We consider 5 years of spectrometer measurements of OH(6–2) and O
Observations of OH and O
Routine observations of OH(6–2) and O
In this paper, we describe the results from the spectrometer for the 5-year
period from September 2001 until August 2006, when it ceased operation. We
compare the spectrometer OH(6–2) and O
A detailed interpretation of ground-based passive airglow observations is often limited by the lack of information about the actual emission height, which may change with time of day and time of year. Younger et al. (2015) have described a new technique for determining the height of a constant density surface at altitudes of 78–85 km using meteor radar data. In this work, we compare 1 year of spectrometer OH(6–2) and SABER temperatures using the assumption that the OH(6–2) emission height follows a constant density surface using meteor-radar-derived neutral density measurements. This allows us to gain a better understanding of this aspect of our observations and significantly improves the correlation between the two observations.
The BP field site is home to several instruments for investigating the
atmosphere. In addition to the Czerny–Turner spectrometer and meteor radar,
which we describe below, the instruments of most interest to this work are
the 3FP and the Aerospace Imager. The 3FP has been described by
Woithe (2000), Ding et al. (2004), Reid and Woithe (2005, 2007), and Reid et
al. (2014). It measures the intensity of the O(
The spectrometer is a high-throughput, modified Czerny–Turner spectrometer
fitted with long, Fastie-type, curved entrance slits. The detector is a
1024
OH temperature estimates were calculated using the standard “ratio of lines” method from the (6–2) OH band. The J constants for each OH line were obtained from Mies (1974), the Einstein A coefficients for each OH line from Langhoff et al. (1986), the rotational terms for each OH transition from Coxon and Foster (1982), and the nominal centre wavelengths (in nm) of each transition OH line emission were obtained from Greet et al. (1998).
Due to very low intensity, the P1(6) and P1(7) lines proved too difficult to definitively characterise in general, so they (and temperature estimates based on them) were omitted from the process. During the analysis, it was also observed that jitter on the P1(5) line due to sampling resolution and low intensity was unacceptably high compared to P1(2), P1(3), and P1(4) and that consequently temperatures calculated using P1(5) often differed wildly from the others. As a result, the “average” OH temperature uses the temperatures derived from the P1(2) : P1(3) and P1(2) : P1(4) ratios.
Two different methods were used to estimate the intensity of the OH lines. The simplest, referred to as the “height” method, used the peak's maximum recorded value. The alternative, dubbed the “intensity” method, used an integrated intensity under the peak. Both methods yield similar results although the height method may be slightly better if the spectrum is a little noisy. The main problem with the intensity method is that it is hard to positively identify the integration bounds at times due to the limited pixel resolution relative to the peak widths, and this can lead to integration inaccuracies.
Unlike the OH temperatures there is no analytical method for calculating
temperatures from the O
The meteor radar used in this work is described by Holdsworth et al. (2004a). It is an ATRAD meteor detection radar (MDR) and operated at Buckland Park between 16 July 2002 and 25 January 2004 before being relocated to Darwin in northern Australia. This radar operates at a frequency of 33.2 MHz, with a peak power of 7.5 kW, has one “all-sky” transmit antenna, and uses a five-antenna interferometer on reception to detect meteor echoes in the 70 to 110 km height range. For the observations we discuss here, typical daily height-resolvable underdense meteor counts at BP varied between 9000 and 14 000 per day over the year, and usable winds were determined between heights of 75 and 100 km. A 55 MHz meteor radar similar to that described by Reid et al. (2006) commenced operation at BP at the beginning of 2006, but the spectrometer ceased operation soon after, and there are limited coincident measurements from the two instruments.
Note that we do not attempt to derive temperatures from the meteor radar measured diffusion coefficients here, as for example, described in Holdsworth et al. (2006), as there are significant limitations in this approach (see Lee et al., 2013; Younger et al., 2014). However, Lee et al. (2016) have described a new method of estimating temperatures near the mesopause region using meteor radar observations by calibrating their meteor radar against Aura MLS temperatures. This approach looks promising and has some similarities to the approach we describe below in Sect. 4.3.1.
To further investigate our temperature results, we considered Aura MLS and TIMED SABER observations. Two important aspects of the satellite measurements to be considered in our comparisons are the vertical resolution and the known bias. The vertical resolution (the averaging kernel width) of the MLS at 0.46 Pa is about 14–15 km, and the bias is cold by up to 2 K (Schwartz et al., 2008). The vertical resolution of SABER in the mesopause region is superior at about 2 km (Remsberg et al., 2003), and this motivates our use of these measurements in preference to the Aura MLS measurements in Sect. 4.3.2 below.
