86
performed at a nearly flat and homogenous area in Denmark, observed87
ABL winds quasi-continuously during one year combining a wind lidar88
and meteorological (met) mast measurements to attempt to respond to89
the late challenges brought by the wind community. Here, we present90
ten cases (out of a much larger dataset), where the ABL winds were ac-91
curately measured up to about 1000 m and the forcing and winds were92
simulated with a mesoscale model. We first provide some definitions93
(Section 2) useful for the interpretation of the observations. We then94
describe the site, the measurements, and the modelling in Section 3.95
The data analysis is explained in Section 4 and illustrates the cases96
explored in this study. Summary and conclusions are provided in the97
last section.98
2. Definitions99
The three wind speed components (u, v, w) are here placed on a left-100
handed coordinate system (see Fig. 1), being u and v the horizontal and101
w the vertical wind speed components (the latter aligned with the z-102
axis, i.e. the height above the ground). In this fashion, by aligning u at103
the surface (as shown in Section 3 this means at a 10-m height) with the104
horizontal wind speed vector (i.e. with the wind direction), v is zero105
at the surface increasing when the wind vector turns clockwise with106
height (veering wind) and decreasing when it turns counterclockwise107
with height (backing wind). The horizontal wind speed magnitude U108
at any height is then computed as109
U =(
u2 + v2)1/2
. (1)
The friction velocity u∗ is defined as110
u2∗=
(
u′w′2+ v′w′
2)1/2
, (2)
where the overbar indicates a time average and the primes fluctuations111
over the average. The Obukhov length L is defined as112
L =−Tv u3
∗
κ g w′T ′
v
, (3)
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.3
4 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
U
θ
...............................
................................................
u
v
EW
N
S
x
y
Figure 1. Coordinate system used for the wind profile and the estimation of thesurface geostrophic and thermal winds. U is the horizontal wind speed vector at thesurface and θ the wind direction from the geographical north
where Tv is the virtual temperature, κ the von Karman constant (here113
we use the value 0.4), g the gravitational acceleration, and w′T ′
v the114
virtual kinematic heat flux.115
In the surface layer and under neutral atmospheric conditions, the116
logarithmic wind profile117
U =u∗κ
ln
(
z
zo
)
, (4)
where zo is the roughness length, is commonly used to predict the wind118
speed over flat, non-forested, and homogenous terrain without taking119
into account its turning with height.120
We derive the surface geostrophic, the gradient, and the ‘total’121
geostrophic wind (the latter known here simply as geostrophic wind)122
from the WRF simulations (explained in Section 3). The gradient wind123
takes into account the curvature of the isobars in the surface geostrophic124
wind. For their derivation, we define their two components oriented125
with the x and y axis, eastwards and northwards, respectively (see126
Fig. 1).127
The two components of the surface geostrophic winds(
Gox , Goy
)
are128
then given as,129
Gox = −
1
ρ fc
∂Po
∂yand (5a)
Goy =1
ρ fc
∂Po
∂x, (5b)
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The Høvsøre tall wind profile experiment 5
where ρ is the air density, fc the Coriolis parameter, and Po the mean130
sea level pressure. The baroclinic effect on the two components of the131
geostrophic wind (Gx, Gy) is derived as (Holton and Hakim, 2004),132
GTx = −
1
fc
∂Φz − ∂Φo
∂yand (6a)
GTy =1
fc
∂Φz − ∂Φo
∂x, (6b)
where Φ is the geopotential, and the subindexes z and o refer to a given133
height and the surface, respectively. The magnitude of the gradient134
wind Gg is a function of the magnitude of the surface geostrophic wind135
Go =√
G2ox +G2
oy (Kristensen and Jensen, 1999)136
Go
fc R
(
Gg
Go
)2
+Gg
Go− 1 = 0, (7)
where R is the radius of the curvature of the isobars. The two compo-137
nents of the gradient wind(
Ggx , Ggy
)
are computed assuming that the138
angle between them is equal to that between Gox and Goy .139
The geostrophic wind components are thus computed as140
Gx = Ggx +∆z GTx and (8a)
Gy = Ggy +∆z GTy, (8b)
where ∆z is the difference between a given height and the surface (the141
z and o levels in Eqs. (6a) and (6b)). uG and vG hereafter refer to142
Gx and Gy when rotated into the u-v coordinate system (Fig. 1). The143
magnitude of the geostrophic wind is given as UG =√
u2G + v2G.144
3. Site, measurements, and WRF modelling145
3.1. Site146
The measurements were performed at the National Test Station for147
Wind Turbines located in a coastal area known as Høvsøre in west148
Jutland, Denmark (Fig. 2). Høvsøre is a flat farmland area, which is149
fairly homogeneous with disturbances on the flow from the presence of150
the North Sea and the Nissum Fjord, 1.7 km west and 950 m south,151
respectively, some scattered trees, houses, and crop patches east, the152
village of Bøvlingbjerg 3 km south-east, and five wind turbines north153
of a meteorological mast placed south of the station at a height of 2 m154
above mean sea level.155
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6 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
120◦
Meteorological mast
1 km
Nissum
Fjord
North
Sea
30◦
Figure 2. National Test Station for Wind Turbines at Høvsøre, Denmark. The mete-orological mast location (circle) and the analyzed sector are also shown. The imagewas taken from Google Earth
Easterly winds (within the range 30◦–120◦) are therefore nearly ideal156
