ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-16-8009-2016A study of local turbulence and anisotropy during the afternoon and evening transition
with an unmanned aerial system and mesoscale simulationLampertAstridastrid.lampert@tu-braunschweig.dePätzoldFalkJiménezMaria Antoniahttps://orcid.org/0000-0002-8411-5512LobitzLennartMartinSabrinaLohmannGeraldhttps://orcid.org/0000-0001-9971-6268CanutGuylaineLegainDominiqueBangeJenshttps://orcid.org/0000-0003-4075-1573Martínez-VillagrasaDaniCuxartJoanInstitute of Flight Guidance, TU Braunschweig, Braunschweig,
GermanyUniversitat de les Illes Balears, Palma de Mallorca,
SpainClimatology and Environmental Meteorology, Institute of
Geoecology, TU Braunschweig, Braunschweig, GermanyEnergy
Meteorology Group, Institute of Physics, Oldenburg University, Oldenburg,
GermanyCNRM-GAME, UMR3589, Météo-France and CNRS,
Toulouse, FranceEberhard Karls University Tübingen,
Tübingen, GermanyAstrid Lampert (astrid.lampert@tu-braunschweig.de)1July20161612800980219January201629January20162June20168June2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/16/8009/2016/acp-16-8009-2016.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/16/8009/2016/acp-16-8009-2016.pdf
Observations of turbulence are analysed for the afternoon and evening
transition (AET) during the Boundary-Layer Late Afternoon and Sunset
Turbulence (BLLAST) experimental field campaign that took place in Lannemezan
(foothills of the Pyrenees) in summer 2011. The case of 2 July is further
studied because the turbulence properties of the lower atmosphere (up to
300 m above ground level) were sampled with the Meteorological Mini Aerial
Vehicle (M2AV) from turbulently mixed to stably stratified atmospheric
conditions. Additionally, data from radiosoundings, 60 m tower and UHF wind
profiler were taken together with the model results from a high-resolution
mesoscale simulation of this case. Weak large-scale winds and clear-sky
conditions were present on the studied AET case favouring the development of
slope winds and mountain–plain circulations. It is found that during the AET
the anisotropy of the turbulent eddies increases as the vertical motions are
damped due to the stably stratified conditions. This effect is enhanced by
the formation of a low-level jet after sunset. Finally, the comparison of the
anisotropy ratio computed from the different sources of observations allow us
to determine the most relevant scales of the motion during the AET in such a
complex terrain region.
Introduction
The afternoon–evening transition (AET) of the atmospheric boundary layer
(ABL) involves the processes of converting a convective ABL into a
stably stratified nocturnal ABL. The afternoon transition (AT) and evening
transition (ET) are defined differently in the literature, depending on, e.g.
the observational techniques and available data sets. Some definitions are
based on the surface heat flux evolution , as in , who apply the definition by
to the BLLAST (Boundary-Layer
Late Afternoon and Sunset Turbulence) campaign. The AT begins when the surface heat flux starts to
decrease, and afterwards the ET occurs when the surface sensible heat flux
becomes negative (close to sunset), with the formation of a temperature
inversion above the Earth's surface. This process finishes when a
stably stratified boundary layer is well established.
The AET usually includes several consecutive changes of near-surface
parameters that have also been used for alternative definitions: a decrease
in wind speed and temperature is typical, sometimes with a
significant change of the wind direction , while the mixing
ratio within the ABL rapidly increases . Besides, the
generation of a temperature inversion is responsible for a general drop in
horizontal and vertical wind variances and thermal
fluctuations. Consequently, the decay of the turbulence kinetic energy (TKE)
occurs in two stages : a slow decay of TKE during the AT
followed by a rapid collapse during the ET. The last stage of this evolution
is often complemented with a change in turbulence characteristics like its
spectral shape or anisotropy . Under unstable
stratification and low wind speed conditions, turbulence is mainly generated
by convection, and the variance in the vertical is similar to the one in the
horizontal wind components, leading to isotropic turbulence and large values
of TKE. Along the AET, turbulence anisotropy may arise from the effect of the
thermal stratification that inhibits the extent of the vertical motions.
During the AET, spatial inhomogeneities are created, which influence the
development of the ABL through the night .
