Introduction
The measurement of horizontal wind profiles in the 20–70 km altitude range
remains a challenge for atmospheric science. Although a variety of in situ
and remote sensing techniques, summarised in Fig. 1, are available for
observing winds in the troposphere, lower stratosphere, and lower
thermosphere the routine measurement of upper stratospheric and mesospheric
winds have been difficult to obtain.
Overview of atmospheric wind measurement techniques with their
altitude coverage. For space-borne sensors the abbreviations for the
satellite/instrument names are given with years of operation.
Ground-based radar systems such as meteor radars (Maekawa et al., 1993;
Jacobi et al., 2007; Hoffmann et al., 2007), incoherent scatter radars
(Alcaydé and Fontanari, 1986; Nicolls et al., 2010) and medium frequency
radars (Briggs, 1980; Hoffmann et al., 2007) profile winds down to 70 km.
mesosphere–stratosphere–troposphere (MST) radar techniques (e.g. Hooper et
al., 2008; Lee et al., 2014) provide additional coverage over 0–20 km.
Under clear-sky conditions the Rayleigh–Mie–Raman (RMR) lidar (Baumgarten,
2010; Hildebrand et al., 2012) measures winds throughout the middle
atmosphere above Andenes, northern Norway but requires complex laser
transmission and detection equipment and is not portable. Ground-based
Doppler lidars measure tropospheric and lower stratospheric winds (Gentry et
al., 2000), with possible extension up to 50 km (Souprayen et al., 1999) and
sodium lidars cover the altitude range 85–100 km (Williams et al., 2004).
The ground-based E-region wind interferometer (ERWIN) measured upper
atmospheric winds at three altitudes near the mesopause using airglow
emissions from electronically excited atomic oxygen O(1S), OH, and
molecular oxygen (O2) (Gault et al., 1996a). Balloon-borne radiosondes
provide detailed wind measurements in the troposphere and lower stratosphere
(e.g. Hibbins et al., 2005). Rockets can deploy falling targets tracked by
radar (Müllemann and Lübken, 2005), or chemical tracers (Chu et al.,
2007), but such campaigns are expensive and unsuitable for long-term
monitoring. Infrasound measurements are used for investigating wind velocity
variations in the stratosphere, mesosphere, and lower thermosphere (e.g. Le
Pichon et al., 2010; Assink et al., 2012, 2013; Chunchuzov et al., 2015).
Over a 14-year period the space–borne high-resolution Doppler imager (HRDI)
(Burrage et al., 1996) measured wind velocities typically between
60∘ N and 60∘ S and down to 50 km and contributed to the
Upper Atmosphere Research Satellite (UARS) Reference Atmosphere Project
(URAP) (Swinbank and Ortland, 2003) wind climatology. Also on UARS, the
limb-sounding WIND Imaging Interferometer (WINDII) observed O(1S)
airglow emission to measure winds over 90–110 km (Gault et al., 1996b).
Since 2002 the TIMED Doppler Interferometer (TIDI) has been making
limb–scanning measurements of O(1S) and O2 (0–0) band emissions
for determining horizontal winds above 60 km (Killeen et al., 2006).
Satellite measurements of mesospheric winds down to 80 km were determined
from Aura Microwave Limb Sounder (MLS) observations of Doppler-shifted,
Zeeman-split O2σ- and σ+ lines around
118.75 GHz (Wu et al., 2008). Winds at 35–80 km were observed for a limited
time over the latitude range 30∘ S to 55∘ N using ozone
(O3) and hydrogen chloride emission line measurements in the
625–650 GHz range by the Submillimeter-Wave Limb-Emission Sounder
(SMILES) (Baron et al., 2013). The Atmospheric Laser Doppler Instrument
(ALADIN) on the forthcoming Atmospheric Dynamics Mission (ADM) Aeolus
satellite will make UV lidar measurements of winds in the troposphere and
lower stratosphere (Stoffelen et al., 2005). The aim of the planned
Stratospheric Wind Interferometer for Transport studies (SWIFT) is to make
global measurements of middle stratospheric winds between 15 and 50 km using
8 µm O3 emission lines (McDade et al., 2001; Shepherd et al.,
2001).
For the reasons outlined above, global models such as the semi-empirical
Horizontal Wind Model (HWM) (Drob et al., 2008, 2015) and
reanalysis datasets such as the European Centre for Medium-Range
Weather Forecasts (ECMWF) operational analyses (Dee et al., 2011) and NASAs
Modern-Era Retrospective Analysis for Research and Applications (MERRA)
(Rienecker et al., 2011) contain sparse information based on observations
above 20 km, in contrast to the widespread operational data for the lower
atmosphere. Systematic comparisons between co-located ground-based wind
radiometer, lidar, and infrasound observations and re-analysis data found
both temperature and horizontal wind speeds deviate increasingly above 40 km
as the assimilated observations became sparser (Le Pichon et al., 2015).
Between altitudes of 40 to 60 km the standard deviation of the mean
difference in zonal winds exceeds 20 m s-1 with the largest differences
in winter when variability associated with large-scale planetary waves
dominates. High-latitude mesospheric horizontal winds in HWM-07 (Drob
et al., 2008) have standard deviations greater than 25 m s-1 and
significant differences with observed zonal and meridional winds above 80 km
(Sandford et al., 2010). With ECMWF producing specifications based on
temperature soundings up to 75 km and fully assimilative high-top global
circulation models being extended into the thermosphere, there is
considerable urgency to verify the mean horizontal winds in models and
meteorological (re)analyses. Superimposed on the mean flow are atmospheric
tides and vertically propagating waves that influence the
planetary-scale circulation of the stratosphere, drive mesospheric
circulation, and drive chemical transport and temperature gradients through
pole-pole meridional circulation, turbulent mixing, and diffusion (Brasseur
and Solomon, 2005; Holton, 2004). These impact on the stability of the
northern and southern hemisphere polar vortices where abrupt changes or even
reversals of strong zonal winds during sudden stratospheric warming (SSW)
events lead to strong dynamical and chemical coupling between the lower and
upper atmosphere (Manney et al., 2008). New wind observing techniques for
the polar regions are essential to better understand and parameterise these
processes in circulation models for climate studies and numerical weather
prediction.