for the study of flow over flat and homogeneous terrain. Thus, we focus157
our analysis to these directions, although winds within this range are158
not the predominant ones at Høvsøre (Pena, 2009).159
3.2. Measurements160
The measurements come from two different types of instrumentation:161
sonic anemometers at the meteorological mast and a wind lidar system.162
3.2.1. Sonic measurements163
Metek USA-1 scientific sonic anemometers are placed at 10, 20, 40, 60,164
80, and 100 m on the booms facing north of the meteorological mast.165
Thus, for easterly winds the mast effect on the sonic measurements is166
negligible. Other details about the mast and its instrumentation can be167
found in Jørgensen et al. (2008). The recording frequency of the sonic168
time series is 20 Hz.169
3.2.2. Wind lidar170
AWLS70 WindCube, a pulsed wind lidar from the company Leosphere,171
was installed ≈10 m south-west from the meteorological mast during172
the period April 2010–March 2011. The WLS70 measures the radial173
velocity at four azimuthal positions separated 90◦ in the horizontal174
plane with an inclination of 15◦ from the zenith and derives the three175
wind-speed components assuming horizontal flow homogeneity. The176
wavelength, the pulse length, and pulse energy of the laser are 1.5 µm,177
400 ns, and 20 µJ, respectively. Under ‘good’ aerosol conditions, the178
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The Høvsøre tall wind profile experiment 7
system reports measurements up to 2 km. Recorded data depend on179
the instrument’s threshold for the carrier-to-noise ratio (CNR), which180
was left equal to the default value (−35 dB). The instrument measures181
from a height of 100 m every 50 m at a rate of ≈10 s for each azimuthal182
position. The measurement volume at each azimuthal position and183
height extends ≈60 m radially.184
−200
0
200
−2000
2000
100
200
300
400
500
600
x [m]y [m]
z[m
]
EN
W
S−200 −100 0 100 200
−200
−150
−100
−50
0
50
100
150
200
x [m]
y[m
]
N
W
S
E
←−ul
←−vl
Figure 3. WLS70 wind lidar scanning pattern from side (left) and top (right) views.The instrument is shown in the grey rectangle, the mast in the white square, andthe four azimuthal radial positions in black, cyan, blue, and red colours
As shown in Fig. 3, the wind lidar was positioned with an offset185
of 50◦ from the north in order to avoid influence of the mast on the186
eastern azimuthal position shown in blue. This is important as one wind187
lidar wind-speed component, vl, is related to the difference between the188
eastern and western radial velocities (in this case indicated by the red189
and blue points).190
3.3. WRF modelling191
We use outputs of simulations using the WRF model version 3.4 (Ska-192
marock et al., 2008). Two domains are used with horizontal resolutions193
of 18 and 6 km as shown in Fig. 4.194
The model was run in analysis mode every 10 days starting at195
0000 UTC during April 2010–April 2011 (see details in Gryning et al.,196
2013b). Initial and boundary conditions came from the National Center197
for Environmental Prediction (NCEP) final analysis data and real-time198
global sea-surface temperature analysis from NCEP. Model outputs199
from 24 to 264 h were used to generate continuous time series of 10-200
min resolution (24-h spin-up period). Timesteps were 120 and 40 s for201
the outermost and innermost domains, respectively. The first 11 vertical202
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8 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
Figure 4. Model outermost (D1) and innermost domains (D2) used for the simu-lations (black lines). The red square shows the area used for the derivation of thepressure and geopotential gradients
model levels are approx. at 14, 43, 72, 101, 130, 191, 311, 485, 705, 966,203
and 1263 m. The first-order Yonsei University (YSU) PBL scheme is204
used (Hong et al., 2006). The boundary-layer height is estimated in the205
PBL parametrization as a function of the ratio of the critical to the206
bulk Richardson number at the boundary-layer top. The model was207
nudged in the outermost domain above the 11th model level towards208
the analysis data. Other details about the model setup can be found in209
Gryning et al. (2013a).210
4. Data analysis211
The WLS70 system provides two datasets: a ‘fast’ one with the ≈10 s212
measurements at each height and azimuthal position and a ‘slow’ one213
with outputs for the same parameters but based on 10-min averages.214
The sonic time series of the wind velocity and temperature were recorded215
on a third dataset. Here we provide a description of the filtering and216
selecting criteria we use on the three datasets to produce the final217
output with wind speed profiles from 10 m up to ≈1000 m and sonic218
turbulence measurements from 10 m up to 100 m averaged in 30-min219
periods.220
The first part of the analysis is performed on the ‘slow’ wind lidar221
dataset. We extract 10-min data from 100 up to 600 m to increase the222
number of vertical profiles for the study. We also apply a filter so that223
each 10-min profile shows measurements every 50 m with a minimum224
mean CNR of –22 dB, used by Floors et al. (2013) and Pena et al. (2013)225
for accurate wind speed measurements, and with 100% availability (this226
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The Høvsøre tall wind profile experiment 9
is a number relating the amount of ≈10 s records where CNR > −35 dB227
within the 10-min period).228
We then exclude non-easterly winds by looking at the wind direction229
at 100 m only. Since the final analysis is performed in 30-min averages,230
we extract data where three consecutive 10-min intervals are found.231