Over complex terrain, temperature gradients at local scales
or larger-scale structures normally
associated with topography are responsible for the generation of a
low-level jet (LLJ), first described in . This feature
is described as a local maximum of wind speed
with values 2 m s-1 larger than at lower and higher levels
alternatively, an LLJ is also considered if the wind decreases above
and below at least 25 % of the maximum, as in . LLJs are
frequently reported over land , initiated during the AET
and reach near-steady-state conditions at night, when the ABL decouples
from the ground as the surface temperature cools down and a temperature
inversion layer is formed. Some climatologies report LLJ occurrence between
30 and 60 % of all nights , with the exact percentage depending on the local features and
ambient conditions. When an LLJ is present, the wind shear between the
surface and the wind maximum is enhanced and the corresponding turbulent
mixing decreases the intensity
of the surface temperature inversion. Besides, the wind shear associated to
the LLJ favours the elongation of the eddies along the main wind direction
, leading to larger values of anisotropy
compared to areas where the LLJ is weaker or non-existent.
The aim of this work is twofold: firstly, to evaluate the changes in the
turbulence characteristics during the AET for the lower ABL, with special
regard to the isotropy of turbulent eddies, and secondly, to study the
influence of a nocturnal LLJ on these turbulence properties. A case from the
BLLAST experimental field campaign is taken where
clear-sky and weak pressure gradient conditions were present to favour the
formation of a mountain–plain circulation, as previously reported in
. An LLJ was generated during that ET, when turbulent
measurements in the lower ABL were taken by the Meteorological Mini Aerial
Vehicle (M2AV). The analysis is complemented by other sources of
observations (standard and frequent radiosoundings, UHF and 60 m tower) and
a high-resolution mesoscale simulation with the MesoNH model
. A detailed analysis of the increase in anisotropy during
the AET for all the IOPs during BLLAST is reported in , but
here the case of 2 July 2011 is further studied with the help of M2AV
observations and mesoscale modelling. The manuscript is organized as follows.
Section 2 is devoted to the observations and model set-up. The organization of
the flow at lower levels and a description of the turbulent motions, as
described in Sects. 3 and 4, evaluates the measured and modelled anisotropy
ratio. Finally, discussion of the results and conclusions are shown in
Sects. 5 and 6 respectively.
Throughout the article, times are given in UTC, as the study area has
approximately the same longitude as Greenwich and therefore the same solar
time. The official local time is UTC + 2 h.
Field site, instrumentation and model set-up
(a) Topography of the inner domain of the mesoscale
simulation which covers the Pyrenees (mountains and foothills). The plateau
where Lannemezan is placed is coloured in green and the Aure valley is at the
south. Topography lines are labelled at 200, 400, 1000 and 2000 m (above sea
level, a.s.l.). (b) Zoom of (a) over the plateau where
Lannemezan is placed together with the M2AV flight tracks (black lines).
The location of Site 1 (60 m tower, UHF radar and GRAW soundings) and Site 2
(frequent radiosoundings, MODEM) are indicated with an asterisk and a dot
respectively.
The BLLAST experimental field campaign, conducted in summer 2011 in southern
France (Fig. a), was dedicated to study the physical processes that
take place in the AT . Measurements were taken at three
different sites spanning a triangle with sides about 3–4 km long, close to
Lannemezan, over a plateau at 600 m above sea level (a.s.l.) approximately
20 km north of the Pyrenees mountain range. The experimental area was
located following the exit of the Aure valley. The Aure valley is a narrow
valley, 30 km long, with the main axis oriented approximately in the
north–south direction. Data used here are from the main site (Site 1,
asterisk in Fig. b) and Site 2 (dot in Fig. b), both
equipped with various in situ and remote sensing instruments, the main
features of which are described below:
Standard GRAW and MODEM radiosondes were launched from Site 1 at least
four times per day at 05:00, 11:00, 17:00 and 23:00 UTC during the intensive
operation period (IOP) days. Additional radiosondes were launched at 2030 UTC
on 2 July and at 02:00 on 3 July 2011. At Site 2, frequent
Väisälä radiosoundings were performed every
hour from 13:00 to 20:00 UTC. Therefore, differences between simultaneous
soundings can be attributed to different launching locations and measurement
techniques.
An ultra-high-frequency (UHF) radar was installed at Site 1 for
continuous monitoring of the atmosphere from 200 to 3000 m above ground
level (a.g.l.). The UHF data have a vertical resolution of 75 m and were
averaged over 30 min. Wind and potential temperature reported from the UHF
are used in this work.