Attention has recently turned to using ground-based microwave and
sub-millimetre Doppler spectroradiometry to provide measurements of
horizontal wind profiles covering the altitude range 30–85 km. By measuring
the Doppler frequency shift of passive emission due to a rotational
transition by a selected atmospheric molecule the line-of-sight wind
speed can be determined (Clancy and Muhleman, 1993). The magnitude of the
shift Δν (in units of Hz) depends both on the wind speed along
the line-of-sight (LOS) of the detector, vLOS (in m s-1),
and the rest frame frequency of the line, ν0 (in Hz):
Δν=vLOScν0,
where c is the speed of light (in m s-1). The horizontal wind speed (in
m s-1) is given by
vwind=vLOSsecε,
where ε is the zenith angle of the ground-based observation.
By taking measurements of the Doppler shifts from perpendicular azimuthal
directions the zonal and meridional wind components are determined, and
measurement biases on each component can be removed using measurements taken
in opposite directions. The frequency shifts are small, in the range 5
to 200 kHz, but can be measured precisely using stable, high-resolution
digital fast Fourier transform spectrometers (Klein et al., 2012). Wind
speeds at 70–85 km above the South Pole were determined with uncertainty
±5 m s-1 by observing the carbon monoxide (CO) line at 461 GHz
(Burrows et al., 2007). Rüfenacht et al. (2012, 2014) used observations
of the O3 microwave emission line at 142.18 GHz by the ground-based
wind radiometer (WIRA), and optimal estimation retrieval, to measure daily
mean zonal and meridional wind profiles. Comparison of their measured time
series from four locations at polar, mid-, and tropical latitudes with
ECMWF model data showed that meridional and zonal stratospheric winds agreed
to within 10 %. However in the mesosphere, above 40–50 km, observed and
modelled zonal wind speeds differ significantly by up to 50 %
(Rüfenacht et al., 2014).
The aim of this work is to investigate the potential for retrieving wind
speeds from ground-based 230–250 GHz radiometer observations of the
polar atmosphere. Potential advantages of radiometry at these intermediate
frequencies, in-between the microwave and sub-millimetre, include
larger Doppler shifts than in the microwave, lower atmospheric opacity and
signal attenuation and smaller Doppler line widths than in the
sub-millimetre, and numerous isolated or overlapping O3 emission
lines and a CO line centred at 230.54 GHz. The O3 231.28 GHz line
intensity (4.846 × 10-23 cm molecule-1 at 296 K) is over
twice that for the 142.18 GHz line (2.346 × 10-23 cm molecule-1 at 296 K), producing a more intense emission signal at
source. We perform calculations for simulated wind retrievals above Halley
station, Antarctica. Studies of mean winds, gravity waves, planetary waves,
and atmospheric tides have utilised radiosonde balloon, imaging Doppler
interferometer, and SuperDARN radar observations from Halley (Hibbins et
al., 2006, 2009; Nielsen et al., 2012). These observations
have been limited to the troposphere, lower stratosphere, and upper
mesosphere; co-located radiometric measurements could provide
complementary observations filling the gap in altitudes at 25–75 km. In
Sect. 2 the methodology for simulating millimetre-wave atmospheric
spectra and performing wind retrievals is described. In Sect. 3 we present
the wind retrieval results for different atmospheric conditions and
radiometer instrument configurations, and the main conclusions are
summarised in Sect. 4.
Methodology
Ground-based radiometer instrument and location
Atmospheric observations are simulated for a ground-based
millimetre-wave radiometer located at Halley station (75∘37′ S, 26∘14′ W, 43 m above mean sea level), Antarctica. The
instrument characteristics and performance are based on an existing total
power radiometer (Espy et al., 2006; Newnham et al., 2011; Straub et al.,
2013; Daae et al., 2014), a relatively portable and robust instrument that
has been deployed in the polar regions for semi-autonomous, continuous
year-round operation. This instrument utilises a
superconductor–insulator–superconductor (SIS) mixer at 4 K and
low-noise amplifiers for sensitive heterodyne measurements of atmospheric
spectra in the frequency region 230–250 GHz. Measurements by such a system
achieve a single-sideband noise temperature of 200 K and a total system
temperature of 1400 K. We also assess how wind measurements would be
improved by using radiometers with system temperatures of 700 and 1000 K.
Spectral analysis of the down-converted signal over a 300 MHz bandwidth,
centred on the emission line(s) of interest, and with channel widths ≥10 kHz is based on the specifications of commercially available chirp
transform and fast Fourier transform (FFT) spectrometers for radiofrequency
(RF) analysis. Rüfenacht et al. (2014) showed for the WIRA instrument
that frequency errors arising from reference oscillator instabilities and
spectrum baseline artefacts such as standing waves are either small or can
be adequately characterised to minimise their impact on the wind retrievals.
However for other wind radiometers these effects could make a larger
contribution to the measurement uncertainty that is not considered in the
simulations here. For example, with instruments using a SIS mixer there is
the potential for significant interfering reflections between cryostat
windows and other optical components. The potential sources of such
artefacts need to be identified at the instrument design and build stages
and steps taken to reduce them to an acceptable level, e.g. through
anti-reflection machining of optical surfaces and path-length
modulation aimed at minimising standing wave amplitudes.
The radiometer is assumed to make total power measurements in turn of two
calibration targets, one at ambient temperature and a cold reference load,
and upward-viewing sky measurements at either two or four cardinal
azimuthal directions and at a fixed zenith angle. If the duration of each
measurement is ∼ 10 s, allowing for receiver mirror
repositioning in each viewing direction, then one complete measurement cycle
taking ∼ 60 s would provide calibrated spectra in two
azimuthally opposite directions, i.e. east and west for zonal wind and
north and south for meridional wind determination. Integration of measured
data over repeated calibration cycles increases the signal-to-noise ratio of
the calibrated atmospheric spectra.
The zenith angle of the sky observation affects the wind measurement in a
number of ways. At higher zenith viewing angles the LOS Doppler shift due to
the horizontal movement of the observed air mass is increased. The
atmospheric column of ozone or carbon monoxide molecules increases with
zenith angle, with angles of 45, 60, and
80∘ yielding geometric air mass factors of 1.4, 2.0, and 5.8
respectively. Atmospheric opacity will affect the wind measurement and may
dominate at higher zenith angles under conditions of high precipitable water
vapour (PWV).