We also apply a stationarity check based on the criteria by Lange232
et al. (2004), where the ratio between any of the three consecutive233
10-min mean values of U and wind direction is limited to the interval234
[0.8,1.2]. This is mostly done to avoid large differences between the235
three consecutive 10-min periods. We extract the wind lidar ‘fast’ time236
series correspondent to those 30-min periods.237
Statistics of all wind lidar parameters are performed based on the238
30-min periods. Here we choose to present those related to the mean239
wind speed components only, since turbulence quantities are highly240
influenced by the wind lidar’s measurement volume and scanning pat-241
tern. The over/underprediction of the wind lidar turbulence (compared242
to that of a sonic measurement) depends on the turbulence spectral243
tensor, the observed height, and atmospheric stability, among others244
(Sathe et al., 2011; Sathe and Mann, 2012).245
We then extract the concurrent sonic time series; these are linearly246
detrended over the 30-min period. u∗ and L are estimated from the247
sonics; here we assume that the sonic temperature and kinematic heat248
flux are good estimates of Tv and w′T ′
v in Eq. (3). We use the crosswind249
corrections in Liu et al. (2001) for w′T ′
v. However, the sonics did not250
continuously operate during the wind lidar campaign. We therefore251
have to make a compromise between data amount and number of sonic252
levels; we leave out of the analysis the sonics at 20, 60, and 80 m. The253
total number of combined sonic/wind lidar 30-min observations is 371254
(we also check that on each wind lidar 30-min time series, there are at255
least 160 of the ideal ≈180 records). Table I shows a summary of the256
results of the filtering criteria.257
We extract the 10-min instantaneous outputs from the WRF simu-258
lations correspondent to the time stamps of the combined sonic/wind259
lidar observations and average them in 30 min means. The gradi-260
ents of geopotential and mean sea level pressure in Eqs. (5a)–(6b)261
are computed from these outputs over a 300 km square around the262
meteorological mast (see Fig. 4). Linear regression is applied to the263
northward and eastward gradient of the mean sea level pressure field.264
Similarly, the gradient of the geopotential difference in Eqs. (6a) and265
(6b) is computed. The gradient of the geopotential difference between266
any given model level and the first one is computed using linear regres-267
sion; this results in the baroclinic term at each level that is added to268
the gradient wind. We estimate the gradient wind in Eq. (7) assuming269
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10 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
Table I. Results of the analysis of measurements after the filtering and selectingcriteria described in Sec. 4. The total number of potential 10-min measurementsfor the period of the wind lidar campaign at Høvsøre is 49968. The wind lidarreports 39173 10-min mean measurements at least at one height
Filtering criteria applied Number of samples/profiles left
Wind lidar measurements at each height 15772 10 min
in the range 100–600 m after availability
and CNR criteria
Easterly winds only (30◦–120◦) 2592 10 min
Three consecutive 10-min periods 1857 10 min
Stationarity criterion 1713 10 min (571 30 min)
Sonic availability (10, 40 and 100 m) 371 30 min
that in a given area the pressure field can be described by the surface270
(Kristensen and Jensen, 1999),271
P (x, y) = Pr + Pxx+ Pyy + 0.5(
Pxxx2 + Pxyxy + Pyyy
2)
, (9)
where Pr is a reference pressure and Px, Pxx, Pxy, Py, and Pyy are the272
first and second derivatives with respect to x and y, respectively. The273
curvature can then be estimated using this field as (Kristensen and274
Jensen, 1999)275
R =
(
P 2x + P 2
y
)3/2
PyyP 2x − 2PxyPxPy + PxxP 2
y
. (10)
The curvature of the isobars is estimated using the algorithm described276
in Shary (1995), which fits Eq. (9) to a 3 by 3 grid in a least-squares277
sense. A mean curvature is then computed for all grid points in the278
area of interest around the site.279
4.1. Wind lidar accuracy280
The wind lidar and the sonic measurements overlap at the 100-m height.281
Figure 5 illustrates a comparison of the total 371 30-min observations282
of U and direction from the 100-m sonic and wind lidar. As shown both283
wind speed and direction measurements show a very high correlation,284
although the techniques and the measurement volumes are different.285
The sonic shows a slightly higher wind speed compared to the wind286
lidar particularly within the high wind speed range. For the wind profile287
analysis, we scale/adjust the wind lidar wind speed measurements at288
all heights (of both components) so that the 100-m wind lidar matches289
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The Høvsøre tall wind profile experiment 11
the sonic observations at 100 m. The wind lidar shows an offset of290
4–10◦ with the sonic wind direction and as with the wind speed, we291
correct/adjust all wind lidar directions so that in the wind profile292
analysis both show the same wind direction at 100 m.293
0 3 6 9 12 15 180
3
6
9
12
15
18
sonic wind speed [m s−1]
lidarwindspeed[m
s−1]
y = 0.95xy = 0.93x + 0.21R2 = 0.98N = 371
40 60 80 100 120
40
60
80
100
120
sonic wind direction [deg.]lidarwinddirection[deg.]
y = 0.92xy = 0.95x − 2.0R2 = 0.99N = 371
Figure 5. Comparison of the sonic anemometer and the wind lidar 30-min measure-ments at 100 m of horizontal wind speed magnitude (left frame) and wind direction(right frame). The observations are shown with grey markers together with a 1:1 solidline in black. The results of a linear regression through origin, a linear regressionwith offset, the Pearson’s linear correlation coefficient (R2), and the number ofobservations (N) are also given