A 60 m tower from Centre de Recherches Atmosphériques is
permanently installed at Site 1, providing year-round turbulent measurements
at 30, 45 and 60 m a.g.l. Other low-frequency sensors were also installed
but they are not used in the current analysis.
The Meteorological Mini Aerial Vehicle M2AV
Several unmanned aerial vehicles were operated within a radius of 2 km
around Site 1 during the BLLAST campaign. This was particularly the case for the
M2AV as well, which took four distinct flights during the AET on 2
July 2011. The M2AV is an unmanned aerial vehicle with a wing span of 2 m
and a weight of 6 kg. It is started and landed manually and can be fully
controlled during the mission by an autopilot system. For this case study,
most ascents and descents as well as the main flight, consisting of a race
track pattern with straight horizontal legs, were flown with the autopilot.
The flight track is shown in Fig. b.
The M2AV is equipped with a miniaturized turbulence measurement payload
comprising a 5-hole probe for deriving the angle of attack and sideslip in
the aerodynamic coordinate system. The data can then be converted to the 3-D
wind vector in the geodetic coordinate system using precise information on
position and attitude of the aircraft obtained by GPS and an inertial
measurement unit (IMU). The application of the method for unmanned aircraft
is demonstrated by . Further, the payload includes
both a slow but accurate (Pt1000) and a fast temperature sensor, as well as a
capacitive humidity sensor . The static air temperature was
derived from the Pt1000 thermometer, measuring the stagnation point
temperature by correcting the time lag effect and the total temperature
effect as described in using individual coefficients for
the M2AV. The dry potential temperature was then calculated according to
.
The parameters measured by the M2AV (profiles of temperature, humidity,
wind speed and wind direction, as well as TKE and turbulent fluxes of
sensible heat) have been validated extensively against other airborne
measurements , as well as in situ measurements from a
meteorological tower and remote sensing observations . The system has been deployed for high-resolution atmospheric
profiling and for deriving turbulent
parameters worldwide at
various locations.
Takeoff and landing time for each flight of the M2AV on 2 July
2011.
For the present analysis, the M2AV performed four distinct flights
starting around 14:30, 16:30, 18:30 and 20:30 UTC. Flights lasted
approximately 40 min except Flight 2, which was shorter due to a failure of
the autopilot around 20 min after take off. The exact times for take off and
landing are given in Table . Each flight combined vertical
profiles followed by horizontal race track patterns of about 1 km length
oriented in the east–west direction for deriving turbulent parameters. The
profiles were performed with an ascent (descent) rate of about 3.5
(8.0) m s-1. The profiles of wind speed were averaged over intervals
of 10 m altitude for an individual ascent or descent, while wind direction
was additionally smoothed using a linear interpolation function. The race
track pattern consisted of three legs at 300 and 250 m a.g.l. and two more
legs at 200 m a.g.l. The same pattern was repeated three times for each
flight. During the last flight, these altitudes were reduced by 50 m,
corresponding to a lower observed ABL height. Note that the time for one
flight leg is only about 45 s at the aircraft speed of 22 m s-1,
therefore providing an instantaneous snapshot of the turbulence properties.
Data from the horizontal legs of the race track pattern are used to calculate
the turbulent properties at different heights of the lower ABL. Several legs
provided time series of the fluctuation part of the wind components with a
quasi-steady wave-like structure (wavelength around 2 km) of relatively
large amplitude compared to the fast fluctuations. This structure had a high
impact on the wind variances calculated with a linear detrending. Since the
flight legs were not long enough for obtaining statistically relevant
information about these longwave features, we decided to remove their impact
by employing a high-pass Butterworth filter of third order. After testing
different cut-off frequencies, the variances were calculated using the
high-pass filter with a frequency of 0.01 Hz.
The dynamic behaviour of the pressure sensors can be different depending on
their orientation with respect to the aircraft track, providing discrepancies
between the variances estimated for the wind components parallel and
perpendicular to the race track. If isotropy is assumed in the horizontal
plane, the wind variance parallel to the race track σu2 can
be replaced by σv2, according to the meteorological
coordinate system. This is not in agreement with the results of
but is a common approach for airborne data obtained at a
high air speed compared to wind speed
. A convective ABL generates
isotropic turbulence, while in a sheared ABL, the eddies are elongated
following the direction of the main wind, as described in ,
and therefore they lose isotropy. However, in this case the eddy sizes in the
transversal direction have scales of the order of 1 km
, which is comparable to the leg length of the M2AV,
thus we may assume that horizontal isotropy applies for the sampled scales.
