We use TOMCAT, a 3-dimensional (3D) offline chemical transport model (CTM) forced by two different meteorological reanalysis data sets (ERA-Interim and ERA5) from the European Centre for Medium-Range weather Forecasts (ECMWF) to analyse seasonal behaviour and long-term trends in stratospheric ozone and mean age of air. The model-simulated ozone variations are evaluated against two observation-based data sets. For total column ozone (TCO) comparisons, we use the Copernicus Climate Change Service (C3S) data (1979–2019), while for ozone profiles we use the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set (1984–2019). We find that the CTM simulations forced by ERA-Interim (A_ERAI) and ERA5 (B_ERA5) can both successfully reproduce the spatial and temporal variations in stratospheric ozone. Also, modelled TCO anomalies from B_ERA5 show better agreement with C3S than A_ERAI, especially in Northern Hemisphere (NH) mid latitudes, except that it gives somewhat larger positive biases (> 15 DU, Dobson units) during winter–spring seasons. Ozone profile comparisons against SWOOSH data show larger differences between the two simulations. In the lower stratosphere, ozone differences can be directly attributed to the representation of dynamical processes, whereas in the upper stratosphere they can be directly linked to the differences in temperatures between ERAI and ERA5 data sets. Although TCO anomalies from B_ERA5 show relatively better agreement with C3S compared to A_ERAI, a comparison with SWOOSH data does not confirm that B_ERA5 performs better at simulating the variations in the stratospheric ozone profiles. We employ a multivariate regression model to quantify the TCO and ozone profile trends before and after peak stratospheric halogen loading in 1997. Our results show that, compared to C3S, TCO recovery trends (since 1998) in simulation B_ERA5 are significantly overestimated in the Southern Hemisphere (SH) mid latitudes, while for A_ERAI in the NH mid latitudes, simulated ozone trends remain negative. Similarly, in the lower stratosphere, B_ERA5 shows positive ozone recovery trends for both NH and SH mid latitudes. In contrast, both SWOOSH and A_ERAI show opposite (negative) trends in the NH mid latitudes. Furthermore, we analyse age of air (AoA) trends to diagnose transport differences between the two reanalysis data sets. Simulation B_ERA5 shows a positive AoA trend after 1998 and somewhat older age in the NH lower stratosphere compared to A_ERAI, indicating that a slower Brewer–Dobson circulation does not translate into reduced wintertime ozone buildup in the NH extratropical lower stratosphere. Overall, our results show that models forced by the most recent ERA5 reanalyses may not yet be capable of reproducing observed changes in stratospheric ozone, particularly in the lower stratosphere.

Accurate quantification of long-term trends in stratospheric ozone can be challenging due to their sensitivity to natural variability, the quality of the observational datasets, and non-linear changes in forcing processes as well as the statistical methodologies. Multivariate linear regression (MLR) is the most commonly used tool for ozone trend analysis; however, the complex coupling in many atmospheric processes can make it prone to the issue of over-fitting when using the conventional ordinary-least-squares (OLS) approach. To overcome this issue, here we adopt a regularized (ridge) regression method to estimate ozone trends and quantify the influence of individual processes. We use the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) merged dataset (v2.7) to derive stratospheric ozone profile trends for the period 1984–2020. Besides SWOOSH, we also analyse a machine-learning-based satellite-corrected gap-free global stratospheric ozone profile dataset from a chemical transport model (ML-TOMCAT) and output from a chemical transport model (TOMCAT) simulation forced with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis. For 1984–1997, we observe smaller negative trends in the SWOOSH stratospheric ozone profile using ridge regression compared to OLS. Except for the tropical lower stratosphere, the largest differences arise in the mid-latitude lowermost stratosphere (>4 % per decade difference at 100 hPa). From 1998 and the onset of ozone recovery in the upper stratosphere, the positive trends estimated using the ridge regression model (∼1 % per decade near 2 hPa) are smaller than those using OLS (∼2 % per decade). In the lower stratosphere, post-1998 negative trends with large uncertainties are observed and ridge-based trend estimates are somewhat smaller and less variable in magnitude compared to the OLS regression. Aside from the tropical lower stratosphere, the largest difference is around 2 % per decade at 100 hPa (with ∼3 % per decade uncertainties for individual trends) in northern mid-latitudes. For both time periods the SWOOSH data produce large negative trends in the tropical lower stratosphere with a correspondingly large difference between the two trend methods. In both cases the ridge method produces a smaller trend. The regression coefficients from both OLS and ridge models, which represent ozone variations associated with natural processes (e.g. the quasi-biennial oscillation, solar variability, El Niño–Southern Oscillation, Arctic Oscillation, Antarctic Oscillation, and Eliassen–Palm flux), highlight the dominance of dynamical processes in controlling lower-stratospheric ozone concentrations. Ridge regression generally yields smaller regression coefficients due to correlated explanatory variables, and care must be exercised when comparing fit coefficients and their statistical significance across different regression methods. Comparing the ML-TOMCAT-based trend estimates with the ERA5-forced model simulation, we find ML-TOMCAT shows significant improvements with much better consistency with the SWOOSH dataset, despite the ML-TOMCAT training period overlapping with SWOOSH only for the Microwave Limb Sounder (MLS) measurement period. The largest inconsistencies with respect to SWOOSH-based trends post-1998 appear in the lower stratosphere where the ERA5-forced model simulation shows positive trends for both the tropics and the mid-latitudes. The large differences between satellite-based data and the ERA5-forced model simulation confirm significant uncertainties in ozone trend estimates, especially in the lower stratosphere, underscoring the need for caution when interpreting results obtained with different regression methods and datasets.

