This paper presents a new dataset of nighttime atomic oxygen density [O], derived from OH(8–4) ro-vibrational band emissions, using a non-local thermal equilibrium model, with the aim of offering new insight into the atomic oxygen abundances in the mesopause region. The dataset is derived from the level-1 atmospheric background measurements observed by the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument aboard Envisat, with the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) measurements for the atmospheric background. Raw data are reprocessed into monthly zonal mean values in 10
The atomic oxygen density peaks at about 95 km and the highest values are in the range of 3–8
In the middle and upper atmosphere, atomic oxygen (O) is mainly produced by the photolysis of molecular oxygen and ozone, and transported downward by diffusion and mixing from the thermosphere to the mesopause. Its lifetime varies from over 1 week at 100 km to around 1 d at 80 km due to its increasing chemical loss rate with decreasing altitude
The measurement of atomic oxygen dates back to before the satellite era when the MLT region was explored by means of sounding rocket experiments, hosting resonance fluorescence instruments or mass spectrometers
However, these measurements lead to the development of photochemical models of the Earth's day- and nightglow, which enables the use of proxies of the atomic oxygen abundance obtained from satellite observations. Suitable proxies are airglow emissions (e.g.,
More recent measurements were conducted by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics (TIMED) satellite. The instrument detects
While various datasets are consistent in terms of the overall profile shape of derived [O] densities, some discrepancies still exist
To contribute another piece of information to the currently ongoing discussions, a new dataset derived from the OH nightglow observed by the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on the European Space Agency (ESA)'s environmental satellite (Envisat) during the years 2002 to 2012 is presented and discussed here. This dataset is particularly valuable in that it was obtained at the same time as the already-published SABER and SCIAMACHY data but from a different instrument with its own radiometric calibration. Emissions from OH(8–4) are used to obtain atomic oxygen abundances, which is a similar proxy to that provided by the SABER and SCIAMACHY OH measurements.
This paper is structured as follows: the second section provides a brief introduction to the instrument and data processing procedure, followed by a section describing the airglow modeling. The derived results are shown in the fourth section, including error analysis as well as latitudinal and temporal analysis. The next section investigates the validation of the dataset in a broad context, including comparisons with the SCIAMACHY dataset and other data sources, while the final section concludes the topic with an outlook on future expectations.
Schematic view of the GOMOS stellar occultation observations. The star transmission spectra are recorded in the central band of the instrument detector, while the atmospheric background radiation is imprinted in the upper/lower bands. The
The GOMOS spectrometer is one of nine instruments aboard Envisat. It is designed to monitor ozone profiles and other trace species using stellar occultation and atmospheric transmission measurements in limb-viewing mode
Latitudinal distribution of resampled GOMOS data available from 2002 to 2012. Color coding indicates the number of selected profiles for each monthly and zonally averaged 10
Monthly averaged spectrum from GOMOS (black solid line) for February 2004 at 40–50
The GOMOS data were processed with the processor version 6.01–2012. The resulting level-1b limb products have already been geolocated and calibrated
The raw data from level-1b limb products are first filtered with the corresponding auxiliary “quality flag” and “product confidence data”(PCD), which indicate the presence of bad pixels, saturation, cosmic rays, modulation, dark current, flat-field or vignetting correction, with only data in the normal status being kept. This is then followed by a geolocation-related selection, in which the data with ray-tracing errors are eliminated, and their star IDs and geolocation errors are restricted to within an acceptable range, as recommended by
Due to the nature of the stellar occultation observations, the tangent points of single vertical profiles diverge significantly and are not stationary in latitude–longitude locations. In the level-2 product, they are characterized by the obliquity
The archived level-1b data are signals recorded by the detector, which must be dynamically decoded to electrons and then converted to a physical unit of flux with wavelength-specific radiometric calibration factors. The star is a point source, and part of the stellar light is spread to the lower and upper bands, which is supposed to be totally imaged in the central band in an ideal case. Considering the contamination of star leakage and residual stray light, which are assumed to be constant with altitude, the averaged spectra from above 110 km are subtracted from each profile as background radiation. No airglow emissions are found above the region of 110 km in the GOMOS measurements. The subtraction is then followed by the individual “base” removal at each altitude layer, in which this “base” offset is the mean of residual noise of the emission lines. The processed data are resampled into monthly and zonally averaged 10
Atomic oxygen abundances, derived from GOMOS monthly zonal mean measurements of OH(8–4) airglow emissions for February 2006 at 10–20
The quality of the reprocessed spectra is evaluated by calculating the standard deviation (SD) of averaged spectra for each sample bin, supplemented by the SNR analysis. The calculations show that the mean SD for a typical sample bin in autumn at midlatitudes is around 2–4
The method to derive atomic oxygen abundance relies on the chemical equilibrium between ozone production and loss during nighttime. It is also applied for the retrieval of atomic oxygen abundances from SABER
OH airglow modeling parameters used in this study, where
Atmospheric background profiles of temperature, total density and ozone mixing ratio are taken from SABER measurements (v2.0–2016). The same latitude bins (
The inverse model applies a constrained global-fit approach following the formalism of
Applying the global fitting method to GOMOS level-1b limb products, a globally distributed time series [O] dataset is derived, along with other quantities. Shown in Fig.
