the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
SAO, AO, QBO, and Long-term trend of the peak OH airglow emission
Sheng-Yang Gu
Dong Wang
Liang Tang
Yafei Wei
Abstract. Based on the volume emission rate of the OH airglow observed by TIMED/SABER, we fitted the peak emission rate and the peak height of the OH airglow and analyzed the seasonal and interannual variations of both. The results show similar latitudinal variations in the semiannual oscillation (SAO) and annual oscillation (AO) of peak emission rate and peak height: the amplitude of SAO is greatest in equatorial regions and AO is greatest in mid-latitudes. For interannual variations, we find that OH airglow emission in equatorial regions is modulated by the quasi-biennial oscillation (QBO), while the QBO signal at other latitudes is much weaker than in equatorial regions and can be ignored. The QBO in OH airglow is consistent with the phase variation of the QBO in the tropical lower stratosphere (30 km), which is also consistent with the phase variation of the QBO in the migrating diurnal tide. As an important kinetic process affecting OH airglow emission, we suggest that the tides play an important role in the modulation of the OH airglow by the QBO. In addition, we have analyzed the relationship between peak OH airglow emission and solar activity. The results show a good correlation between peak emission rate and solar activity, with a correlation coefficient of 0.89, while peak height shows no significant solar cycle variation, with a correlation coefficient of −0.66. The modulation of peak emission rate by solar activity has significant latitudinal variation. The modulation effect is weakest in the equatorial region and greatest at mid-latitudes in both hemispheres.
Sheng-Yang Gu et al.
Status: open (until 22 Jun 2023)
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RC1: 'Comment on egusphere-2023-910', Anonymous Referee #1, 02 Jun 2023
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Summary
This paper presents an analysis of the peak altitude and peak emission rate of the hydroxyl (OH) emission rates observed for the past 20 years by the SABER instrument on the NASA TIMED satellite. SABER measures OH emission in two distinct spectral intervals, one centered at 2.0 um and the other at 1.6 um. The paper analyzes and presents results for the 1.6 um channel. The 20 years of SABER data enable comprehensive analysis of various temporal features that appear in the peak height and peak altitude of the OH emission. The analysis presented in the paper shows clear evidence for semi-annual and annual oscillations in the peak features and evidence for influence of the stratospheric quasi-biennial oscillation on the peak features. The results presented often confirm the results of previous papers regarding the presence of temporal features in the OH emission. The paper is clearly written.
The results in the paper are presented as ‘engineering’ analysis of the temporal variations in the OH emission. There is very little, if any, quantitative physics or chemistry given to explain the observed behavior. As an example, the discussion of solar variability is primarily of correlations between the OH variability and the F10.7 solar radio flux index. Solar variability affects temperature, composition, and dynamics. But the paper does not attempt to quantify which of these effects is dominant. The paper does not explain why there is strong latitude dependence in many of the analyses. However, the SABER dataset includes temperature, atomic oxygen, atomic hydrogen. These datasets could be explored along with model simulations (the WACCM model would be ideal for this) to put the results in context. In addition, although a secondary concern, the paper does not state why the peak altitude and peak emission rates are important physically. They are clearly markers for atmospheric variability. But is the variability important and why? One could imagine that since the reaction of H + O3 is the largest source of heating in the mesopause region, the variation in intensity and location of the OH emission means that the energetics of the mesopause are being altered significantly. Discussions such as this are necessary to place the results in a physical context as the reported variability largely reproduces prior works.
Recommendation
The recommendation is to reject the paper and invite submission of a new paper that contains much more detailed physical explanation of the observed OH behavior. This should include comparisons with the WACCM model and evaluations with other SABER data products. The paper should provide a quantitative explanation of features such as the latitudinal dependence of the semiannual and annual oscillations and should go into detail about the relative roles of temperature, chemistry, and dynamics in producing the observed variability.
A second recommendation is to evaluate the variability of the OH emissions on pressure surfaces and not on altitude. Studying variations at fixed altitudes mix variations in emission as the pressure surfaces rise and fall around the altitudes as the atmosphere warms and cools over the year and over the solar cycle. Pressure is the natural vertical coordinate of the SABER data.
Specific Comments
Title – the title contains the word ‘trend’ in relation to the peak OH emission. The word ‘trend’ typically implies looking at the long-term change of a parameter due to some forcing that is fundamentally changing the atmosphere such as increasing carbon dioxide concentrations. The original time series is analyzed in a way to remove variability (such as the AO, SAO, QBO, and solar cycle) and the linear trend of the residual is computed to derive a change (typically parameter per decade units). The paper does not appear to contain a trend analysis of this type. Please correct the title and the few places in the text where the word ‘trend’ occurs
Data use – An error was discovered in the SABER data for dates after December 16, 2019. A new version, v2.08 is available for data after that date. Please visit the SABER data web site to review and please discard all v2.0 data after Dec 16 2019.
Line 23-24. This sentence is an example of the lack of quantitative understanding of the airglow that comes across in the paper. The airglow intensity is not directly related to density and only indirectly related to temperature through the temperature dependence of the rate coefficient for the reaction of H and O3. The entire Introduction is full of generalities that makes one question whether the paper truly understands the physics of airglow generation including how and why it varies. A revised Introduction should directly address the physics/chemistry of OH formation and how it may vary, thus setting up the results and analysis with a model such as WACCM later in the paper.
Line 116-117 – please provide a reference citation to the vibrational states that contribute to each of the SABER OH channels.
Line 125 – the instantaneous field of view of the SABER instrument is 2 km. SABER samples the atmosphere at a much higher cadence than every 2 km and so it may appear that the vertical resolution is much higher. The paper needs to discuss the effects of the finite field of view on the ability to determine and analyze variations of the peak height and emission.
Line 136 – please provide a reference citation to the OMNI database and spell out the acronym.
Line 161, Section 3.1. The authors are encouraged to examine the data with Fourier techniques to see if other periodic features are evident.
Lines 181 to 200 – Any new manuscript should include explanations of the origins of the AO, SAO, and QBO, and how these influence the OH emissions. In particular, the AO should be primarily driven by the annual variation of earth-sun distance. So there is an annual cycle of solar radiation along with varying solar radiation on an 11 year cycle. Does any of the 11 year cycle ‘alias’ into the annual cycle? Could the Fourier techniques mentioned above help sort out different cyclic variations?
Line 240-250 – please explain physically how the QBO in the stratosphere modulates the OH emission in the mesosphere.
Line 259-270. SABER has temperature, atomic oxygen, atomic hydrogen, and ozone data. These could be analyzed in concert with the OH data and WACCM model results to produce a complete picture of the relative importance of temperature, chemistry, and dynamics in producing the observed variations in the OH emission.
Line 300- Instead of using the F10.7 proxy, it is suggested to use the actual solar irradiance measured by the SORCE and SEE instruments over the past 20-plus years. Focus on the wavelength regions that drive most of the heating in the mesopause region. This may provide a much better result than using F10.7.
Citation: https://doi.org/10.5194/egusphere-2023-910-RC1
Sheng-Yang Gu et al.
Sheng-Yang Gu et al.
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