In addition, as the prevailing wind direction was from the north during the day,
the horizontal wind component v corresponds to the along-wind data, which
has a higher coherence than the crosswind component, e.g. according to
.
Assuming horizontal isotropy (σu2=σv2),
TKE is calculated for each flight leg as TKE=12(σu2+σv2+σw2)=σv2+12σw2.
For investigating the turbulence anisotropy, the anisotropy ratio is defined in
this study as the ratio of horizontal-to-vertical wind variances
.
A=σu2+σv22σw2=σv2σw2.
where σu2=σv2 is also assumed
when calculating this parameter with airborne data.
Equation () implies that isotropic turbulence is
characterized with A=1; that values lower than 1 correspond to daytime
convection with a large vertical turbulence component; values exceeding 1 are
caused by a dominating turbulence component in the horizontal direction
induced by wind shear or by a decrease of the vertical variance under
stably stratified conditions. Despite the fact that here we use a different
definition of the anisotropy ratio compared to other studies e.g., all of them can be easily related.
Model set-up
The mesoscale model MesoNH was run in a similar manner to previous studies, particularly in the Garonne river basin seeand
the references therein. Two nested domains were used. The outer
one, at 2 km × 2 km resolution (domain size of
50 km × 480 km), covered the Garonne river and the inner one, at
400 m × 400 m resolution (domain size of
80 km × 120 km), was centred in Lannemezan (see
Fig. a). The vertical resolution is fine close to the surface
(3 m) to properly represent the physical processes that take place at
lower levels, and coarser above the surface. The initial and lateral boundary conditions
are taken from the European Centre for Medium-Range Weather Forecasts (ECMWF)
every 6 h.
For the case study, the simulation start time was set to 00:00 UTC on
29 June 2011 so that rain observed during 30 June could be included, with the
aim that soil moisture in the model would be more similar to the
observations. The simulation end time was set to 12:00 UTC on 3 July 2011.
For the case study, attention is focused on describing the AET of 2 July 2011
(from 15:00 to 00:00 UTC).
Flow at lower levels during the AET
Modelled 100 m a.g.l. wind vectors together with wind speed (in
colours) and the topography lines (in blue) at different instants
(a) 15:00, (b) 20:30, (c) 21:30,
(d) 00:00 UTC. The 60 m wind vector observed by the tower is
indicated with a red arrow.
The synoptic conditions during 2 July 2011 include a weak anticyclone
(1025 hPa) over Britain and Ireland, with lower values of the pressure field
at the mean sea level on the western Mediterranean (1012 hPa), resulting in a
weak north-easterly to east-north-easterly flow over southern France at low
levels. This synoptic-scale flow coexisted with the mountain–plain system
that generated northerly flows in the daytime over the foothills of the
Pyrenees (Fig. a). Additionally, the Aure valley, just south of
Lannemezan, had a well developed up-valley wind system. At 20:30 UTC, the
wind in the plain blew from east-north-east (also over Lannemezan,
Fig. b), whereas the mountain valleys were generating down-valley
flows that still did not reach the foothills where Lannemezan is located.
Just 1 h later (Fig. c), the site was located in an area where
the mountain-to-plain wind merged with the more general easterly wind,
resulting in a local wind maximum over Lannemezan (an LLJ, as it will be
described later), a structure that still stayed there and was even reinforced at
00:00 UTC (Fig. d). The model reproduces the observed
intensity and direction of the wind in Lannemezan (red arrow in
Fig. ) very well for all the inspected instants.
Modelled and observed time series for (a) wind speed (in
m s-1), (b) wind direction (in ∘),
(c) temperature (in ∘C) and (d) TKE (in
m2 s-2) from 14:00 UTC until midnight on 2 July 2011. Tower
observations are in green circles, model results in red lines and M2AV
data in blue asterisks. The temporal evolution of wind and temperature data
from M2AV is constructed with the values of the vertical profiles taken at
the corresponding height of the tower measurements. For TKE, all the M2AV
legs where TKE is derived, at 150, 200, 250 and 300 m a.g.l., are included
in the plot. The time of sunset is represented by a black vertical line.