We accepted satellite measurements within a 500 km radius of Buckland Park and a time difference for the satellite and ground-based measurements of 30 min (that is, satellite measurements were only used if they are preceded or followed by a ground-based measurement within 30 min). The latter was based on the findings of French and Mulligan (2010). However, we do note that in their study, no substantial change in bias between satellite and ground-based measurements was detected when the time difference between ground and satellite observations was varied between 15 min and 8 h.
Top: the OH(6–2) temperature plotted as a function of time of day and time of year for a superposed year. The equinoxes are indicated by dotted lines, the solstices by dashed lines. Minimum temperatures are observed in summer, with a general increase in temperature between the equinoxes. During this period, the temperatures are greatest at dawn and dusk. There is a tendency for the temperature to be greatest between the autumnal equinox and the vernal equinox, with a semi-annual variation in temperature, which is strongest late in the night, although there is a mid-winter maximum present as well. Bottom: as for top panel but for the OH(6–2) emission intensity.
Top: the O
Initially, we applied a Gaussian weighting kernel to the satellite-derived
temperatures as per empirically determined weighting functions for the OH(6–2) (Baker and Stair, 1988) and the O
Figures 1 and 2 show the temperatures and intensities through the night and
through the year for the OH and O
In the OH temperatures, minimum temperatures are observed in summer, with a general increase in temperature between the autumnal and vernal equinoxes. During this period, the temperatures are greatest at dawn and dusk. There is a tendency for the temperature to be greatest at equinox, resulting in a semi-annual variation in temperature, which is strongest late in the night, although there is a mid-winter maximum present as well. The OH intensity tends to be a minimum in the middle of the night throughout the year, with a tendency to a maximum around dusk. There is a general brightening between day 120 and day 250, but with a 30 to 40-day periodicity also evident during this interval.
In the O
To quantify the variation of the temperature and intensity data through the night, we follow Reid et al. (2014) and divide the period between 18:00 and 06:00 LT into four 3 h blocks of data. We then analyse each 3 h data block using a Lomb–Scargle periodogram to determine the dominant periods present. The significant periods identified in the Lomb periodograms are then used in a harmonic analysis to determine the mean amplitudes and phases of these periods through the period of observation and to estimate the geophysical variation through the night. We also calculate the Lomb–Scargle periodogram for the entire night.
This analysis indicates that OH temperatures are dominated by an annual
oscillation (AO), while in the O
Results of the harmonic fits to the spectrometer OH(6–2) and O
When the composite years for the four 3 h blocks are examined for the
nightly OH variation, we see a change from a predominately annual variation
at the beginning of the night to an annual variation with a semi-annual
variation superposed on it. In the case of O
Only the AO and SAO are significant at the 99 % level through the entire
night, and our results for harmonic fits to the entire observational period
for these periods are summarised quantitatively in Table 1. In the OH, the
SAO maximises in the autumn and the AO in the winter. The SAO takes a value
of 2.1 K and the AO a value of 6.6 K. In the case of the O
Comparison between coincident Aura MLS and TIMED SABER and
spectrometer temperatures. The Aura MLS results are for 8 August 2004 to
1 August 2006 and the TIMED SABER results for 26 January 2002 to
1 August 2006.
Top: the wavelet power spectrum for the OH(6–2) temperature (top)
with the time series of 30-day averaged values and their standard
deviations (bottom) and the corresponding Lomb periodogram (right). The
periods of the SAO, AO, and QBO are indicated by the horizontal grey lines.
The time series is dominated by the AO, which is consistent across the
observational period in amplitude and phase. The SAO is present in the second
half of the observational period and the QBO at its centre. Bottom: as for
top panel, but for the O
To further examine the variation of the harmonic components through time, we
applied a wavelet spectral analysis to the time series of the 30-day average
temperatures (Torrence and Compo, 1998). The results are shown in Fig. 3
(bottom panel; as for Fig. 3 (top panel), but for the O
Figure 4 shows the results of a fit of the AO and SAO only for the OH(6–2)
and O
Top: a comparison of AO and SAO harmonic fits to the OH(6–2)
rotational temperature and intensity from the spectrometer and the
corresponding OH(8–3) intensity from the 3FP for the period 2001 to 2007.
Bottom: as for top panel, but for the O
Table 2 gives a summary of the spectrometer OH(6–2) and O
The MLS data have been selected according to the v3.3 status, quality, threshold, and convergence values recommended by the MLS Science Team (Livesey et al., 2011). The Aura MLS mean temperatures weighted according to the estimated OH(6–2) profile shown in Table 2 are lower than the spectrometer mean, with a difference of 7.5 K, but the results agree to within the experimental error. There is generally good agreement between the amplitudes and phases of the AO as measured by the two instruments, but not to within the experimental error for the SAO. We have included the temperatures of the Aura MLS corresponding to the 0.46 Pa level in this table, and these agree with the spectrometer observations to within the experimental error for the mean, the AO, and the SAO. We will further discuss the significance of this below.
