Three months of Doppler lidar wind measurements were obtained during
the Arctic Cloud Summer Experiment on the icebreaker
Profiles of wind speed and direction are one of the most fundamental
quantities for meteorological studies. Radio soundings are still the
primary source of global wind profiles
Over the ocean, remote sensing with a ship-based Doppler lidar
provides an attractive alternative to radio soundings for obtaining
profiles with a high time resolution
Here we present measurements with a motion-stabilised commercial scanning Doppler lidar. Lacking real-time control of the scanning head orientation, as used by Wolfe et al. (2007) and Pichugina et al. (2012), we mount the lidar as a whole in a motion-stabilised platform. The instrument was operated nearly continuously over a period of 3 months on a ship in the Arctic Ocean during the summer and autumn of 2014. The wind measurements are compared to 6-hourly radio soundings.
The measurements presented here are drawn from the Arctic Cloud Summer
Experiment (ACSE), part of the Swedish–Russian–US Arctic Ocean
Investigation on Climate–Cryosphere–Carbon Interactions (SWERUS-C3), which
undertook a 3-month-long cruise on the icebreaker
System parameters of the HALO Doppler lidar.
The lidar used here is a HALO Photonics Stream Line scanning
micro-pulsed Doppler lidar (
The lidar was stabilised against the pitch and roll of the ship by
mounting it within a specially constructed motion-stabilised frame
(Fig.
Approximately half of the ACSE cruise took place in sea ice where
the ship's pitch and roll are modest (typically less than
2
Cruise track of the legs from Tromsø to Barrow (red) and back (brown). Ice edges at the times of start and end of the cruise are shown in light and dark blue, respectively.
The residual attitude and three-dimensional velocity of the stabilised
inner frame were calculated and combined with the lidar beam
orientation to correct the line-of-sight Doppler velocity
measurement for the ship's velocity along the beam. The largest tilts were associated
with rotation of the lidar head prior to each new measurement. This changed the centre
of mass, inducing a small rotation before the motion-control and logging system detected and
compensated for this. In principle
the complete platform attitude and velocity solution could be
obtained directly from the internal solution of the Xsens AHRS; however, we had no
opportunity to calibrate the magnetic field sensors for the
hard-iron distortions induced by the ship, and the Xsens compass
heading thus suffered significant errors. We therefore utilised
a combination of the high-frequency attitude and motion calculated
from the raw Xsens AHRS measurements of accelerations (nominal accuracy:
Because the lidar Doppler velocities are 2
The signal-to-noise ratio (SNR) of the Doppler velocity measurement
depends on the set-up of the instrument and the availability of
aerosols and cloud droplets to reflect the laser beam and act as
tracers for atmospheric motion. It is used to separate reliable
data from signal noise
Wind speed and direction were obtained from the motion-corrected
HALO Doppler lidar measurements using the five-point
geometrical wind solution and the four-point sinusoidal fit method
both described in
We also investigated the influence of changes in the heading of the
ship during individual scan cycles with and without applying the
quality assurance criteria of
Doppler lidar evaluation: the sinusoidal fit solution is compared to
data from radiosondes launched every 6
Statistics of the comparison between lidar and radio sounding for
a height of 75
Continuous wind profiles could be retrieved up to a maximum
altitude of 1600
In order to assess the accuracy of the lidar wind retrievals,
results have been compared to the 6-hourly radio soundings. We used
Vaisala RS92 radiosondes with a nominal ascent rate of
4
Figure
Extreme outliers (red points in
Fig.
Linear fit parameters for both geometric and sinusoidal fits, as well as the
number of measurements for the comparisons shown in Fig.
Squared correlation coefficient
Statistics of the comparison between lidar and radio sounding at heights of 75, 100, 400, 600, and 700
Both the five-point geometrical and sinusoidal methods to derive wind
speed from the lidar data yield similar
results. However, the sinusoidal fit is of advantage for our
application as it only requires three input points to provide
a solution. This increases the number of measurement intervals that
can be used by around 25
Time series of lidar (black, every 50
Figure
Example measurement of 17 September 2014: calibrated backscatter
coefficients from ceilometer
The squared correlation coefficient for the solution for wind speed
improves from 0.86 at 100 to 0.94 at 400
There are a number of effects that might influence the measurements at low level. The primary source of discrepancy is likely to be the fundamentally different nature of the measurements. The radiosonde follows a unique trajectory resulting from the sum of its buoyant ascent rate and the motion of the air it ascends through. Within the atmospheric boundary layer, turbulence superimposes chaotic perturbations about the mean flow; the largest-scale eddies might result in very different trajectories depending on the precise time and location of launch. The lidar, on the other hand, calculates a wind profile from the air motions along each beam, which are separated both in time and in space – increasingly so with increasing altitude. These effects, along with the increasing spatial separation between the radiosonde and the lidar, may also cause the slight decrease in the correlation for wind direction with increasing altitude. An additional source of discrepancies is flow distortion around the ship; this would influence low-level measurements from both, with different effects on each due to their different locations.
The radiosonde will furthermore take time to accelerate to the
ambient wind speed following launch, and it can suffer from pendulum
motions as the tether unwinds after launch
Time series of wind speed and direction at an altitude of
100
A typical measurement day of 17 September 2014 is presented in
Fig.
Following the approach of
The observed standard deviation of the vertical velocity as
a function of SNR is presented in Fig.
In addition to the random error we also investigated the measurements
of vertical wind speed for systematic errors.
To determine the systematic errors of the measurements, we
averaged all data
for which steady wind conditions prevailed (about 3000 points at
200
Standard deviations of the Doppler horizontal velocity determined
from the zero lag impulse in the auto-covariance and the theoretical standard
deviation (black line) for a signal spectral width of 2
CFD study results for
There are a number of potential sources of real bias in the
measured vertical wind. One is the projection of
horizontal wind into the vertical wind speed measurement as the result of
imperfect motion stabilisation or misalignment of the lidar and
AHRS units; the latter is estimated to be less than
0.5
A CFD study of flow over the
The ship imposes a significant obstacle to the flow and forces
a strong vertical velocity in the lowest few tens of metres
above the lidar, which varies with wind direction
(Fig.
The vertical velocity at the top of the model domain at
250
We have presented Doppler lidar measurements made during the Arctic
cruise of the icebreaker
The fundamental measurement error of the lidar vertical wind speed was found to
be in the range of 0.025 to 0.2
Our determination of the residual linear velocity of the lidar follows the
complementary filtering method of
In order to determine the high-frequency time-varying velocity, we first
determine the instantaneous orientation of the platform, rotate the measured
accelerations from the instrument frame of reference to the Earth frame, and
integrate over time. The orientation of the platform is defined by a set of
Euler angles: pitch (
For small tilts from the horizontal (
Having obtained the full pitch, roll, and yaw angles for each sample
interval, the measured accelerations along sensor
The lidar Doppler velocity measurement is corrected by adding the component
of the mean platform velocity along the direction of the beam. We first
rotate the platform velocity back into the instrument reference frame,
The velocity along the beam is then simply the first (
ACSE was supported by funding from the Knut and Alice Wallenberg
Foundation, Swedish Research Council, Faculty of Science at
Stockholm University, US Office of Naval Research, the US National
Oceanic and Atmospheric Administration (NOAA), and the UK Natural
Environment Research Council (grant No. NE/K011820/1). The lidar and
the radio sounding system were supplied by the Atmospheric
Measurement Facility of the UK National Centre for Atmospheric
Science. We are grateful to the Swedish Polar Research Secretariat
and to the two captains and crews of the