The infrared atmospheric band emission (a1Δg→X3Σg) of O2 observed near the wavelength of 1.27 µm has remarkable advantages in atmospheric remote sensing due to its bright signal and extended altitude coverage (Mlynczak et al., 2007). The enormous success of the Wind Imaging Interferometer (WINDII) (Shepherd et al., 2012), high-resolution Doppler imager (HRDI) (Ortland et al., 1996) and TIMED Doppler interferometer (TIDI) (Killeen et al., 2006), which measured winds in the upper mesosphere and lower thermosphere using Doppler shifts in visible airglow emission lines, stimulates interest in measuring wind and temperature from limb-viewing satellites using the 1.27 µm dayglow (Wu et al., 2018).

Ward et al. (2001) designed a high-sensitivity interferometer, WAMI, to provide simultaneous measurements of horizontal wind and rotational temperature by using the combination of a “strong” emission line group and a “weak” group of the O2(a1Δg) airglow. A similar instrument, MIMI, designed by York University, also takes advantage of strong and weak emission lines for dynamics and thermodynamics measurement. Both WAMI and MIMI are imaging, field-widened Michelson interferometers and the same measurement technique, known as Doppler Michelson imaging interferometry, is employed successfully by the WINDII instrument on NASA's UARS satellite (Shepherd et al., 2012). The observing strategy of using two sets of three emission lines (as shown in Fig. 1 of Ward et al., 2001) makes it a perfect approach for WAMI and MIMI to improve our knowledge of the wind and temperature of the lower thermosphere and middle atmosphere, as well as global distribution and transport of O3. In recent years, measuring wind and temperature in the planetary atmosphere of Mars and Venus, for example, was also proposed by using a 1.27 µm band emission of the electronically excited O2(a1Δg) state (Ward et al., 2002; Zhang et al., 2017). Closely following the WAMI concept, we recently proposed a near-space wind and temperature sensing interferometer (NWTSI) for simultaneous measurements of the atmospheric wind and temperature in the near-space from the limb-viewing satellite by observing the O2(a1Δg) dayglow near 1.27 µm (He et al., 2019).

The strategy of choosing two sets of three emission lines adopted by WAMI, MIMI and NWTSI is quite ingenious. Three emission lines of each group are relatively well separated and belong to different branches within the same band, which allows them to be optically isolated and ensures distinct temperature sensitivities. Additionally, the line strengths of the strong group and the weak one differ by about 1 order of magnitude, so their radiation intensities and absorption characteristics varying with altitude are available for covering a great extended altitude range from 45 to 100 km.

However, vibrational–rotational emission lines of the OH dayglow produced by the hydrogen–ozone reaction (H+O3→OH⚫+O2) overlap the infrared atmospheric band emission (a1Δg→X3Σg) of O2 near 1.27 µm (Maihara et al., 1993), which may potentially contribute to the increase in wind and temperature errors.

The main goal of this paper is to discuss the effect of OH emission on the wind and temperature measurements derived from the 1.27 µm O2 dayglow limb-viewing observations. The atmospheric radiance model is simulated using a line-by-line radiative transfer method. A brief description of the O2 dayglow and OH dayglow spectrum over the spectral region and altitude range of interest is provided. The forward simulation including instrument model and the method of four-point sampling of the interferogram, as well as sample results of measurement simulations, is presented. Inversion errors of wind and temperature measurements due to the effect of OH dayglow are presented and discussed. Here we report, to the best of our knowledge, the first consideration and discussion of the effect of OH dayglow on the temperature and wind measurements using the 1.27 µm O2 dayglow.

Molecular species in NWTSI's selected spectral range of 7820–7824 and 7908–7912 cm-1 other than O2 can affect NWTSI's wind and temperature measurements through absorption and emission. Limb spectral radiance of OH airglow is the most important interfering constituent for NWTSI, especially for the weak group detection, as shown in Figs. 3 and 5. Using etalon as the ultra-narrow filter significantly reduces but does not eliminate the influence from OH airglow. Therefore, the uncertainty in its mixing ratio surely contributes to the increase in wind and temperature errors. Note that while the fabrication of this ultra-narrow filter with a spectral width of 0.1 nm is feasible for current technical levels and engineering capability, it would be extremely challenging to monitor the changes in its width and central wavelength during the mission.