4.2. Boundary-layer wind profiles294
Here we describe and illustrate some cases (ensemble means) that can295
be studied and further modelled based on the combined sonic/wind296
lidar data and the simulations (hereafter all WRF simulations are297
referred to as simulations). They are selected because they show par-298
ticular wind speed and turning of the wind situations, and a variety of299
surface and simulated forcing conditions. Table II provides a summary300
of the ten selected cases.301
For each case the ensemble mean of 30-min averages of observed302
vertical profiles of u, v, and U from 10 up to 600 m is illustrated. As303
mentioned before, we aligned u at 10 m with U at 10 m (so v at 10 m304
is always 0 m s−1). The turning of the wind can therefore be estimated305
from the angle between v and u (see Fig. 1).306
The median of the simulated boundary-layer height (zi) is also shown.307
Because in some cases zi is between 600 and ≈1200 m, we also illustrate308
the ensemble mean of the concurrent 10-min wind lidar profiles from309
650 up to 1200 m. These are shown in a different colour because they310
might be more uncertain than the measurements below. This is due311
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12 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
Table II. Summary of Tall wind profile cases. All cases represent observationsperformed in 2010
Case Observation period Description
(local time)
1 May 5, 0530–0700 Very stable surface conditions, high wind
veering, and low forcing
2 June 9, 0600–0730 Neutral to stable surface conditions and low
boundary-layer height
3 Apr. 25–26, 2200–0130 Low-level jet and highly baroclinic atmosphere
4 Sep. 8, 0150–0620 Stable surface conditions and high forcing
Sep. 8–9, 2040–0700
5 Sep. 7, 1330–1700 Neutral surface conditions and barotropic
Sep. 8, 1330–1650 atmosphere
Sep. 9, 1400–1830
6 May 7, 0830–1630 Slightly unstable surface conditions, high
forcing, and nearly barotropic atmosphere
7 Sep. 27, 1320–1920 Neutral surface conditions and baroclinic
atmosphere
8 Nov. 24, 0200–0330 Slightly stable surface conditions and highly
baroclinic atmosphere
9 Sep. 25, 0940–1420 Very unstable surface conditions and low forcing
10 Dec. 12, 0820–0950 Stable surface conditions and highly baroclinic
atmosphere
to their generally low CNR (it might be lower than −22 dB) and312
that the amount of “concurrent” measurements might decrease with313
height (neither the CNR nor the availability criteria are applied to314
these retrievals).315
Together with the observed profiles, the simulated gradient and316
geostrophic winds and simulated wind outputs are shown. They are317
also rotated using the observed wind direction at 10 m. The prediction318
of U from the log profile, Eq. (4), using the observed u∗ value at 10 m319
and zo = 0.015 m (Pena et al., 2010b; Pena et al., 2010a), up to zi is320
also illustrated. In Tables III–VIII, the ensemble mean of the measured321
and simulated parameters for all the discussed cases are given.322
4.2.1. Case 1323
Here, the wind lidar observed some of the largest values of turning324
of the wind: the wind veers 43◦ and 66◦ in the first 100 and 200 m,325
respectively, and backs slightly above this. This is due to a small baro-326
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The Høvsøre tall wind profile experiment 13
clinic component clearly observed in v (see Fig. 6, where both v and U327
decrease above 200 m both in the observations and the simulated wind328
and geostrophic components). The observed wind direction at 10 m is329
66◦, so this small baroclinic component decelerates the flow due to the330
colder air over land compared to the warmer air over sea.331
−1
0
1
2 U100
U10
G14G100
N
S
EW
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 6. Observed (black circles) and simulated (green lines) mean vertical profilesof u, v, and U for case 1. The error bars represent± one standard deviation. Observedprofiles from 650 up to 1200 m are shown in cyan circles. The simulated zi value isshown in the dashed grey line. The gradient and the geostrophic winds are shown inblue and red lines, respectively. The prediction using the log profile is also illustratedin the grey solid line. Observed horizontal wind speed vectors at 10 m and at a heightclose to the simulated zi, and simulated geostrophic winds at the first model level(≈14 m) and at a height close to the simulated zi are shown above the profiles
Close to the surface the observed conditions are very stable and the332
stability increases with height as shown by the z/L values in Table IV.333
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.13
14 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
The observed friction velocity at 10 m is very low (u∗ = 0.19 m s−1)334
and decreases linearly with height (the observed surface winds and335
simulated forcing are rather low). The simulated zi is 87 m; the closest336
model level to the zi value (i.e. 101 m) shows a geostrophic wind angle337
(i.e. that between the simulated geostrophic wind and the observed338
wind at 10 m) of 42◦, which is very close to the observed turning of339
the wind. Although the simulated winds agree reasonable well with the340
behaviour of both observed u and v (for such a complicated modelling341
scenario), the turning of the wind is highly underestimated; it is 20◦342
and 31◦ at 101 and 191 m, respectively.343
4.2.2. Case 2344
The simulated zi is relatively low (169 m), and the observed profiles of345