At different slant angles the air mass observed, and its distance from the
radiometer, will change. For a zenith angle of 45∘, the distances
on the ground between Halley and the intercepts at altitudes of 25, 50,
and 75 km are 25, 50, and 75 km, neglecting refraction, whereas at
80∘ the distances are 142, 284, and 425 km, respectively.
Since the zonal and meridional wind retrievals are derived by combining
radiometric measurements at opposing east–west or north–south
directions, the choice of zenith angle will affect the spatial resolution of
wind structures and atmospheric dynamical effects, as well as inter-comparisons
with radiosonde, radar, and uniformly gridded reanalysis data. Halley is
typically inside the Antarctic polar vortex, which can extend to
60∘ S (Turunen et al., 2009) meaning that wintertime
observations, even at a zenith angle of 80∘, would usually be
well within the vortex edge. Halley station is on the Brunt Ice Shelf, a
relatively flat location that would allow unobscured clear-sky views from
the ground in all directions and at zenith angles reaching 80∘ or
higher. However, antenna sidelobes could adversely affect the radiometric
calibration for atmospheric observations made at high zenith angles.
Figure 2 shows histograms of 6-hourly zonal and meridional wind data from
ECMWF Interim re-analysis data (Dee et al., 2011) over the pressure
(altitude) range 0.1–25 hPa (∼ 64–25 km). The data are for
75.5∘ S, 26.5∘ W, the grid point closest to Halley, and
cover the austral winter (June, July, August – JJA) and summer (December,
January, February – DJF) periods over the 5-year period 2009–2014. The zonal
winds in the middle atmosphere are predominantly westward in summer with
mean speed -9 m s-1 and more strongly eastward in winter with mean
value +34 m s-1. However the re-analysis data show a large range
of zonal wind speeds, in particular during winter where wind speeds span
-36 to +126 m s-1. The meridional winds are lighter with
mean values of +1 m s-1 in both winter and summer. The winter
meridional wind speeds show a large range from -92 to
+75 m s-1.
Histograms of (a) zonal and (b) meridional winds over the
pressure range 0.1–25 hPa (∼ 64–25 km) in winter (JJA, blue)
and summer (DJF, red) from 6-hourly ERA-interim data for 2009–2014 at
grid-point 75.5∘ S, 26.5∘ W. The horizontal error
bars show the mean winds (μw, μs) and standard
deviations (σw, σs) for winter (JJA) and summer
(DJF) respectively. The corresponding boxplots of the (c) zonal and
(d) meridional wind data indicate the minima, lower quartile (25th percentile), median, upper quartile (75th percentile), and maxima wind
speeds. +ve zonal winds are eastwards and +ve meridional winds are
northwards.
Wind speed gradients across the areas covered by measurements in opposite
azimuthal directions will affect the zonal and meridional wind measurements.
We have compared ECMWF Interim re-analysis zonal and meridional wind
speed data for 2012 at the grid point closest to Halley with the
corresponding data for grid points within the areas covered by measurements
at zenith angles of 45, 60, and 80∘. For
zenith angle 45∘ over altitudes 35–65 km, and zenith angle
60∘ below 50 km, the mean difference in wind speeds is below
1 m s-1. For zenith angle 60∘ and altitude 65 km the mean
difference is 1.2 m s-1 in zonal wind and 1.6 m s-1 for meridional
winds. At higher zenith angle the wind gradients are larger and increase
with altitude as the coverage area expands. At 80∘ zenith angle
the mean differences in zonal winds at 35, 50, and 65 km altitude are
2.1, 21.9, and 26.8 m s-1, respectively. For
meridional winds the corresponding values are 2.7, 11.4, and 16.7 m s-1. For both zonal and meridional winds the
largest instantaneous zonal or meridional wind gradients approach
90 m s-1 at 65 km for 80∘ zenith angle. Wind gradients across
the area observed by wind radiometry could therefore have a significant
effect on the retrieved wind speeds at higher zenith angles (above
60∘) and in the mesosphere where the observed air masses are
separated by hundreds of km.
Atmospheric spectra
The clear-sky atmospheric spectrum in the 230–250 GHz region above
Halley is dominated by discrete O3, O2, and CO lines together with
smoothly varying continua due to water vapour, oxygen, and nitrogen. Weak
emission lines in this frequency range due to trace species such as nitric
oxide and nitrogen dioxide are not included in our wind retrieval
calculations. Winter (June, July, August – JJA) and summer (December,
January, February - DJF) seasonal average profiles of O3, CO,
water vapour, O2, and temperature over the altitude range 0–120 km are
calculated from 12 years of simulations by the Whole Atmosphere Community
Climate Model with Specified Dynamics (SD-WACCM) version 3.5.48 (Garcia
et al., 2007; Marsh, 2011; Lamarque et al., 2012). The profiles, calculated
by combining the day-time and night-time SD-WACCM profiles at
74.8 and 76.7∘ S, the gridded latitudes closest to
Halley, according to the solar elevation angle at 72 km are shown in Fig. 3.
The continuum contribution from molecular nitrogen uses standard
sub-Arctic profiles. Compared to the summer case, wintertime O3
VMR is higher in the secondary ozone layer centred at 10-3 hPa
(∼ 96 km) and in the seasonal tertiary layer at
∼ 0.05 hPa (∼ 70–75 km). In summer O3 VMR
is higher in the upper stratosphere between 0.3–0.8 hPa (∼ 54–38 km). Mesospheric CO VMR is higher in winter, due to strong descent in
the southern polar vortex, but SD-WACCM may underestimate the seasonal CO
variability observed by Aura MLS (Pumphrey et al., 2007). Higher summer mean
temperatures and tropospheric water vapour VMR lead to increased PWV and
atmospheric opacity at millimetre wavelengths. For Halley the mean PWV
calculated from the SD-WACCM data is 6.58 mm in summer and 1.18 mm in
winter. The lower quartile PWV in winter is 0.92 mm, i.e. for 25 % of the
time during winter months (JJA) PWV is at this value or lower with a mean
value of 0.76 mm.