The wind velocity vw is measured as a phase shift δφ of the interferogram 6vw=c2πΔν0δφ, and phase φ can be calculated from 7φt=tan⁡-1J3J2. Fourier coefficients, J1, J2 and J3, also referred to as the apparent quantities, are related to any point k along a fringe interferogram I (Shepherd et al., 2012): 8J1=Imean=14∑k=14Ik,J2=12U∑k=14Ikcos⁡φklj,J3=12U∑k=14Iksin⁡φklj. Omitting the presence of OH emission will change the value of J2 and J3, which will inevitably lead to an inversion error for the wind measurement.

The error standard deviation of inverted wind due to the presence of OH emission is found from the following relation (He et al., 2019): 9σν=cJ22σJ32+J32σJ222πν0ΔJ22+J32, where σJ22 and σJ32 represent the variance of the Fourier coefficients J2 and J3 due to the lack of knowledge on OH emission.

The contribution of OH dayglow to the wind error is shown in Fig. 6a. The black curve represents omitting the presence of the OH emission. As can be seen, the wind error is about 1–2 m s-1 for altitudes below 70 km, climbing to greater than 8 m s-1 as the altitude increases from 80 to 90 km. The sensitivity of wind retrieval is weaker in the lower altitudes due to the lower OH volume emission rate. The degree of knowledge of OH dayglow is important for NWTSI retrieval. The blue short-dash–dot line and the red short-dash line in Fig. 6a represent the error deviation of inverted wind with OH dayglow knowledge of 80 % and 90 %, respectively. As can be seen, when OH dayglow is known to 80 %, the wind error is 0.3–0.5 m s-1 for the altitude range of 40–70 km; for OH dayglow knowledge of 90 %, the wind error decreases to 0.1–0.3 m s-1.

The error standard deviation of inverted temperature due to the presence of OH emission can be written as 10σT=ΔTT=RABTdTdRABσJ1A2+σJ1B2, where σJ1A2 and σJ1B2 represent the variance of the Fourier coefficients J1 of two emission lines A and B of the weak group of the O2 dayglow, and RAB is the ratio of the measured integral absorbances of this two lines, RAB=J1A/J1B.

A similar trend with the wind error is found for the temperature obtained from J1A and J1B: the temperature error is about 4–6 K for altitudes below 70 km and greater than 20 K for altitudes from 80 to 90 km (see the black curve in Fig. 6b). When OH dayglow is known to 80 %, the temperature error is 0.7–1.0 K for the altitude range of 40–70 km (see the blue short-dash–dot line in Fig. 6b); for OH dayglow knowledge of 90 %, the temperature error decreases to 0.3–0.5 K (see the red short-dash line in Fig. 6b).

By happy coincidence, the wind and temperature inversion for altitude above 70 km is irrelevant to the weak group. Due to their relative weak self-absorption effect, the weak emission lines are used only for wind and temperature measurement at low altitude. The three strong emission lines suffering little from self-absorption at relatively higher tangent heights take the place of the weak group for data inversion.

The performance analyses presented assume that the OH dayglow is known to a degree that results in meeting the threshold wind and temperature accuracies. The largest errors are obtained when not accounting for OH dayglow in the retrievals. In order to bring down the wind and temperature error to an acceptable level, OH dayglow knowledge with an accuracy of 80 %–90 % is required.

We have simulated and discussed the effect of OH dayglow on the wind and temperature measurements derived from the 1.27 µm O2 dayglow limb-viewing observations. We first calculated the O2 and OH dayglow spectrum over the spectral region and altitude range of interest using the line-by-line radiative transfer model and the photochemical model incorporating the most recent spectroscopic parameters, rate constants and solar fluxes. They show that the OH lines RR2.5e and RR2.5f are too close to the third weak emission line of the O2 dayglow near 7823 cm-1 (less than 0.05 nm), which will surely affect the spectral integral intensity of the O2 mission line. A brief description of the instrument model of NWTSI including the schematic drawing of limb-imaging geometry and the instrument concept is presented. The method of four-point sampling of the interferogram and sample results of measurement simulations are provided for both O2 and OH dayglow. It was apparent from the simulations that the interference fringe of OH dayglow is much stronger for pixels nearer the periphery of FPA, where the signal of the third weak emission line of the O2 dayglow near 7823 cm-1 is imaged. Inversion errors of wind and temperature measurements due to the effect of OH dayglow are presented and discussed in detail. The presence of OH dayglow as an interfering species decreases the NWTSI performance at all altitudes, with the largest impact for altitudes from 80 to 90 km. The effect of OH dayglow on NWTSI inversion can be reduced by improving OH dayglow knowledge. Accurate OH(v=8) concentrations (uncertainty level of 20 % or better) are required to help meet the wind and temperature accuracy requirements.