u, v, and U show a wind maximum at ≈350 m and rapidly decrease346
upwards (Fig. 7). This might be due to wind deceleration due to baro-347
clinity (particularly for u). The observed wind direction at 10 m is 69◦,348
so u decelerates due to the warmer air south compared to that north of349
Høvsøre. Both observed u and U approach the simulated geostrophic350
wind high above zi. The observed wind veers 8◦ and 26◦ in the first 100351
and 250 m, respectively, agreeing with the simulated geostrophic wind352
angle (28◦ at 191 m). Thus zi is probably between the simulated value353
and 250 m.354
Near the surface the observed atmospheric conditions are close to355
neutral and become slightly stable with height (Table IV). The observed356
friction velocity at 10 m is 0.37 m s−1 and is relatively constant with357
height. The wind speeds are not as low as in Case 1 and the log profile358
predictions are much closer to the observations. The simulated winds359
are in very good agrement with the observed v component, but highly360
underpredict the observations of u, and thus, U .361
4.2.3. Case 3362
Here, a low-level jet (LLJ) is clearly observed (Fig. 8). The observed363
U at 10 m is not very high (6.33 m s−1), but it reaches 20.11 m s−1 at364
400 m, which is the wind speed maximum, and that height is similar365
to the simulated zi (351 m). The simulated geostrophic wind angle is366
58◦ at 485 m and the observed wind veers 11◦ and 61◦ at 100 and367
500 m, respectively. The wind is highly ageostrophic (the observed368
wind around the wind maximum is much higher than the geostrophic369
wind), as expected. Baroclinity has a high impact on the observa-370
tions and simulated geostrophic wind (on the latter already below371
the simulated zi). The observed 10-m wind direction is 107◦ so that372
the high baroclinity component in u is due to positive temperature373
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The Høvsøre tall wind profile experiment 15
U250
G191
G14
U10
W E
S
N
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 7. Similar to Fig. 6 but for case 2
difference northwards. At about 1200 m the observed winds approach374
the simulated geostrophic values.375
The observed atmospheric conditions close to the surface are stable376
and L is nearly the same at all sonic levels. The observed friction veloc-377
ity at 10 m is 0.38 m s−1 and decreases slightly with height (Table IV).378
Although the simulated winds behave similarly compared to the ob-379
served u and v components, the strength of the LLJ is underestimated380
as found by Floors et al. (2013).381
4.2.4. Case 4382
The conditions as seen by the simulations are nearly barotropic and383
the strength of the forcing is very high (UG = 21.42 m s−1 at the first384
model level). The simulated zi (763 m) corresponds well with the height385
where the observed U shows its maximum (Fig. 9). The observed U is386
high at all levels: 11.75 and 21.18 m s−1 at 100 and 600 m, respectively.387
Close to the simulated zi (at 705 m), the simulated geostrophic wind388
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16 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
W E
S
NU10
G485
U500
G14
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 8. Similar to Fig. 6 but for case 3
angle is 45◦; the observed veering is 7◦ and 45◦ in the first 100 and389
700 m, respectively. The observed u and v components approach well390
the simulated geostrophic wind close to zi.391
Near the surface the observed atmospheric conditions are stable392
and remain nearly constant in the first 100 m. The observed friction393
velocity at 10 m is 0.45 m s−1 (the observed wind direction at 10 m394
is 84◦) and also remains constant within the sonics’ range (Table IV).395
The simulated winds are in good agreement with the observed U (v396
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.16
The Høvsøre tall wind profile experiment 17
N
E
S
WU10
G705
G14U700
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 9. Similar to Fig. 6 but for case 4
is slightly overpredicted) and the highest differences are found close to397
and above zi.398
4.2.5. Case 5399
Very high wind speeds are observed close to the surface (U = 10.04400
and 13.26 m s−1 at 10 and 100 m, respectively) and the conditions,401
as seen by the simulations, are nearly barotropic with high forcing402
(UG = 19.45 m s−1 at the first model level). The simulated zi (1120 m)403
matches well the height of the observed wind speed maximum (Fig. 10).404
The simulated geostrophic wind angle is 28◦ at 1263 m and the observed405
wind veers 4◦ and 25◦ at 100 and 1200 m, respectively (the observed406
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.17
18Alfre
doPena,RogierFloors
andSven-E
rikGryning
Table III. Observed mean horizontal wind-speed components (u, v) at different heights z. The simulated geostrophic wind com-ponents (uG, vG) are also given at different levels (between 10 and 950 m the closest model level output to an observed height isused). The results are provided for Cases 1–4, where the number in parenthesis indicates the number of 30-min averages used forthe ensemble mean and zi indicates the boundary-layer height from the model simulations
Case 1 (3): zi ≈ 87 m Case 2 (3): zi ≈ 169 m Case 3 (7): zi ≈ 351 m Case 4 (23): zi ≈ 763 m
z u v uG vG u v uG vG u v uG vG u v uG vG
[m] [m s−1] [m s−1] [m s−1] [m s−1]
10 3.01 0.00 4.96 4.76 5.10 0.00 9.39 5.07 6.33 0.00 9.42 11.16 7.31 0.00 15.05 15.09
40 4.33 1.30 5.00 4.73 6.06 0.26 9.36 5.07 8.00 0.52 9.35 11.15 8.96 0.33 15.05 15.06
100 4.92 4.67 5.11 4.67 7.82 1.08 9.24 5.06 10.59 2.14 9.12 11.10 11.65 1.51 15.03 14.99