The O
OH and O
Table 2 also gives a summary of the same spectrometer temperatures compared
to the coincident measurements from TIMED SABER. In contrast to the Aura MLS
result, this comparison indicates that the mean spectrometer OH(6–2)
temperatures are lower than the TIMED SABER temperatures, being 1.7 and
2.1 K lower than the OH 1.6
Like the Aura MLS temperatures, the O
As we have noted above, there have been many ground-based observational studies of midlatitude airglow temperatures in the Northern Hemisphere (e.g. She and Lowe, 1998; Bittner et al., 2002; López-González et al., 2007). Similar studies in the Southern Hemisphere are rarer (e.g. Buriti et al., 2004). The most important of these for the present work is that of G08, which used coincident data from the Aerospace Buckland Park airglow imager. Table 3 summarises the OH(6–2) temperature results from the present study, along with those from G08, who also include corresponding results from the TIME-GCM (Roble and Ridley, 1994). For this table, the periods of BP spectrometer observation times have been matched to those of G08. There is generally good agreement between these measurements, but not always to within the experimental uncertainties. However, we can summarise the results by saying that the mean temperature is in the range of 188 to 192 K with a mean of 190 K, the AO is consistently about 3 times larger than the SAO and maximises in winter, and the SAO takes its first maximum in autumn.
Table 3 also summarises the O
Table 3 also summarises TIMED SABER results from Xu et al. (2007) and Huang
et al. (2006). Xu et al. (2007) used TIMED SABER observations to examine
long-term variations in zonal mean temperatures in the years 2002 to 2006.
Their results indicate that the mean was 195 K for 86 km at 40
Examples of the comparison between the spectrometer OH temperatures
and the Aura MLS temperatures. The panels on the left show the correlation
values between the spectrometer and Aura MLS temperatures for the 0.46 Pa (top)
and the 0.22 Pa (bottom) retrieval levels. The blue and red lines
indicate lines of best fit made assuming all experimental errors are in the
Aura MLS and the spectrometer, respectively. The green line indicates the
In the case of the OH emission shown in Fig. 4, a strong correlation between
the temperature and intensity is typical of other studies. For example,
Shepherd et al. (2007) looked at winter results from Resolute Bay
(74.7
In the case of the O
Thus far we have assumed that the OH emission occurred at a fixed and known geometrical height. In the next two sections, we consider whether we can improve on this assumption, firstly by looking for the height of the minimum residual between the spectrometer and the satellite temperatures for different satellite pressure heights and then by interpolating the SABER temperatures to a fixed density surface derived from meteor radar observations.
The simplest Gaussian averaging kernel we have applied to the satellite data
assumes that the OH layer is at a fixed altitude. However, when we use the
assumption of a fixed height for the OH emission and plot the residual
temperature (ground-based – satellite), we find that the residuals for the
Gaussian-weighted satellite data show a seasonal behaviour, suggesting that
the mean emission height is changing throughout the year. When we examine the
Lomb–Scargle periodograms of the residuals for temperatures at a series of
constant pressure surfaces derived from the Aura MLS observations using the
same conditions for coincidence as described earlier, we find that the
residual minimises for MLS temperature estimates at the native retrieval
level of 0.46 Pa (
We have included the 0.46 Pa result in Table 2 for the period between 8 August 2004 and 1 August 2006 as an example. The 0.46 Pa Aura MLS and spectrometer OH(6–2) results agree quite closely, with the mean of the former being 1.4 K lower than the latter. This difference is consistent with the bias reported for MLS (see Livesey et al., 2011). We note that there is arguably better agreement between the OH spectrometer result and the Aura MLS temperature at the 0.46 Pa retrieval level, with the AO and SAO amplitudes and phases at the 0.46 Pa retrieval level in closer agreement with the spectrometer results than those from the fixed weighting function.
Irrespective of the actual level of best agreement, the behaviour of these residuals suggests that the OH temperatures measured by the spectrometer are more closely associated with the layer being tied to a constant pressure surface rather than a fixed geometric height. This would be consistent with the density of atomic oxygen being tied to the background density (see, e.g., Marsh et al., 2006) and with the model results for the hydroxyl layer of Grygalashvyly et al. (2014).