Seasonal mean winter (JJA, solid blue line) and summer
(DJF, dashed red line) atmospheric profiles for (a) O3 VMR, (b) CO VMR,
(c) water vapour VMR, (d) O2 VMR, and (e) temperature from SD-WACCM
simulation data.
Simulated ground-based atmospheric brightness
temperature spectra for clear-sky conditions, 60∘ zenith angle viewing
conditions at Halley station (75∘37′ S, 26∘14′ W),
Antarctica for (a) the frequency range 228–252 GHz in winter (JJA, solid
blue line) and summer (DJF, dashed red line). The 300 MHz wide target
frequencies, highlighted as grey shaded panels in (a), are shown enlarged
for the (b) 230.54 GHz CO, (c) 231.28 GHz O3, and (d) 249.79 and
249.96 GHz O3 lines in winter.
The Atmospheric Radiative Transfer Simulator (ARTS) (version 2.2.0) available
at http://www.radiativetransfer.org/ is the forward model used in this
study (Buehler et al., 2005; Eriksson et al., 2011). ARTS is a line-by-line
model that can simulate radiances from the infrared to the microwave, and has
been validated against other models in the millimetre spectral range
(Melsheimer et al., 2005). It includes contributions from spectral lines and
continua via a choice of user-specified parameterisations. For our work, we
use the Planck formalism for calculating brightness temperatures and
spectroscopic line parameters are taken from the high-resolution transmission
(HITRAN) molecular database 2012 (Rothman et al., 2013). The oxygen continuum
according to Rosenkranz (1998), nitrogen self-broadening (Liebe et al.,
1993), and water vapour continuum (Rosenkranz, 1993) are included in the
model. Survey clear-sky atmospheric spectra covering the 228 to 252 GHz
range, calculated on a 10 MHz frequency grid, are shown in Fig. 5a. The
higher baseline brightness temperatures, and reduced emission line signals in
summer at Halley are due primarily to increased atmospheric opacity at higher
tropospheric temperature and water vapour VMR. The spectra show the most
intense O3 emission lines, the J=2→1 CO line centred at
230.54 GHz, and a 16O18O line centred at 233.95 GHz. The nearly
constant mixing ratio of 16O18O could make the 233.95 GHz emission
line suitable for profiling winds throughout the stratosphere and mesosphere.
However, the Zeeman-splitting of the 16O18O line would need to be
accurately modelled in the forward model and retrieval algorithms
(Navas-Guzmán et al., 2015) and such analysis is not included in this
report. The enlarged 300 MHz-wide plots shown in Fig. 5b–d show the target
frequencies for wind retrievals with the molecular line shapes dominated by
contributions from Doppler- and pressure broadening.
Example zonal wind retrievals for simulated clear-sky,
12 h observations (i.e. 6 h in east and 6 h in west directions) of the
O3 231.28 GHz line using a ground-based radiometer with a 1400 K
system temperature, 30 kHz frequency resolution, and 60∘ zenith
viewing angle located at Halley station (75∘37′ S, 26∘14′ W), Antarctica. In (a) and (e) every sixth averaging kernel, and the
scaled measurement response (MR), are shown for mean winter (JJA) and summer
(DJF) conditions respectively. The vertical grey lines in (a) and (e),
dashed horizontal lines, and the thicker sections of the plots indicate
where MR ≥ 0.8.
For wind retrievals, Doppler-shifted atmospheric spectra are calculated
for ground-based north- and south-, or east- and west-,
pointing azimuthal directions with zonal and meridional winds at fixed
values of +20 m s-1 at all altitudes from the ground to 120 km. The
frequency spacing of the atmospheric spectra is 10 kHz within 2.3 MHz of
line centres, 100 kHz at 2.3–9.4 MHz from the line centres, and 1 MHz
beyond 9.4 MHz from the line centres. This variable frequency grid ensures
the spectral features are accurately represented while reducing the
computing resource needed for wind retrieval calculations.
The statistical fluctuation ΔT (K) in the total system temperature
Tsys (K) is calculated according to the ideal radiometer
equation (Kraus, 1986):
ΔT=TsystΔf,
where t is observation time (in s) and Δf is the frequency resolution
(in Hz) of the radiometer.
Wind retrieval
The simulated atmospheric spectra are inverted into altitude profiles of
zonal and meridional wind speed using an iterative optimal estimation method
(OEM) (Rodgers, 2000) implemented in the Qpack (a part of atmlab v2.2.0)
software package (Eriksson et al., 2005). A detailed description of wind
profile retrievals using ARTS and Qpack is given by Rüfenacht et al. (2014).
Here we focus on the description of our specific retrieval setups and
discussion of results for wind speed estimations from simulated 230–250 GHz
measurements at Halley, Antarctica. Iterative absorption calculations in
ARTS are performed line by line inside the radiative transfer
calculation, rather than using pre-calculated look-up tables, in order
to accurately model atmospheric spectra at the Doppler shifted frequencies
(Buehler et al., 2011).
O3 or CO VMR profiles and zonal/meridional wind profiles are retrieved
at altitude levels 0–120 km with a 1 km spacing, where hydrostatic
equilibrium is assumed for the altitude and pressure. The a priori wind speed
is 0 m s-1 for all altitudes, with diagonal elements of the covariance
set according to a horizontal wind speed uncertainty of 20 m s-1 based
on the ECMWF reanalysis data (Fig. 3). Rüfenacht et al. (2014) showed that
the retrieved wind profiles are relatively insensitive and unbiased to
different a priori wind profiles even when the a priori assumption is far
from the true wind. The shape of the covariance is set to decrease linearly
towards the off-diagonal elements with correlation length adjusted to match
the altitude resolution of initial retrievals using only the diagonal
covariance matrix elements. The correlation length is typically in the range
0.6–0.8 of a pressure decade (approximately 10–12 km).
The O3 and CO a priori VMR profiles used in wind retrievals are those
used to calculate the simulated atmospheric spectra, apart from calculations
to test the effect of scaling the original VMR profiles at all altitudes by
80, 90, 110, and 120 %. The diagonal elements in the covariance of the
O3 and CO a priori are fixed at the square of 50 % of the VMR
values. The shape of the covariance is set to linearly decrease towards the
off-diagonal elements with a correlation length of a fifth of a pressure
decade (approximately 3 km).