150 3.69 6.56 5.14 4.65 9.20 2.48 9.20 5.03 13.20 4.16 8.97 11.07 13.75 3.07 15.01 14.96
200 2.88 6.34 5.15 4.63 9.87 3.97 9.14 4.94 14.51 5.67 8.57 10.90 15.03 4.15 14.98 14.92
250 2.51 5.37 - - 9.98 4.91 - - 15.29 7.70 - - 15.86 5.47 - -
300 3.02 5.58 5.09 4.52 10.79 5.30 8.99 4.84 15.81 10.27 7.66 10.54 16.66 6.72 14.89 14.86
350 2.96 5.29 - - 11.51 5.67 - - 14.86 13.21 - - 17.02 7.99 - -
400 2.77 4.96 - - 11.66 5.46 - - 12.70 15.52 - - 17.12 9.19 - -
450 2.69 4.66 - - 11.53 4.97 - - 10.41 16.31 - - 17.10 10.37 - -
500 2.80 4.40 5.00 4.27 11.27 4.45 8.52 4.75 8.76 16.10 6.37 10.12 17.03 11.49 14.78 14.85
550 3.05 4.19 - - 10.96 4.09 - - 7.44 15.78 - - 16.78 12.60 - -
600 3.32 4.05 - - 10.49 4.01 - - 6.29 15.42 - - 16.20 13.66 - -
650 3.63 4.02 - - 10.30 4.15 - - 5.03 15.00 - - 15.61 14.66 - -
700 3.78 4.15 4.96 3.88 10.04 4.12 7.49 4.73 3.97 14.57 4.92 9.64 15.17 15.32 14.70 14.92
750 3.85 4.29 - - 9.69 3.87 - - 3.23 14.20 - - 14.73 15.81 - -
800 3.91 4.43 - - 9.23 3.56 - - 2.67 13.83 - - 14.33 16.15 - -
850 3.95 4.60 - - 8.78 3.20 - - 2.21 13.32 - - 14.04 16.37 - -
900 3.99 4.83 - - 8.44 2.90 - - 1.80 12.67 - - 13.89 16.50 - -
950 4.06 4.98 4.94 3.50 8.16 2.74 5.81 4.89 1.54 12.03 3.34 9.20 13.78 16.56 14.63 15.04
1000 4.07 5.14 - - 7.82 2.66 - - 1.45 11.48 - - 13.68 16.53 - -
1050 4.12 5.26 - - 7.28 2.56 - - 1.47 11.03 - - 13.65 16.48 - -
1100 4.25 5.44 - - 6.74 2.35 - - 1.58 10.67 - - 13.37 16.20 - -
1150 4.27 5.53 - - 6.12 2.19 - - 1.78 10.28 - - 12.91 15.80 - -
1200 4.25 5.54 - - 5.40 2.10 - - 1.91 9.91 - - 12.69 15.61 - -
1263 - - 4.78 3.18 - - 3.74 5.14 - - 1.68 8.90 - - 14.47 15.07
Hovsore_tall_wind_profile.tex;
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The Høvsøre tall wind profile experiment 19
Table IV. Observed mean friction velocity u∗ and dimensionless stability param-eter z/L at different heights z. The results are provided for Cases 1–4
Case 1 Case 2 Case 3 Case 4
z u∗ z/L u∗ z/L u∗ z/L u∗ z/L
[m] [m s−1] [-] [m s−1] [-] [m s−1] [-] [m s−1] [-]
10 0.19 0.035 0.37 -0.003 0.38 0.077 0.45 0.045
40 0.15 0.946 0.34 0.058 0.37 0.216 0.45 0.184
100 0.08 1.870 0.40 0.263 0.35 0.673 0.50 0.386
wind direction at 10 m is 100◦). The observed wind-speed components407
approach well the simulated geostrophic values.408
The rather large error bars in Fig. 10 show the high wind variability409
observed during the afternoon hours of these three consecutive days.410
Within the first 100 m, the observed stability conditions are highly411
neutral (z/L values close to zero). The observed friction velocity at412
10 m is rather high (0.70 m s−1) and increases to 0.85 m s−1 at 100 m413
(Table VI). The observed U is well predicted by the log profile within414
the entire ABL. The simulated winds are in good agreement with the415
observed v component, slightly underestimating u.416
4.2.6. Case 6417
The simulations show an atmosphere that is nearly barotropic with very418
high forcing conditions (UG = 20.47 m s−1 at the first model level). The419
simulated zi is very high (1290 m) and although it is beyond the highest420
observed level, the observations of both u and v seem to approach the421
simulated geostrophic wind at zi (Fig. 11). The observed wind speeds422
are also very high: U is 14.94 and 16.54 m s−1 at 100 and 600 m,423
respectively. The observed wind direction at 10 m is 57◦. The observed424
wind veers very little: 4◦ and 14◦ at 100 and 1200 m, respectively, while425
the simulated geostrophic wind angle at 1263 m is 15◦.426
Close to the surface the observed conditions are slightly unstable427
becoming more neutral with height. The observed friction velocity at428
10 m is 0.62 m s−1 and increases with height (Table VI). The log profile429
predicts well the observed U values within the ABL. The simulated430
winds are in very good agreement with the observations, particularly431
for u. The simulated wind veering is however rather low in the first432
hundred of metres; it veers less than 1◦ at 101 m.433
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.19
20 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
N
E
S
W
U10
G14
G1263
U1200
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 10. Similar to Fig. 6 but for case 5
4.2.7. Case 7434
The simulations indicate that the atmosphere is baroclinic and in both435
observed u and v components, the flow decelerates approaching zi,436
which is simulated at 746 m (Fig. 12). The observed wind direction437
at 10 m is 41◦ and so the baroclinic components on u and v are mainly438
due to the warmer air south of Høvsøre (compared to that north of it).439
Both observed wind speed components, particularly u and therefore440
U , show a higher deceleration compared to the simulated geostrophic441
wind but approach well its value at zi. The observed wind speeds are442
high: U is 11.17 and 14.37 m s−1 at 100 and 600 m, respectively. The443
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.20
The Høvsøre tall wind profile experiment 21
G14
U1200
G1263
U10
W E
S
N
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 11. Similar to Fig. 6 but for case 6
observed wind veers 5◦ and 26◦ at 100 and 700 m, respectively, and the444
simulated geostrophic wind angle is 22◦ at 705 m.445
Within the first 100 m the observations indicate that the atmo-446
sphere is near-neutral with a nearly constant friction velocity of u∗ =447
0.56 m s−1 at 10 m (Table VI). The log profile agrees reasonable448
well with the observed U values, although it overpredicts slightly the449
wind speed. During summer and early autumn, the fields and crops at450
Høvsøre are close to be harvested and a zo value of 0.015 m is perhaps451