Additional information about the OH emission heights may be obtained by
calibrating meteor radar results using Aura MLS (or SABER) densities, as
Younger et al. (2015) have shown. They showed that a constant density surface
may be determined in the 78 to 85 km height region from vertical profiles of
meteor trail radar echo decay times. Additional work by
P. J. Younger (personal communication, 2016) indicates that a second upper
constant density surface between 95 and 100 km may be determined. With some
assumptions, this allows the constant density surfaces to be determined
independently of satellite measurements after “calibration” for a
particular meteor radar wavelength. While we do not have meteor radar
observations for the entire period of the spectrometer observations, we do
have coincident 33.2 MHz meteor radar,
The geometric heights for 10-day average fixed density surfaces for
14 May 2002 to 28 January 2004 determined from the meteor radar. This diagram
has been prepared using the difference in the estimate of the geometric
height of two constant density surfaces to calculate the density scale
height,
Two examples of the comparison between the spectrometer OH
temperatures and the SABER temperatures interpolated to constant density
surfaces. The panels on the left show the correlation values between the
spectrometer and SABER temperatures for two density surfaces. The blue and
red lines indicate lines of best fit made assuming that all experimental
errors are in the SABER and spectrometer, respectively. The green line
indicates the
First, we weight the SABER temperatures with a Gaussian emulating the OH VER
(which is centred on interpolated heights of “fixed” density and has a full
width at half minimum (FWHM) of 8 km). Then we use two methods to evaluate
the density scale height,
Comparison between coincident TIMED SABER and spectrometer temperatures for the period 16 July 2002 to 25 January 2004 when the meteor radar data were available to calculate the neutral density. N is the number of points in each sample. See text for further details.
The meteor data used in this work were acquired before the development of the phase calibration technique described by Holdsworth et al. (2004b) which uses the meteor echoes themselves to calibrate the radar. A post-statistics approach was used to improve the phase characteristics of the meteor returns, but because the radar was being used in a variety of different experimental modes during this period, it likely that the data are not of the quality of more recent meteor radar observations, and 10-day averages were used to determine the fixed density contours. These are shown in Fig. 6. Inspection of this figure indicates that variations in geometrical height of the constant density surfaces are generally less than 2 km on this timescale.
Figure 7 shows two examples of the comparison between the spectrometer and
SABER temperatures on constant density surfaces. The density surface in the
upper panels corresponds exactly to the lower curve height estimates, and the
one in the lower panels corresponds to a surface interpolated between the
lower and upper curves. Using the
The correlation coefficient and the mean discrepancy between the spectrometer OH temperatures and the SABER temperatures when the latter are interpolated to a series of constant density levels. See text for further details.
To extend the intercomparison beyond a simple correlation, we harmonically
analysed the OH data as we have done above. The results are shown in Table 4.
This table shows a comparison between the spectrometer OH results for the
period of the meteor radar observations, along with the coincident SABER
results, both for the meteor radar determined constant density surfaces
(“SABER MDR”) and for the 1.6 and 2.0
It is pleasing that the mean geometric height for the OH emission determined
here (
OH(6–2) and O
OH(6–2) temperatures measured in the present work agree well with coincident
measurements, with TIME-GCM results, and with WINDII observations reported
previously by Gelinas et al. (2008). Our O
We used Aura MLS and TIMED SABER results to compare with our spectrometer results. We find good agreement between our OH(6–2) temperature measurements and OH weighted Aura MLS results for the mean, AO, and SAO, all agreeing to within the experimental uncertainty, with the suggestion of a downward bias in the Aura MLS mean temperature. We find better agreement between the techniques when we use the Aura MLS results from the 0.46 and 0.22 Pa retrieval levels where the residuals between the techniques minimise and the correlation coefficients maximise.
Our spectrometer O
In the case of the SABER results, we find SABER 1.6 and 2.0
We used the SABER temperature results to show that the OH airglow emission heights appear to follow meteor-radar-derived constant density surfaces, and even at the relatively coarse sampling resolution of 10 days, using this to calculate the emission height significantly improves the correlation between the spectrometer OH and the SABER temperatures. Based on more recent meteor observations, this suggests that its application to more recent meteor radars would offer a way of better determining the actual emission height over time periods of 6 h or less.
Aura MLS data are available from
ATRAD Pty Ltd partially funded this work through the involvement of Iain M. Reid, Jonathan M. Woithe, and Joel P. Younger. An ATRAD meteor detection radar was used for the meteor observations used here.
Funding for this research was provided by the Australian Research Council
grants A69943065, DP0450787, DP0878144, and DP1096901, by the Adelaide
University ARC Small Grants Scheme, and by ATRAD Pty Ltd. The IDL wavelet analysis software was provided by C. Torrence and
G. Compo, and is available at