Nominal wind retrievals were performed for simulated clear-sky 12 h
observations of the O3 231.28 GHz line at 60∘ zenith angle from
Halley in mean winter and summer conditions and for a radiometer with 1400 K
system temperature and 30 kHz frequency resolution. The averaging kernels
(AVKs) for every sixth retrieved altitude are shown in Fig. 5a and e for the
winter (JJA) and summer (DJF) cases respectively. The AVKs describe the
relationship between the true, a priori, and retrieved atmospheric states
(Rodgers, 2000). None of the AVKs peak at pressure levels above 0.02 hPa
(∼ 74 km) in winter, or above 0.08 hPa (∼ 66 km) in summer due
to the combination of Doppler broadening dominating over pressure broadening
and low O3 VMR in particular during summer when the seasonal tertiary
ozone layer at 70–75 km is not present. The lowest AVK peaks are at 27 hPa
(∼ 25 km) in winter and 17 hPa (∼ 28 km) in summer. The
retrievals in summer are also adversely affected by higher PWV and
atmospheric opacity. O3 diurnal variability also affects the
measurements, with wind information retrieved from simulated observations
using either day- or night-time profiles during mid-winter (15 July) but not
from day-time observations at mid-summer (15 January). Wind information can
be retrieved for both day- and night-time conditions at the start and end of
summer (1 December and 28 February) and start and end of winter (1 June and
31 August), but for these dates day-time wind profiles only reach
∼ 64 km due to low O3 abundance at higher altitude.
The sum of the AVKs at each altitude, called the measurement (or total)
response (MR), represents the extent to which the measurement contributes to
the retrieval solution as compared to the amount of influence of the a priori
at that altitude (Christensen and Eriksson, 2013). The altitude range where
the retrieved wind profile has a high degree of independence from the a
priori is estimated by MR values higher than 0.8. The retrieval range is
shown by the thicker sections of the black lines in Fig. 5a and e and
is 0.02–27 hPa (∼ 74–25 km) for mean wintertime conditions and
0.08–17 hPa (∼ 66–28 km) in summer. Outside of these altitudes
(i.e. below 25 km and above 74 km in winter, and below 28 km and above
66 km in summer) the MR weakens and wind values in these regions should be
interpreted with caution as the information from the a priori becomes
important. The AVKs indicate the range of altitudes over which the retrieved
wind speeds has smoothed the information in the data. Thus, the full-width
half-maximum (FWHM) width of the kernels provide a measure of the vertical
resolution of the retrieved profile. The FWHM values shown in Fig. 5b and f indicate altitude resolutions of 10.0–15.5 and 9.5–14.9 km
over the winter and summer retrieval ranges respectively, similar to the WIRA
instrument performance (Rüfenacht et al., 2014). The OEM calculations
provide observation errors σobs and total retrieval
(observation plus smoothing) errors (σtot) to give further
diagnostic estimates of the uncertainty of retrieved profiles. The
observation errors describe how the retrieved profiles are affected by
measurement noise and are shown in Fig. 5c and g, with typical
values of 4.8 m s-1 in winter and 6.1 m s-1 in summer. The
observation errors are small outside of the range of the AVK peaks as the
retrieval tends to the a priori values in these regions and the contribution
from the measurement is small. The total retrieval errors shown in Fig. 5d
and h are in the range 7.8–15.9 m s-1 in winter and
9.8–15.3 m s-1 in summer, and outside the range of AVK peaks tend
towards the a priori standard deviation of 20 m s-1.
We have also assessed measurement uncertainties using Monte Carlo
simulations, as was done by Rüfenacht et al. (2014) in their wind
retrievals using the O3 142.18 GHz emission line. Our Monte Carlo error
analysis results, using 500 repeat zonal wind retrievals to test the
retrieval algorithm's ability to reproduce the “true” state of the
atmosphere, are shown in Fig. 6. Figure 6c and h are for the winter
and summer nominal cases, i.e. simulated clear-sky, 12 h observations
(i.e. 6 h in east and 6 h in west directions) of the O3 231.28 GHz line
using a ground-based radiometer with a 1400 K system temperature, 30 kHz
frequency resolution, and 60∘ zenith viewing angle. Over the
trustable altitude range the mean wind profile is 20.3 m s-1 in winter
and 19.6 m s-1 in summer, both values within 2 % of the “true”
value of 20.0 m s-1. The standard deviation of the individual
retrievals is an estimator for the uncertainty of the wind retrieval, and
the mean values of 4.8 m s-1 in winter and 6.1 m s-1 in summer
match the mean observation errors determined from single retrievals. This is
not surprising as both parameters are dependent on the signal-to-noise
ratio of the input spectrum. Our calculated observation error is
considerably smaller than the 12–20 m s-1 range reported for the WIRA
new single sideband receiver (Rüfenacht et al., 2014). The improvement
is probably largely due to the low noise levels for a SIS mixer receiver
used in our spectrum simulations, and the larger Doppler shifts and higher
line intensity of O3 at 231.28 GHz compared to the 142.18 GHz line.
However it should be noted that the location and atmospheric conditions for
the calculations differ and an exact comparison between the actual, or
likely, performance of each instrument cannot be made using these data.
Figure 6a–b, d–e and f–g, i–j show the Monte Carlo simulation
results for winter and summer conditions respectively when the a priori
O3 VMR profiles are scaled by 80, 90, 110, and 120 %
of the “true” profiles used to simulate the atmospheric spectra. These
calculations indicate that 10 and 20 % uncertainties in a priori
O3 VMR could introduce errors in the retrieved wind profiles of ± 2 and ± 4 m s-1, respectively. However, careful
construction of a priori datasets and configuring of retrieval
parameters may mitigate against such errors which would be significant at
wind speeds of 20 m s-1 but would have less effect on measuring wind
speeds of 100 m s-1. Uncertainties in spectroscopic parameters and
temperature profiles are not expected to cause significant biases in the
retrieved winds, as was reported by Rüfenacht et al. (2014).