low (see also the slight overprediction of the log profile on cases 2 and452
5). The simulated winds agree well with the behaviour of the observed453
u component, but the wind veering is overpredicted in the first 250 m.454
4.2.8. Case 8455
The observed wind veers 4◦ within the first 150 m and then backs456
upwards; 17◦ at 900 m relative to the 10-m wind (Fig. 13). This is due457
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22 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
EW
U10G14
G705
U700
N
S
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 12. Similar to Fig. 6 but for case 7
to a high thermal-wind component, particularly observed in v, which458
notoriously decelerates and becomes negative at 350 m. The observed459
wind direction at 10 m is 41◦, thus such a high thermal wind comes460
from a colder north-east air over land compared to the warmer south-461
west air over sea. Close to the simulated zi (897 m), the observed u and462
v components approach the simulated geostrophic wind. The simulated463
geostrophic wind angle at 966 m is –20◦ (agreeing with the observed464
backing above).465
The observed conditions within the first 100 m are slightly stable466
and the observed friction velocity is rather constant u∗ = 0.38 m s−1467
(Table VI). The simulated wind-speed components show similar be-468
haviour compared to the observations, although u is underpredicted469
above 400 m, v is overpredicted (in magnitude) the first 400 m, and the470
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The Høvsøre tall wind profile experiment 23
U10
G14
U900
G966
W E
N
S
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 13. Similar to Fig. 6 but for case 8
simulated backing is underpredicted (the wind angle from the simulated471
winds is –7◦ at 966 m).472
4.2.9. Case 9473
The observed wind speeds do not change much with height within the474
first 1200 m: U is 4.91 and 4.98 m s−1 at 100 and 600 m, respectively475
(Fig. 14). There is a slight baroclinic component decelerating u close476
to zi, which is estimated at 1064 m by the simulations. The observed477
wind direction at 10 m is 91◦ and so this simulated eastward thermal478
wind is due to the higher air temperature southwards from Høvsøre.479
The simulated forcing is low: UG = 5.54 m s−1 at the first model level.480
The observed wind veers 2◦ and 14◦ at 100 and 600 m, respectively,481
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24Alfre
doPena,RogierFloors
andSven-E
rikGryning
Table V. Similar to Table III but for Cases 5–8
Case 5 (19): zi ≈ 1120 m Case 6 (30): zi ≈ 1290 m Case 7 (12): zi ≈ 746 m Case 8 (3): zi ≈ 897 m
z u v uG vG u v uG vG u v uG vG u v uG vG
[m] [m s−1] [m s−1] [m s−1] [m s−1]
10 10.04 0.00 16.92 9.32 11.13 0.00 19.82 4.74 7.95 0.00 13.46 6.37 5.87 0.00 13.85 -1.16
40 11.57 0.24 16.93 9.33 12.41 0.34 19.79 4.77 9.65 0.24 13.46 6.33 7.17 0.09 13.91 -1.26
100 13.23 0.98 16.96 9.36 13.90 1.04 19.69 4.84 11.13 1.01 13.45 6.23 8.57 0.65 14.06 -1.53
150 15.14 2.21 16.97 9.37 14.55 1.61 19.65 4.88 11.85 1.18 13.44 6.17 9.16 0.73 14.13 -1.67
200 15.72 2.36 17.01 9.38 14.93 1.69 19.55 4.95 12.34 1.47 13.42 6.06 9.68 0.72 14.27 -1.96
250 15.92 2.62 - - 15.13 1.71 - - 12.73 1.80 - - 10.00 0.56 - -
300 16.48 2.76 17.09 9.41 15.35 1.78 19.37 5.10 13.06 2.15 13.36 5.83 10.49 0.31 14.53 -2.54
350 16.74 2.95 - - 15.60 1.90 - - 13.29 2.59 - - 10.78 -0.09 - -
400 16.92 3.08 - - 15.78 1.94 - - 13.42 3.10 - - 11.11 -0.63 - -
450 17.11 3.25 - - 15.98 1.99 - - 13.48 3.71 - - 11.54 -1.11 - -
500 17.28 3.50 17.23 9.43 16.11 2.08 19.17 5.29 13.42 4.32 13.25 5.51 11.98 -1.54 14.87 -3.36
550 17.42 3.75 - - 16.25 2.13 - - 13.38 4.84 - - 12.37 -2.00 - -
600 17.50 3.97 - - 16.37 2.24 - - 13.29 5.47 - - 12.69 -2.35 - -
650 17.56 4.18 - - 16.50 2.36 - - 12.89 6.18 - - 12.95 -2.65 - -
700 17.69 4.45 17.41 9.42 16.68 2.52 19.19 5.45 13.40 6.54 12.86 5.08 13.16 -2.89 15.23 -4.37
750 17.82 4.76 - - 16.89 2.70 - - 12.50 6.36 - - 13.32 -3.11 - -
800 17.97 5.13 - - 17.02 2.89 - - 10.13 4.24 - - 13.58 -3.39 - -
850 18.13 5.47 - - 17.21 3.12 - - 11.25 5.56 - - 13.52 -3.50 - -
900 18.28 5.87 - - 17.40 3.40 - - 10.43 5.49 - - 13.53 -3.69 - -
950 18.40 6.29 17.51 9.35 17.57 3.65 19.50 5.42 10.00 4.98 11.92 4.33 13.26 -4.04 15.45 -5.59
1000 18.50 6.67 - - 17.75 3.80 - - 9.57 5.04 - - 13.38 -5.19 - -
1050 18.32 7.13 - - 17.91 3.89 - - 9.20 5.06 - - 13.47 -4.87 - -
1100 17.91 7.27 - - 18.02 4.01 - - 8.60 4.27 - - 13.30 -5.74 - -
1150 17.81 7.83 - - 18.11 4.21 - - 8.37 2.72 - - 15.47 -3.79 - -
1200 17.81 8.20 - - 18.13 4.38 - - 6.97 1.69 - - 12.29 -5.96 - -
1263 - - 17.27 9.17 - - 19.64 5.13 - - 10.97 3.30 - - 15.20 -6.91
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The Høvsøre tall wind profile experiment 25
Table VI. Similar to Table IV but for Cases 5–8
Case 5 Case 6 Case 7 Case 8
z u∗ z/L u∗ z/L u∗ z/L u∗ z/L
[m] [m s−1] [-] [m s−1] [-] [m s−1] [-] [m s−1] [-]
10 0.70 -0.005 0.62 -0.021 0.56 0.008 0.38 0.027
40 0.67 -0.012 0.77 -0.020 0.54 0.030 0.40 -0.012
100 0.85 0.006 0.79 -0.032 0.58 0.009 0.38 0.170
only. The observed u and U approach the simulated geostrophic value482
at zi. At 966 m the simulated geostrophic wind angle is –5◦, whereas483
the observations show an angle of 12◦ at 950 m (there is nearly no484
geostrophic wind turning from the simulations).485
G966
U10
U950
G14S
N
EW
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 14. Similar to Fig. 6 but for case 9
Close to the surface the observed conditions are very unstable and486
as the atmosphere is nearly barotropic, the observed wind turning487
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26 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