Looking at the temporal series in Fig. from M2AV, 60 m tower
and mesoscale simulation, the wind speed at 60 m a.g.l. decreases during
the AET (with a higher rate for airborne observations) and increases again
substantially after sunset, as wind turns from north to north-east direction,
a behaviour that the model and the M2AV observations successfully capture.
Besides, the three sources are reproducing a similar temporal evolution of
temperature, being the model 1 K warmer and 1 K colder than the
observations during day and night respectively. Although these biases are
not large, similar values are found for other studies and they can be
attributed to an enhanced mixing of the model at lower levels
or to a misrepresentation of the surface heterogeneities
.
To inspect the vertical characteristics of the LLJ, the profiles observed by
the UHF profiler and those extracted from the model outputs are shown as
Hövmoller plots (z,t) in Fig. . Besides, in Fig.
the observed vertical profiles (M2AV, UHF, soundings and 60 m tower) at
different instants are compared to those obtained from the model.
Temporal evolution of the vertical profiles for (a) UHF
wind direction (in ∘), (b) UHF wind speed (in m s-1),
(c) MesoNH wind direction (in colours) and wind speed (in lines, for
values ≥ 4 m s-1, contour interval = 2 m s-1) and
(d) MesoNH TKE (in m2 s-2). The time of sunset is
represented by a black vertical line.
It is found that the observed and modelled wind direction are in good
agreement with each other. Figure a shows that the UHF wind veers
from north-east to south-east between 20:00 and 21:00 UTC above
200 m a.g.l. and continues in that direction over the following hours. The
model has a similar behaviour at those heights (Fig. c) and
indicates that, at lower levels, the south-easterly flow arrives earlier
constricted to the first tens of metres AGL (as further confirmed with tower
observations, Fig. b). The TKE in the model decreases during the
AET with a minimum close to sunset at about 200 m a.g.l. and increases
again when the LLJ is present due to its shear. It must be mentioned here
that the values of the wind speed as provided by the UHF profiler are always
significantly overestimated with respect to the soundings (Fig. );
instead the wind directions derived from both soundings and wind profiler are
in very good agreement. Therefore, when making our assessment of other data
and of the model, we will not give too much weight to the values of the UHF
profiler for this particular case study. At 19:00 UTC, before sunset, the
thermal stratification is already stable at the site, with very weak winds
from the north-east quadrant (Fig. c). Profiles in Fig.
indicate that, at 20:00 UTC, already after sunset, there is a progressive
formation of a south-easterly jet below 100 m a.g.l., which is clearly
developed at 23:00 UTC, detected by the tower measurements below 60 m and,
according to the model, extending up to almost 300 m a.g.l. with wind speed
around 5 m s-1. The reported LLJ has similar features as those
described in .
Vertical profiles of the wind speed (in m s-1) on the left,
wind direction (in ∘) in the centre and potential temperature (in K)
on the right, obtained from M2AV (in violet) for the four flights of
2 July 2011: (a) 15:00, (b) 16:30, (c) 19:00 and
(d) 21:10 UTC. Purple dots correspond to mean values for each
horizontal leg. M2AV data are compared against instantaneous observations
from UHF (blue squares), 60 m tower (black dots), and frequent (red) and
standard soundings (black), together with mesoscale simulation results
(green). The legend indicates the corresponding times to each data source.
M2AV profiles (Fig. ) show a general good agreement with the
description just given using model and UHF profiler, indicating the increase
in wind speed after sunset and the change of the wind direction. The aeroplane
is also able to successfully capture the transition from thermally unstable
to stable conditions as shown in the potential temperature profiles
(Fig. ).
It seems therefore clear that the M2AV flight just after sunset was able
to capture the transition from a very weak wind regime to the establishment
of a terrain-induced LLJ that was sustained for several hours (the simulation
ends at 12:00 UTC of the next day). Since flight legs were made to estimate
turbulence intensities at heights that are probably located above and below
the LLJ wind maximum, it is possible that we can infer some characteristics
of the turbulence related to this structure using the last flight. Besides,
knowing that an LLJ was present in the area sustainedly after sunset provides
clues for the interpretation of the increase of anisotropy that will be
described in the next section.