Monte Carlo error analyses using 500 repeat zonal wind
retrievals for simulated clear-sky, 12 h observations (i.e. 6 h in east
and 6 h in west directions) of the O3 231.28 GHz line using a
ground-based radiometer with a 1400 K system temperature, 30 kHz
frequency resolution, and 60∘ zenith viewing angle located at
Halley station (75∘37′ S, 26∘14′ W), Antarctica. The a
priori O3 VMR profiles are scaled by 80, 90, 100,
110, and 120 % of the “true” profiles for (a)–(e), and
(f)–(j) respectively. The mean retrieved winter and summer winds and 1σ
errors (shaded areas) are shown, with the thicker sections and the shaded
grey panels indicating where MR ≥ 0.8. The true wind profile used to
simulate the atmospheric spectra is shown by the dash-dotted green lines.
The a priori wind profile is shown by the dotted green lines.
Results
In the following sections horizontal wind retrieval results are presented
for simulated scenarios where five instrument parameters are varied: the
zenith viewing angle of the ground-based observation, the instrument's
frequency resolution, the radiometer system temperature, the observed
emission line, and the measurement time. The main results are summarised in
Table 1. The wind retrievals shown are for the zonal component of the
horizontal wind and quoted measurement times are for corresponding
observations made in opposing east and west directions. Identical results
are obtained for meridional wind analyses where the simulated measurements
are in north and south pointing directions.
Summary of wind retrieval results. Numbers in bold are for the
nominal retrieval case in each parameter category.
Parameter
Value
Pressure range
Altitude range
Mean (range)
Mean (range)
Mean (range)
/hPa
/km
AVK FWHM/km
σobs/m s-1
σtot/m s-1
Winter
Summer
Winter
Summer
Winter
Summer
Winter
Summer
Winter
Summer
Zenith angle
45∘
0.03–16
0.10–11
29–73
31–64
13.2 (10.9–15.7)
12.9 (10.2–15.4)
5.2 (4.3–7.4)
6.5 (5.5–7.7)
9.9 (8.1–15.0)
12.0 (10.2–14.9)
60∘
0.02–27
0.08–17
25–74
28–66
12.1 (10.0–15.5)
12.2 (9.5–14.9)
4.8 (3.7–7.7)
6.1 (5.0–7.7)
9.9 (7.8–15.9)
11.7 (9.8–15.3)
80∘
0.02–39
0.12–17
23–74
28–63
11.4 (9.3–14.7)
12.6 (9.9–15.4)
4.5 (3.3–7.2)
6.5 (5.5–7.8)
9.7 (7.5–16.1)
12.3 (10.5–15.3)
Δf
10 kHz
0.02–27
0.08–17
25–74
28–66
12.1 (10.0–15.5)
12.2 (9.5–14.9)
4.8 (3.7–7.7)
6.1 (5.0–7.7)
9.9 (7.8–15.9)
11.7 (9.8–15.3)
30 kHz
0.02–27
0.08–17
25–74
28–66
12.1 (10.0–15.5)
12.2 (9.5–14.9)
4.8 (3.7–7.7)
6.1 (5.0–7.7)
9.9 (7.8–15.9)
11.7 (9.8–15.3)
100 kHz
0.02–27
0.08–17
25–74
28–66
12.1 (10.0–15.5)
12.2 (9.5–14.9)
4.8 (3.7–7.7)
6.1 (5.0–7.7)
9.9 (7.8–15.9)
11.7 (9.8–15.3)
300 kHz
0.02–27
0.09–17
25–74
28–65
12.4 (10.1–15.6)
12.1 (9.5–14.9)
4.7 (3.5–7.6)
6.1 (5.0–7.7)
9.6 (7.5–15.7)
11.7 (9.8–15.1)
1 MHz
0.12–23
0.25–17
26–63
28–58
12.4 (10.0–15.5)
11.6 (9.6–13.7)
4.9 (3.7–7.3)
5.8 (4.8–7.7)
9.7 (7.8–13.4)
11.0 (9.4–13.8)
Tsys
700 K
0.02–39
0.04–35
23–75
23–71
10.5 (8.5–13.8)
11.3 (8.5–13.9)
4.0 (3.0–7.0)
4.9 (3.6–7.7)
9.5 (7.3–16.7)
10.0 (8.0–15.1)
1000 K
0.02–32
0.06–23
24–74
26–68
11.3 (9.3–14.9)
11.7 (9.0–14.4)
4.4 (3.3–7.4)
5.4 (4.2–7.5)
9.6 (7.5–15.8)
10.5 (8.6–14.9)
1400 K
0.02–27
0.08–17
25–74
28–66
12.1 (10.0–15.5)
12.2 (9.5–14.9)
4.8 (3.7–7.7)
6.1 (5.0–7.7)
9.9 (7.8–15.9)
11.7 (9.8–15.3)
Measurement time
4 h
0.03–13
–
30–73
–
13.5 (11.1–16.3)
–
5.5 (4.6–7.3)
–
10.3 (8.5–15.4)
–
6 h
0.03–16
0.01–11
29–73
31–64
12.9 (10.7–15.5)
13.0 (10.3–15.5)
5.2 (4.3–7.3)
6.5 (5.6–7.7)
10.1 (8.2–15.3)
12.0 (10.3–15.1)
12 h
0.02–27
0.08–17
25–74
28–66
12.1 (10.0–15.5)
12.2 (9.5–14.9)
4.8 (3.7–7.7)
6.1 (5.0–7.7)
9.9 (7.8–15.9)
11.7 (9.8–15.3)
Emission line
O3231.28 GHz
0.02–27
0.08–17
25–74
28–66
12.1 (10.0–15.5)
12.2 (9.5–14.9)
4.8 (3.7–7.7)
6.1 (5.0-7.7)
9.9 (7.8–15.9)
11.7 (9.8-15.3)
O3 250 GHz
0.02–27
0.05–20
25–75
27–69
11.1 (9.4–13.8)
12.0 (9.4–14.8)
4.3 (3.4–7.4)
5.3 (4.0–7.4)
9.7 (7.6–16.4)
10.2 (8.4–14.7)
CO 230.54 GHz
0.0009–0.03
0.0009–0.03
73–97
73–97
19.6 (19.5–20.1)
16.0 (15.5–16.4)
2.7 (1.7–4.7)
2.6 (2.3–3.4)
12.2 (9.2–16.3)
(8.0–15.4)
CO 230.54 GHz
0.001–27
0.001–20
25–96
27–96
14.8 (10.3–32.3)
13.8 (10.4-16.8)
4.0 (2.3–7.3)
5.2 (2.4–7.7)
10.2 (7.5–16.1)
(8.3–15.4)
+ O3 231.28 GHz
Effect of zenith angle
In order to observe a Doppler shift in the millimetre-wave atmospheric
emission arising from the horizontal motion of the molecules in the air
mass, observations must be made at non-zero zenith angles. The results of
wind retrievals for simulated observations with zenith angles of
45, 60, and 80∘ are shown in Fig. 7 and in
Table 1. A zenith angle of 80∘ gives the best results for the
Halley mean wintertime conditions considered, with winds retrieved over
0.02–38.8 hPa (∼ 74–23 km). Summertime coverage at
80∘ is over a narrower pressure range, 0.12–16.9 hPa
(∼ 63–28 km), and at a 60∘ angle the retrieval for
summer conditions reaches slightly higher, covering 0.08–16.9 hPa
(∼ 66–28 km). The 80∘ observations give the best
height resolutions in winter, estimated at 9–15 km from the AVK FWHMs, and
smallest observation errors, in the range 3.3–7.2 m s-1. In summer
both the height resolutions and observation errors at 60∘ are
slightly smaller than for the corresponding 45 or 80∘
summer retrievals over most of the altitudes where wind information is