Based on the resonance fluorescence scattering mechanism, a narrowband sodium (Na) lidar can measure temperature and wind in the mesosphere and lower thermosphere (MLT) region. By using a narrowband spectral filter, background light noise during the day can be suppressed, allowing for continuous observations. To obtain full-diurnal-cycle temperature and wind measurement results, a complex and precise retrieval process is required, along with necessary corrections to minimize measurement errors. This paper introduces the design of a data acquisition unit for three frequencies in three directions of the Na lidar system in the Chinese Meridian Project (Phase II) and investigates the calibration and retrieval methods for obtaining diurnal temperature and horizontal wind in the MLT region, using a Na Doppler lidar with Faraday anomalous dispersion optical filter (FADOF). Furthermore, these methods are applied to observations conducted by a Na lidar in Beijing, China. The wind and temperature results over full diurnal cycles obtained from the all-solid-state Na Doppler lidar are reported for the first time and compared with temperature measurements from satellite, as well as wind observations from a meteor radar. The comparison demonstrates a reasonable agreement between the results, indicating the rationality of the lidar-retrieved results and the feasibility and effectiveness of the data correction and retrieval method.

Resonance fluorescence scattering is the physical mechanism with which lidar detects atmospheric metal layers. The resonance fluorescence scattering cross section is an important parameter for lidar data processing. In this work, the resonance fluorescence backscattering cross sections of most detectable metal atoms and ions in the atmosphere were calculated. The calculated maximum backscattering cross section of Na at the D₂ line is 7.38 × 10⁻¹⁷ m²/sr; K at the D₁ line is 7.37 × 10⁻¹⁷ m²/sr; Fe at the 372 nm line is 7.53 × 10⁻¹⁸ m²/sr; Fe at the 374 nm line is 6.98 × 10⁻¹⁸ m²/sr; Fe at the 386 nm line is 3.75 × 10⁻¹⁸ m²/sr; Ni at the 337 nm line is 4.05 × 10⁻¹⁸ m²/sr; and Ni at the 341 nm line is 2.05 × 10⁻¹⁷ m²/sr; Ca is 3.06 × 10⁻¹⁶ m²/sr; Ca⁺ is 1.12 × 10⁻¹⁶ m²/sr. The influence of the laser linewidth on the effective scattering cross section was discussed. If the laser linewidth is lower than 2 GHz to detect Na, the laser center frequency locked at the D_2a line is a better option than the D₂ line in order to obtain greater signals. If an unlocked lidar is used to detect Na, the frequency at D_2a should be used as the laser center frequency when the effective scattering cross section of Na was calculated, because the absorption cross section of Na atom has two local maxima. This work proposes a quantifiable comparative method for assessing the observation difficulty of different metal particles by comparing their relative uncertainties in lidar observation. It is assumed that under the same observation conditions, the detectability of different metal atoms and ions is compared. Using Na as a basis for comparison, the relative uncertainty of Ni at 337 nm is the highest, about a factor of 21 larger than that of Na, indicating that it is the most difficult to be detected. The purpose of this work is to present a quantifiable comparison method for the detection difficulty of the metal particles by lidar in the middle and upper atmosphere, which has great significance for the design of the lidar system.

Based on the full-diurnal-cycle sodium (Na) lidar observations at Beijing (40.41^∘ N, 116.01^∘ E), we report pronounced downward extensions of the Na layer bottomside to below 75 km near mid-December 2014. Considerable Na atoms were observed even as low as ∼ 72 km, where Na atoms are short-lived. More interestingly, an unprecedented Na density of ∼ 2500 atoms cm⁻³ around 75 km was observed on 17 December 2014. Such high Na atoms concentration was 2 orders of magnitude larger than that normally observed at the similar altitude region. The variations of Na density on the layer bottom were found to be accompanied by warming temperature anomalies and considerable perturbations of minor chemical species (H, O, O₃) in the upper mesosphere. Different from the previous reported metal layer bottom enhancements mainly contributed by photolysis after sunrise, these observational results suggest more critical contributions were made by the Na neutral chemical reactions to the Na layer bottom extensions reported here. The time–longitudinal variations of background atmospheric parameters in the upper mesosphere and stratosphere from global satellite observations and ERA reanalysis data indicated that the anomalous structures observed near the lidar site in mid-December 2014 were associated with planetary wave (PW) activities. The anomalies of temperature and O₃ perturbation showed opposite phase in the altitude range of 70–75 and 35–45 km. This implied that the vertical coupling between the mesosphere and stratosphere, possibly driven by the interactions of PW activities with background atmosphere and modulation of gravity wave (GW) filtering by stratospheric wind, contributed to the perturbations of background atmosphere. Furthermore, the bottom enhancement on 17 December 2014 was also accompanied by clear wavy signatures in the main layer. The strong downwelling regions are likely due to the superposition of tide and GW, suggesting the wave-induced adiabatic vertical motion of the air parcel contributed greatly to the formation of the much stronger Na layer bottom enhancement on 17 December 2014. These results provide a clear observational evidence for the Na layer bottom response to the planetary-scale atmospheric perturbations in addition to tide and GW through affecting the chemical balance. The results of this paper also have implications for the response of the metal layer to vertical coupling between the lower atmosphere and the mesosphere.