During the last flight (about 21:00 UTC) ambient conditions were favourable
to develop gravity waves in the ABL, especially at lower levels. Results from
clearly show the presence of gravity waves close to the
surface up to about 100 m a.g.l. but not at higher levels (where the
M2AV sampled). The model results are not able to capture these waves since
they are too attached to the ground.
Turbulence and anisotropy during the AET
Vertical profiles of the simulated TKE (in lines) at different
instants during the M2AV flights (see legend). 60 m tower (in dots) and
M2AV (in asterisk) observations are also included. Note the logarithmic
scale on the x axis. For M2AV, σu2=σv2 is assumed.
Observations of the TKE (5 min averages from the tower and observations
obtained with the M2AV) and model results are similar during the AET, with
a sustained decrease in turbulence, and very small values at sunset
(Fig. d). Once the turbulence collapses around sunset the observed
values are very small in the whole column (tower and M2AV reported TKE of
around 0.05 m2 s-2, Fig. ). As seen in this figure, the
model produces even smaller TKE values throughout the vertical column, with a
local minimum between 75 and 125 m a.g.l. Simulated results are closer to
the observations at lower levels (as those observed by the 60 m tower) but
clearly underestimate the results provided by the M2AV at higher
elevations. Modelled LLJs usually underestimate the intensity of turbulent
mixing compared to observations . Nonetheless, in this
case, the local elevated turbulence usually associated to the LLJ wind
maximum seems to be reproduced by the mesoscale simulation, as shown by a
sustained TKE maximum near 400 m a.g.l. between sunset and 21:00 UTC
(yellow and red colour, Fig. d).
The anisotropy ratio for the afternoon and evening transition in this case
study can be computed from the numerical model, M2AV and the sonic
anemometers in the 60 m tower (Fig. ). Each source samples
different characteristic scales and therefore provides information about the
anisotropy at different ranges of the TKE spectrum.
Time series of the anisotropy computed from different sources:
(1) M2AV flight observations at 150, 200, 250 and 300 m a.g.l. during
the four flights, each symbol representing a particular height (in blue);
(2) tower measurements at 60 m a.g.l. every 5 min covering the
afternoon–evening transition (in green); (3) model results averaged between
150 and 300 m a.g.l. to be close to the altitudes of the M2AV
observations considering a spatial area of 10 km × 10 km centred
at Lannemezan (in red). The time of sunset is represented by a black
vertical line. Note the logarithmic scale on the y axis. For M2AV,
σu2=σv2 is assumed.
For the model, the columns of a box of 10 km side centred at Lannemezan are
extracted using the smallest domain that has a horizontal resolution of
400 m. The mean values of the horizontal and vertical wind speeds are
computed from the 25 × 25 columns, and the corresponding standard
deviations are computed to obtain the anisotropy ratio. This is the
anisotropy corresponding approximately to scales between 1 and 5 km as
created by the model. Afternoon values are slightly below 1, since in summer
prevailing dry-sheared convection typically has a turbulence spectrum with an
inertial subrange (IS) starting at scales close to 1 km. As sunset
approaches and convection weakens, anisotropy increases because the beginning
of the IS shifts to the right. After sunset, the eddies have relatively
shallow dimensions and are elongated along the main wind direction as
described in, showing large values of anisotropy at these
scales. Anisotropy in the model is at maximum close to the ground and decreases with height (not shown).
The same as Fig. but for the (a) horizontal
σu+σv and (b) vertical
2σw variances computed from the tower observations at
60 m a.g.l. during 1 July 2011 (IOP 9, without an LLJ, black line) and
2 July 2011 (IOP10, with an LLJ, green line), together with those derived
from M2AV observations. For M2AV data, σu2=σv2 is assumed.
The M2AV flew legs of 1 km length and resolves eddies down to sizes of
typically a few metres . In the daytime the range of
sampled eddies is almost all in the IS, and the anisotropy ratio has values
close to 1. As sunset approaches and at night, the size of the largest eddies
decreases and the aeroplane samples eddies larger than those in the IS,
generating larger values of the anisotropy ratio. Statistical values over
5 min from a sonic anemometer at 60 m a.g.l. are similar to those from the
M2AV (close to 10) in this case, typically representing scales of a few
hundred metres (assuming a mean wind speed of 5 m s-1) to dissipation.