retrieved from the measurement. With 30∘ zenith angle simulations
the retrieval total response did not exceed 0.8 at any altitude. The
seasonal variability of the wind retrieval quality indicates that the wind
information contained in the Doppler-shifted O3 231.28 GHz emission
line signals depends on zenith angle-dependent factors including
line-of-sight Doppler shifts, air mass factor, and atmospheric opacity
as well as the effects of different seasonal O3 VMR and temperature
profiles. For the zenith angles considered, 80∘ provides the
highest air mass factor and highest LOS Doppler shift with a relatively
small 10∘ angle between the observing beam and the horizontal
plane giving high projection efficiency. The optimum zenith angle will vary
with ground-based location and the atmospheric conditions at the time of
making observations, as well as considerations of the spatial distances
between measurements in opposite directions. From a practical perspective,
the range of zenith angles that the instrument can be pointed may be limited
by the requirement to have a clear, unobscured view of the sky continuously
throughout measurements in each different azimuthal direction.
Zonal wind retrievals for different zenith viewing
angles, where AVK FWHM are the full-width half-maxima of each
averaging kernel, σobs is the measurement uncertainty, and
σtot is the total uncertainty. Calculations are for simulated
clear-sky, 12 h observations (i.e. 6 h in east and 6 h in west
directions) of the O3 231.28 GHz line in mean winter (JJA) and summer
(DJF) conditions at Halley station (75∘37′ S, 26∘14′ W), Antarctica using a ground-based radiometer with a 1400 K system
temperature and 30 kHz frequency resolution. The horizontal dashed lines and
thicker sections of the curves indicate the pressure/altitude ranges where
MR ≥ 0.8.
Effect of instrument frequency resolution
The results of wind retrievals for simulated observations with instrument
channel spacing of 10, 30, 100, 300 kHz, and 1 MHz are shown in
Fig. 8 and Table 1. Increasing the frequency resolution from 10 kHz to
300 kHz has little effect on horizontal wind retrievals from 12 h simulated
observations of the 231.28 GHz O3 emission line in mean wintertime
or summertime conditions at Halley. Height resolutions, estimated from
the AVK FWHMs, and observation errors are similar for all five resolutions
below 1 hPa (∼ 48 km). At 1 MHz resolution the upper limit
where the measured data dominate the wind retrieval is substantially lower,
at 0.12 hPa (∼ 63 km) in winter and 0.25 hPa (∼ 58 km) in summer and, close to this altitude limit, the observation errors
increase to 7.7 m s-1.
As Fig. 7, but for different frequency resolutions and
a 60∘ zenith viewing angle.
The lack of sensitivity of the simulated wind retrievals to frequency
resolution, at least up to 300 kHz channel spacing, is surprising given that
the LOS Doppler shift of the O3 231.28 GHz emission line is 13.4 kHz
for a 20 m s-1 horizontal wind viewed at 60∘ zenith angle.
However, the Jacobian and gain matrices for the wind retrievals indicate the
Doppler-shifted spectral response should be adequately sampled at
instrument resolutions up to 300 kHz for altitudes where the O3
measurement contributes significantly to the retrieval. Frequency resolution
in the range 10–30 kHz is needed to determine upper mesospheric winds from
CO 230.54 MHz observations where Doppler shifts above 75 km result in
changes to the spectral distribution much closer to the emission line
centre. The values of the Jacobian describing the O3 wind retrieval,
normalised by the layer thickness of the retrieval grid for observations at
a 60∘ zenith angle, are shown in Fig. 9 with typical values
around 0.15 mK (m s-1)-1 km-1. The effect of wind variations
of 20 m s-1 on the measured atmospheric brightness temperature will
therefore be small, of the order of 3 mK km-1. For an ideal instrument
the baseline signal-to-noise ratio varies as 1/Δf
for a fixed measurement time, i.e. a factor 3.3 improvement for a
10-fold change in frequency resolution (Δf) from 30 to
300 kHz. Although the improvement in the signal-to-noise ratio gained by lower
resolution measurements is desirable for measuring small changes in
brightness temperature arising from the Doppler shifts, this appears to be
largely offset by reduced sampling of the frequency distribution of the
emission signal. Lower resolution measurements would however produce smaller
datasets for a given frequency bandwidth, which would have the
advantages of processing speed and lower demand on computing resources for
data storage, transfer, and analysis to retrieve atmospheric information.
Rows of the Jacobian describing the horizontal wind
retrieval, normalised by the layer thickness of the retrieval grid. The data
are from zonal wind retrievals for simulated clear-sky, 12 h observations
(i.e. 6 h in east and 6 h in west directions) of the O3 231.28 GHz line
using a ground-based radiometer with a 1400 K system temperature, 30 kHz
frequency resolution, and 60∘ zenith viewing angle located at
Halley station (75∘37′ S, 26∘14′ W), Antarctica. The
colour scale in (a) and (b) indicates the values of the Jacobian matrix.