is small, as expected. The observed friction velocity at 10 m is low488
(u∗ = 0.26 m s−1) and increases with height (Table VIII). The sim-489
ulated winds are in good agreement with the observations and it is490
noticed that they clearly depart from the simulated geostrophic wind,491
as the observations, for the v component and, thus, they also show wind492
veering.493
4.2.10. Case 10494
The highly baroclinic atmosphere clearly influences both u and v (Fig. 15).495
Both observed u and v approach well the simulated geostrophic wind496
close to zi, which is simulated at 971 m. At about 250 m the observed497
U value clearly overtakes the simulated gradient wind and continues498
accelerating with the simulated geostrophic wind. The observed wind499
only veers in the first 100 m and then slowly backs upwards. The500
observed wind angle is –8◦ at 1000 m and the simulated geostrophic501
wind angle is –7◦ at 966 m. The observed wind direction at 10 m is 37◦;502
thus the thermal wind is due to the a large positive air temperature503
gradient eastwards.504
Within the first 100 m, the observed stability conditions are stable.505
The observed friction velocity is rather low and constant with height506
(u∗ = 0.26 m s−1 at 10 m) (Table VIII). The behaviour of the simulated507
winds agree reasonable well with the observations, underestimating u508
after the baroclinic component accelerates the flow. v is simulated to509
point south-easterly all the way the ABL, whereas the observed v points510
north-westerly up to 600 m where it turns south-westerly upwards.511
5. Summary and conclusions512
Accurate observations of the two horizontal wind speed components513
in the entire ABL were performed over flat terrain with nearly ho-514
mogeneous upstream flow under different surface stability and forcing515
conditions. The measurements were carried out combining a long-range516
wind lidar with sonic anemometers. Simulations using the WRF model517
are used to infer the forcing conditions (surface geostrophic, gradient,518
and thermal winds) and to help categorizing the observations. Wind519
outputs from the simulations are also compared to the measurements.520
In the ten different cases here shown, the observed surface winds be-521
have in correspondence to the surface atmospheric stability conditions;522
the vertical wind shear and turning of the wind are higher in stable com-523
pared to unstable conditions. Close to the simulated boundary-layer524
height, the observed wind components approach well the simulated525
geostrophic winds under both barotropic and baroclinic conditions,526
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.26
The Høvsøre tall wind profile experiment 27
Table VII. Similar to Table III but for Cases 9 and 10
Case 9 (6): zi ≈ 1064 m Case 10 (3): zi ≈ 971 m
z u v uG vG u v uG vG
[m] [m s−1] [m s−1]
10 4.36 0.00 5.40 -0.30 5.19 0.00 11.72 1.44
40 4.63 0.00 5.36 -0.30 6.74 0.10 11.84 1.36
100 4.91 0.14 5.23 -0.30 8.48 0.75 12.18 1.15
150 5.12 0.46 5.16 -0.30 9.46 0.49 12.34 1.05
200 5.16 0.66 5.00 -0.30 10.45 0.43 12.67 0.84
250 5.05 0.80 - - 10.76 0.72 - -
300 5.15 0.92 4.71 -0.30 12.04 0.43 13.30 0.43
350 5.14 0.98 - - 12.48 0.32 - -
400 5.09 1.03 - - 12.84 0.34 - -
450 5.00 1.17 - - 13.15 0.30 - -
500 5.00 1.23 4.30 -0.30 13.44 0.26 14.18 -0.17
550 4.92 1.23 - - 13.70 0.26 - -
600 4.82 1.24 - - 13.95 0.15 - -
650 4.85 1.29 - - 14.33 -0.53 - -
700 4.88 1.30 4.06 -0.33 14.49 -0.74 15.18 -0.97
750 4.92 1.26 - - 14.54 -1.02 - -
800 4.95 1.19 - - 14.67 -1.36 - -
850 4.97 1.12 - - 14.74 -1.59 - -
900 5.01 1.05 - - 14.75 -1.88 - -
950 5.06 1.07 4.23 -0.38 14.75 -2.04 16.01 -2.07
1000 5.03 1.17 - - 14.63 -1.96 - -
1050 4.94 1.32 - - 14.68 -2.15 - -
1100 4.91 1.41 - - 14.65 -2.18 - -
1150 4.79 1.30 - - 14.63 -2.15 - -
1200 4.90 1.41 - - 14.59 -2.00 - -
1263 - - 4.58 -0.16 - - 16.60 -3.39
Table VIII. Similar to Table IV but forCases 9 and 10
Case 9 Case 10
z u∗ z/L u∗ z/L
[m] [m s−1] [-] [m s−1] [-]
10 0.26 -0.401 0.26 0.141
40 0.24 -1.148 0.29 0.155
100 0.37 -0.802 0.28 0.491
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.27
28 Alfredo Pena, Rogier Floors and Sven-Erik Gryning
G966
G14
U1000
U10
W
N
S
E
10
20
40
100
200
400
800
1200
0 5 10 15 20
height[m
]
u [m s−1]
10
20
40
100
200
400
800
1200
−5 0 5 10 15
v [m s−1]
10
20
40
100
200
400
800
1200
0 5 10 15 20
U [m s−1]
Figure 15. Similar to Fig. 6 but for case 10
except for a LLJ case, where the wind speed maximum is located527
close to the boundary-layer height (the approach to geostrophic speeds528
occurs much higher in this particular case). Forcing conditions from529
the simulations are therefore useful to understand the wind behaviour530
high above the surface layer.531
Also for all cases and at a height close to the simulated boundary-532
layer height, both simulated geostrophic wind and observed wind angles533
are in very good agreement under both backing and veering conditions.534
This improves the confidence in the simulated forcing and boundary-535
layer height. The simulated horizontal wind speed magnitude agrees536
Hovsore_tall_wind_profile.tex; 30/07/2013; 13:18; p.28
The Høvsøre tall wind profile experiment 29
reasonable well with the observations, although the simulations gen-537
erally underpredict the turning of the wind, and in the LLJ case, the538
strength of the wind.539
Acknowledgements540
Funding from the Danish Council for Strategic Research Project Num-541
ber 2104-08-0025 “Tall Wind” project is acknowledged. We would also542
like to thank the Test and Measurements section of DTU Wind Energy543
for the maintenance of the Høvsøre database.544
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