In the daytime the values of anisotropy provided by the different sources are
very similar and close to 1, as expected with a dry-sheared convective
boundary layer (Fig. ). During the evening transition, the
anisotropy ratio is larger (by a factor of 2 to 5), likely because the
contribution of convection weakens significantly and the eddies become
progressively shallower and more elongated. At night the values of the
anisotropy ratio differ depending on the scale and source of the data. At the
height of the LLJ, the model produces the same values of anisotropy as during
the transition, not significantly influenced by the effects of thermal
stratification at those levels and the elongation of shear-driven eddies at
those scales. Instead, the M2AV and the tower, which measure at smaller
scales, provide much higher values of the anisotropy ratio, indicating that
thermal stratification and wind shear generated by the LLJ play a more
important role at these scales, moving the upper limit of the IS to very
small eddies.
Discussion
The TKE values observed with the M2AV are compatible with other TKE values
obtained on that particular day with ground-based, balloon and airborne
observations . The time evolution of the TKE studied in the
present case can be compared to the results obtained by ,
who analysed the turbulence decay between 12:00 and 20:00 UTC for a similar
day of the BLLAST campaign (20 June 2011, IOP 3) using observations and a
large eddy simulation (LES). Observed TKE during Flights 1 and 2 are of the
same magnitude than those values obtained in between
15:00 and 17:00 UTC (see their Fig. 7). Two hours later, Flight 3 exhibits
much lower values than in their study, suggesting that turbulence collapses
faster and deeper in our case. Interestingly, the TKE produced by the
numerical simulations is lower than the observations for both cases, despite
the differences in the study cases and the numerical tools used. After
sunset, Flight 4 observes a TKE increment with the arrival of the LLJ, with
values between 0.02 and 0.6 m2 s-2. In the summary of
, TKE values around 0.1 m2 s-2 are reported for
LLJs with a similar maximum wind speed around 5 m s-1, which is in the
same order of magnitude as the observations presented here. However, the
direct comparison of absolute TKE values with other values in the literature
is often difficult due to the non-unique definition of TKE and data
treatment, e.g. over what time the data were averaged, a high-pass filtering technique was applied or a linear trend
removal carried out for determining the wind speed variances cf..
The change of TKE with altitude does not provide a clear tendency
(Fig. ). According to , a decrease in TKE with
altitude is expected for an ABL where turbulence is created at the surface by
thermal heating and then transported upwards. In contrast, when turbulence is
induced by wind shear aloft, an increase in TKE with altitude is predicted using the theory by and produced by LES modelling
. In Fig. , a large scatter of TKE values can
be seen for M2AV. This indicates that the individual flight legs for
deriving turbulence properties were too short and the terrain was too
inhomogeneous to derive values which are statistically
representative of the area .
The evolution of turbulence anisotropy, with larger values of the vertical
wind variance during the afternoon and of the horizontal variances after
sunset, is in accordance with other observations during the BLLAST campaign
. Similarly, the numerical simulations of
give a sustained anisotropy ratio around 1 at z= 0.2 zi (zi is the
ABL height) until 17:30 UTC, and a rapid increment up to 2.5 after 1 h.
These results are in accordance with our observations from Flights 1, 2 and 3
of the M2AV, since the first two flights exhibit similar anisotropy
results while the third one doubles its value (Fig. ). In addition,
observations from Flight 4 suggest that the abrupt increment of the
anisotropy ratio during the late afternoon, when the surface buoyancy flux
reduces to zero , is enhanced after sunset.
In order to evaluate the impact of the LLJ on the turbulence anisotropy, this
parameter is evaluated during IOP 9 (1 July) with data from the 60 m tower
and compared against our case study (2 July 2011, IOP 10). Similarly to IOP
10, in IOP 9 large-scale winds were weak, allowing the development of a
mountain–plain circulation but without the arrival of an LLJ
. For both IOPs, the anisotropy ratio at 60 m a.g.l.
increases along the AET, but after sunset it becomes larger for IOP 10 (not
shown). Figure shows the temporal evolution of the horizontal and
vertical wind variances for both cases separately. The results from M2AV
are also depicted for reference. During the day, all variances have similar
values, remaining steady until 16:00 UTC and decreasing afterwards, as
sunset approaches. During this stage, the resulting anisotropy ratio is 1 for
both cases. Close to the sunset time, the vertical wind variance decreases at
a higher rate and thus the anisotropy ratio increases, as in
. After sunset, the drop in σw is
more significant for the IOP 10, coinciding with the arrival of an LLJ at the
area. These results are in agreement with previous observations from
and . The wind shear generated by the
presence of the LLJ and the stably stratified conditions at lower levels (at
60 m a.g.l., see Fig. ) might be responsible for the drop in
σw after sunrise, where the vertical motions are more damped
than if an LLJ is not present.