Rows of the Jacobian matrix for selected altitude levels are plotted in (c)
and (d). Plots (b) and (d) show the centre frequencies on an expanded scale.
Effect of radiometer system temperature and measurement time
The results of zonal wind retrievals for simulated observations with
radiometer system temperatures of 700, 1000, and 1400 K are shown in
Fig. 10 and Table 1. The altitude range, height resolution, and observation
errors of the wind retrievals all improve with lower system temperature, due
to the higher signal-to-noise ratio of the measurements. The signal-to-noise ratio of the
simulated measurements is based on real instrument data for a radiometer
operating at 230–250 GHz and varies with Tsys, i.e. the noise
level halving when Tsys changes from 1400 to 700 K. This
impacts directly on the measurement of small changes in atmospheric emission
spectra arising from Doppler shift perturbations and the retrieval of wind
information, as discussed previously in Sect. 3.2.
As Fig. 7, but for different radiometer system
temperatures and a 60∘ zenith viewing angle.
The results of zonal wind retrievals for simulated 4, 6, and 12 h
measurements (i.e. 2, 4, and 6 h observations in east and west
directions) with a system temperature of 1400 K are shown in Fig. 11 and
Table 1. For the 4 h summertime observation, and measurement times below
4 h (not shown) for the winter case, the retrieval total response does not
exceed 0.8 at any altitude. The minimum measurement times for successfully
retrieving zonal or meridional winds is 4 h in mean wintertime
conditions at Halley and 6 h in summer for the specified instrument
configuration. The altitude range, height resolution, and observation error
of the wind retrievals all improve as measurement time t increases, due to
higher signal-to-noise ratio, which varies as t. The time resolution
of horizontal wind measurements is limited by the need to acquire
atmospheric spectra with sufficiently low noise for the wind retrieval to
succeed. During optimum observing conditions at Halley the measurement time
is considerably reduced, as shown in Fig. 12 and Table 1 for mean
wintertime atmospheric profiles when PWV is in the lower quartile, i.e.
during a quarter of winter (JJA) conditions at Halley when PWV is below
0.92 mm, which corresponds to 23 days per year. A minimum measurement time
of 1.5 h is achieved using a 1400 K system temperature radiometer, reducing
to 0.5 h resolution for a 700 K radiometer. At lower measurement times the
trade-off is a modest reduction in altitude coverage and resolution, and
increased observation error.
As Fig. 7, but for different total measurement times
and a 60∘ zenith viewing angle.
Choice of emission line(s)
The results of zonal wind retrievals for simulated 12 h measurements of the
O3 231.28 GHz, O3 250 GHz, CO 230.54 GHz, and combined CO
230.54 GHz and O3 231.28 GHz emission lines, with a radiometer system
temperature of 1400 K and 60∘ zenith viewing angle are shown in
Fig. 13 and Table 1. Using either the single 231.28 GHz O3 line or the
pair of blended O3 lines centred at 249.79 and 249.96 GHz (see
Fig. 4) the altitude range, height resolution, and observation errors of the
retrievals are very similar for mean wintertime conditions. However in
summer the retrieval using the pair of blended lines covers higher
altitudes, reaching 0.05 hPa (∼ 69 km) with smaller
observation and total retrieval errors.
As Fig. 11, but simulated for different total
measurement times and radiometer system temperatures and under optimal
wintertime observing conditions at Halley where precipitable water
vapour (PWV) is in the lower quartile (below 0.92 mm).
As Fig. 7, but for retrievals using the O3
231.28 GHz, O3 250 GHz, CO 230.54 GHz, and combined CO 230.54 GHz and
O3 231.28 GHz atmospheric lines and a 60∘ zenith viewing
angle.
The retrieval using the CO 230.54 GHz emission line yields wind information
over 0.0009–0.03 hPa (∼ 97–73 km) in both summer and winter
conditions. The retrieval altitudes correspond to the higher CO mixing
ratios in the upper mesosphere and lower thermosphere (75–100 km) where CO
is mainly produced by ultraviolet photo-dissociation of carbon dioxide
(CO2). At the retrieval altitudes the CO linewidth is dominated by
Doppler (thermal) broadening. However the Doppler FWHM linewidth is at a
minimum with a reasonably constant value of 440 ± 10 MHz between 70
and 97 km. Doppler broadening increases above 97 km due to higher
temperatures in the lower thermosphere. Pressure broadening dominates, and
the CO linewidth rapidly increases, below 62 km in winter and below 69 km in
summer. Thus the wind retrieval is possible at high altitudes where the
minimum in the Doppler broadening characterises the altitude and where the
CO mixing ratio is sufficiently high, but the height resolution of the
retrieval is limited by the uniformity of the Doppler linewidth. At lower
altitudes where CO mixing ratios are low, due primarily to the oxidation
reaction with hydroxyl (OH) to form CO2 (Minschwaner et al., 2010), the
MR is below 0.8 and wind values in these regions should be interpreted with
caution as the information from the a priori becomes important. The CO wind
retrieval corresponds to an altitude of 85 ± 12 km where O3
analysis alone does not reliably retrieve wind information. The height
resolutions, estimated at ∼ 20 km in winter and
∼ 16 km in summer from the AVK FWHMs, are coarser than for the
O3 wind retrievals whereas the observation errors are smaller at
∼ 3 m s-1 in both winter and summer conditions at Halley.
Our simulated wind retrieval is comparable to the polar mesospheric wind
speeds above the South Pole determined with uncertainty ± 5 m s-1
by observing the CO line at 461 GHz (Burrows et al., 2007).
Wind retrievals using the combined CO 230.54 GHz and O3 231.28 GHz
observations provide the broadest coverage, 0.001–27 hPa (∼ 96–25 km) in winter and 0.001–20 hPa (∼ 96–27 km) in
summer. Over this range the height resolutions, observation errors, and
total errors are similar to those for the separate CO 230.54 GHz and O3
231.28 GHz retrievals, apart from at the overlapping altitudes
(∼ 75–80 km) in winter where the AVK FWHMs are as high as
32 km. Fine tuning the OEM wind retrieval for the combined analysis may
optimise the information retrieval from the two emission lines and eliminate
this artefact in the upper mesospheric data.