The total uncertainty of the derived atomic oxygen densities not only depends on the measurement noise but also on the smoothing error as well as on uncertainties in forward model parameters and the background atmosphere input. The largest source of uncertainties is found in the forward model parameters. The influence of these uncertainties on the results is assessed through error propagation, by the perturbation of forward model parameters. The chemical reaction rate coefficient
At the altitude of 80–100 km, the effects of the smoothing error and measurement noise on the uncertainty are on the order of 0.5 % and 5 %, respectively. It is due to a properly chosen regularization in the retrieval procedure that the a priori information is negligible in the retrieval results. As part of a more in-depth look into the retrieval results, the averaging kernel and vertical resolution are investigated, as shown in Fig.
Latitude–altitude distribution of the zonal mean atomic oxygen density for 2007. Each row represents approximately a season. The data are linearly interpolated into a 1 km altitude grid for better illustration. The numbers in the subplots indicate the month of the year.
Atomic oxygen reveals a two-cell structure near 95 km at midlatitudes, which is most pronounced during the equinox seasons (Fig.
Temporal evolution of the vertical distribution of monthly zonal mean atomic oxygen densities for 20–40
In Fig.
Multiple linear regression analysis of vertically integrated, monthly mean atomic oxygen densities of 80–97 km for 20–30
A multiple linear regression analysis is applied to quantitatively analyze the longtime variations of the GOMOS [O] dataset. The monthly mean column density integrated from 80 to 97 km for 20–30
The variable
In Fig.
Summary of multiple linear regression analysis results of monthly mean atomic oxygen column densities integrated over 80–97 km for 20–30
Temporal evolution of radiance differences (in percentage) between GOMOS and SCIAMACHY at a tangent altitude of 86.5 km. The radiance is integrated over the wavelength of 930–935 nm. Negative numbers indicate that SCIAMACHY radiances are larger than those of GOMOS.
It could be considered to add an additional slope term in the harmonic fitting (Eq.
The SCIAMACHY instrument, another limb sounder aboard the Envisat satellite, observed OH emissions at various wavelengths from visible to infrared emissions
Latitude–altitude distribution of percentage differences between zonal mean atomic oxygen densities derived from GOMOS and SCIAMACHY OH(8–4) airglow emissions for 2007. Each row represents approximately a season. Negative numbers indicate that SCIAMACHY abundances are larger than those obtained from GOMOS. The data are linearly interpolated into a 1 km altitude grid. The numbers in the subplots indicate the month of the year.
Latitude–altitude distribution of percentage differences between zonal mean atomic oxygen densities derived from GOMOS OH(8–4) and SCIAMACHY OH(9–6) airglow emissions for 2007. The SCIAMACHY OH(9–6) are taken from
SCIAMACHY performed the OH airglow measurements in dark limb-viewing mode in the flight direction, with the recorded spectra always near a local solar time of 22:00 LT and a fixed altitude grid of 3.3 km. The OH(8–4) band observation is located in channel 5 with a spectral resolution of 0.54 nm. SCIAMACHY data version 8–2016 is adopted in this work. A continuous observation was performed during the entire lifetime of Envisat. The number of recorded profiles in one sample bin was around 100–300 before 2005 and significantly increased to 400–600 because of a change in instrument operations. SNRs of single profiles are normally on the order of 6 at peak altitudes and decrease to 1 at lower altitudes. After monthly zonal averaging, SNRs increase by 1 order of magnitude, and the mean noise level is around
Theoretically, the SCIAMACHY and GOMOS measurements should be identical in the same wavelength range. In practice, however, due to effects of various factors, such as instrument characteristics, radiometric calibration and fields of view, they do not fully conform with each other in terms of absolute radiance or instrument line shapes. In this study, the two data products are found to be consistent in terms of absolute radiance within
The same retrieval procedure is applied to the SCIAMACHY data. The differences between the atomic oxygen abundances from the two instruments are illustrated in Fig.