Conclusions
This work focuses on the time evolution of turbulence properties at the lower
ABL during the afternoon and evening transition (AET) for a case study of the
BLLAST experimental field campaign in southern France. The analysis has been
carried out through airborne, tower, radiosonde and remote sensing (UHF wind
profiler) observations. Besides, results from a high-resolution mesoscale
simulation have been used to both characterize the organization of the flow
at lower levels at the foothills of the Pyrenees (where the experimental
campaign was located), and to complement the observations.
It is found that TKE decreases along the AET and reaches a minimum close to
sunset, in agreement to other studied days of the BLLAST dataset. However,
for the present study, an LLJ develops over the area afterwards as a
combination of large-scale winds and the mountain–plain circulation generated
due to the vicinity of the Pyrenees. This major feature remains nearly
stationary during the whole night and is responsible for the increment of the
TKE close to the surface and at higher elevations above the wind speed
maximum after sunset. In addition to its intensity, the turbulence isotropy
has been analysed for the AET. During the day, a well-developed convective
boundary layer is characterized by isotropic turbulence (anisotropy ratio of
1), whereas after sunset, vertical motions are damped due to the establishment
of a stably stratified ABL and the wind shear generated by the LLJ. A
comparison with a similar day of the BLLAST campaign without the occurrence
of an LLJ confirms that the anisotropy ratio is enhanced due to its presence.
The increment of anisotropy is less pronounced in the mesoscale simulation,
probably due to the fact that the larger scales resolved by the model are
less affected by thermal stratification and wind shear.
The use of unmanned aerial vehicles for measuring turbulence properties has
experienced a large increase since the first reports of measuring the 3-D
wind at high resolution on such systems . Information
on turbulence properties is essential for many fields investigating
atmospheric processes, e.g. the formation of new small particles
, the dynamics of the morning transition
, and applications in wind energy .
The unmanned systems contribute valuable complementary information to other
remote sensing and in situ measurement systems. Their limitations in
horizontal and vertical operation range are balanced by the large flexibility
of using the systems (no need for a runway, only small crew necessary for the
operation). As was shown in this case study, the high-resolution measurements
provide additional information at variable altitudes, which enables a large
portfolio of applications in atmospheric research.
Data availability
Metadata and data from the BLLAST campaign are available after registration
at: http://bllast.sedoo.fr/.
Acknowledgements
The authors would like to thank Andreas Scholtz, Thomas Krüger and
Jürgen Heckmann for piloting the M2AV during the BLLAST campaign. The
BLLAST field experiment was made possible thanks to the contribution of
several institutions and supports: INSU-CNRS (Institut National des Sciences
de l'Univers, Centre national de la Recherche Scientifique, LEFE-IDAO
program), Météo-France, Observatoire Midi-Pyrénées
(University of Toulouse), EUFAR (EUropean Facility for Airborne Research) and
COST ES0802 (European Cooperation in the field of Scientific and Technical).
The field experiment would not have occurred without the contribution of all
participating European and American research groups, which all
contributed a significant amount (see supports). BLLAST field experiment
was hosted by the instrumented site of Centre de Recherches
Atmosphériques, Lannemezan, France (Observatoire Midi-Pyrénées,
Laboratoire d'Aérologie). The 60 m tower was partly supported by the
POCTEFA/FLUXPYR European program. BLLAST data are managed by SEDOO, from
Observatoire Midi-Pyrénées. The authors would like to thank Barbara
Altstädter for critically proofreading the manuscript. The authors from
Majorca acknowledge the support of the Spanish government and FEDER through
the research project CGL2015-65627-C3-1-R. The French ANR (Agence Nationale
de la Recherche) is supporting the analysis of the BLLAST dataset. Finally,
the authors would like to thank three anonymous referees, who encouraged us to
rewrite the manuscript completely, and Penny Rowe for proofreading the
English.Edited by: R. J. Beare
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