Comparison of monthly zonal mean atomic oxygen densities derived from hydroxyl airglow emissions observed by the GOMOS and SCIAMACHY instruments in various latitude bins for different months. SCIA-OH(9–6) represents the atomic oxygen dataset derived from the SCIAMACHY OH(9–6) band by
Comparison of atomic oxygen densities derived from various instruments and measurement techniques averaged for 20–40
Similarly, a latitude–altitude comparison of the GOMOS data with atomic oxygen obtained from SCIAMACHY OH(9–6) emissions
There are a number of
The datasets agree within their combined uncertainties in most cases. The absolute abundances are typically 4–6
GOMOS limb observations of the background atmosphere provide the opportunity to retrieve atomic oxygen abundances from hydroxyl nightglow emissions at the mesopause. A global nighttime [O] dataset is obtained by applying the OH modeling and retrieval method to the monthly zonal mean of GOMOS limb measurements, with the atmospheric background profiles of temperature, total density and ozone taken from the SABER measurements. Its uncertainty comes from the measurement noise (around 5 %), selected relaxation schemes and kinetic parameters in OH modeling (contributing around 20 % in total) and background atmosphere inputs, for example, atmospheric temperature and ozone (around 5 % to 20 %). The obtained profiles present an overall picture of the vertical distribution of atomic oxygen from 80 to 100 km. A temporal analysis of the profiles shows 11-year solar cycle effect tendencies as well as semiannual and annual variations, of which SAO is the most prominent.
The GOMOS data agree with the SCIAMACHY OH(8–4) measurements, with deviations typically smaller than 20 %. They are, on average, about 10 %–20 % lower than atomic oxygen data obtained from SCIAMACHY OH(9–6) observations. This might indicate that the collisional energy exchange between OH(
The GOMOS and SCIAMACHY data used in this study are available to the public at
Some rate coefficients used in this work are obtained by simultaneously fitting the OH airglow model to measured limb radiances of OH(9–6) and OH(8–5) bands. The measurements are taken from SCIAMACHY channel-6 radiances. The OH(9–6) band radiance is integrated over the wavelength range of 1378–1404 nm, and the OH(8–5) band is integrated over 1297–1326 nm. The selected parameters are adjusted in such a way that the ratio between the simulated radiances of the two bands is consistent with the ratio obtained from the measurements. Several cases with different rate coefficients or combinations being adjusted in the fitting are considered, as given in Table
The comparison of study cases with the applied rate coefficients being summarized. The adjusted parameters and their fitted values are marked in bold, while the coefficients taken from laboratory measurements are marked in italic.
The ratio of the integrated limb radiances between the OH(9–6) (1378–1404 nm) and OH(8–5) (1297–1326 nm) bands versus tangent altitude. The raw data (black dashed line) are taken from the SCIAMACHY channel-6 measurements. The fitted results (solid line) are obtained by applying the rate coefficients with respect to different cases.
QC processed the data, performed the analysis and drafted the manuscript. MK and YZ initiated the topic, provided insight and instructions, and discussed the results regularly. All authors contributed to the revision and improvement of the paper.
The authors declare that they have no conflict of interest.
Qiuyu Chen was supported in her work by the China Scholarship Council. The work of Yajun Zhu was supported by the 2017 Helmholtz–OCPC Programme and the International Postdoctoral Exchange Fellowship Program 2017. We also thank three anonymous referees for their valuable comments and suggestions.
The article processing charges for this open-access publication were covered by a Research Centre of the Helmholtz Association.
This paper was edited by William Ward and reviewed by three anonymous referees.