Assessment of the quality of ACE-FTS stratospheric ozone data

For the past 17 years, the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) instrument on the Canadian SCISAT satellite has been measuring profiles of atmospheric ozone. The latest two operational versions of the level 2 ozone data are versions 3.6 and 4.1. This technical note characterizes how both products compare with correlative data from other limb-sounding satellite instruments, namely MAESTRO, MLS, OSIRIS, SABER, and SMR. In general, v3.6, with respect to the other instruments, exhibits a smaller bias (which is on the order of ~3 %) in the middle stratosphere than v4.1 (~2–9 %), however the bias exhibited in the v4.1 data tends to be more stable, i.e. not changing significantly over time in any altitude region. In the lower stratosphere, v3.6 has a positive bias of about 3–5 % that is stable to within ±1 % dec−1, and v4.1 has a bias on the order of −1 to +5 % and is also stable to within ±1 % dec−1. In the middle stratosphere, v3.6 has a positive bias of ~3 % with a significant negative drift on the order of 0.5–2.5 % dec−1, and v4.1 has a positive bias of 2–9 % that is stable to within ±0.5 % dec−1. However, the v4.1 bias in the middle stratosphere is reduced to 0–5 % after being corrected for field-of-view modelling errors. In the upper stratosphere, v3.6 has a positive bias that increases with altitude up to ~16 % and a significant negative drift on the order of 2–3 % dec−1, and v4.1 has a positive bias that increases with altitude up to ~15 % and is stable to within ±1 % dec−1.

Smoke-charged vortices in the stratosphere generated by wildfires and their behaviour in both hemispheres: comparing Australia 2020 to Canada 2017

The two most intense wildfires of the last decade that took place in Canada in 2017 and Australia in 2019–2020 were followed by large injections of smoke into the stratosphere due to pyro-convection. After the Australian event, Khaykin et al. (2020) and Kablick et al. (2020) discovered that part of this smoke self-organized as anticyclonic confined vortices that rose in the mid-latitude stratosphere up to 35 km. Based on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations and the ERA5 reanalysis, this new study analyses the Canadian case and finds, similarly, that a large plume had penetrated the stratosphere by 12–13 August 2017 and then became trapped within a mesoscale anticyclonic structure that travelled across the Atlantic. It then broke into three offspring that could be followed until mid-October, performing three round-the-world journeys and rising up to 23 km. We analyse the dynamical structure of the vortices produced by these two wildfires and demonstrate how the assimilation of the real temperature and ozone data from instruments measuring the signature of the vortices explains the appearance and maintenance of the vortices in the constructed dynamical fields. We propose that these vortices can be seen as bubbles of small, almost vanishing, potential vorticity and smoke carried vertically across the stratification from the troposphere inside the middle stratosphere by their internal heating, against the descending flux of the Brewer–Dobson circulation.

Bayesian Spatial and Trend Analysis on Ozone Extreme Data in South Korea: 1991–2015

Background. Extreme events like flooding, extreme temperature, and ozone depletion are happening in every corner of the world. Thus, the need to model such rare events having enormous damage has been getting priorities in most countries of the world. Methods. The dataset contains the ozone data from 29 representative air monitoring sites in South Korea collected from 1991 to 2015. Spatial generalized extreme value (GEV) using maximum likelihood estimation (MLE) and two max-stable and Bayesian kriging models are the statistical models used for analysis. Moreover, predictive performances of these statistical models are compared using measures like root-mean-squared error (RMSE), mean absolute error (MAE), relative bias (rBIAS), and relative mean separation (rMSEP) have been utilized. Results. From the time plot of ozone data, extreme ozone concentration is increasing linearly within the specified period. The return level of ozone concentration after 10, 25, 50, and 100 years have been forecasted and showed that there was an increasing trend in ozone extremes. High spatial variability of ozone extreme was observed, and those areas around the territories were having extreme ozone concentration than the centers. Moreover, Bayesian Kriging brought about relatively the minimum RMSE compared to the other models. Conclusion. The extreme ozone concentration has clearly showed a positive trend and spatial variation. Moreover, among the models considered in the paper, the Bayesian Kriging has been chosen as the better model.

Occurrence of discontinuities in the ozone concentration data from three reanalyses

Ozone is a very important trace gas in the stratosphere and thus we need to know its time evolution over the globe. The ground based measurements are rare, especially in the Southern Hemisphere. Satellite ozone data have broader coverage, but they are not available from everywhere. On the other hand, the reanalyse data have regular spatial and temporal structure, which is very good for trend analyses. But there are discontinuities in these data.These discontinuities may influence the result of trend studies. The aim of this paper is to detect the discontinuity occurrence (DO) in the following reanalyses: MERRA-2, ERA-5 and JRA-55 with the help of the Pettitt homogeneity test at all common layers above 500 hPa. The discontinuities are sorted according to their size to the significant and the insignificant ones; the former can affect the ozone trend studies. It was shown that DO for the significant discontinuities is the smallest in JRA-55. In the upper model layers, the discontinuity occurrence is the highest. The other area of high DO is the troposphere.

Simplified SAGE II ozone data usage rules

High-quality satellite-based measurements are crucial to the assessment of global stratospheric composition change. The Stratospheric Aerosol and Gas Experiment II (SAGE II) provides the longest, continuous data set of vertically resolved ozone and aerosol extinction coefficients to date and therefore remains a cornerstone of understanding and detecting long-term ozone variability and trends in the stratosphere. Despite its stability, SAGE II measurements must be screened for outliers that are a result of excessive aerosol emitted into the atmosphere and that degrade inferences of change. Current methods for SAGE II ozone measurement quality assurance consist of multiple ad hoc and sometimes conflicting rules, leading to too much valuable data being removed or outliers being missed. In this work, the SAGE II ozone data set version 7.00 is used to develop and present a new set of screening recommendations and to compare the output to the screening recommendations currently used. Applying current recommendations to SAGE II ozone leads to unexpected features, such as removing ozone values around zero if the relative error is used as a screening criterion, leading to biases in monthly mean zonal mean ozone concentrations. Most of these current recommendations were developed based on “visual inspection”, leading to inconsistent rules that might not be applicable at every altitude and latitude. Here, a set of new screening recommendations is presented that take into account the knowledge of how the measurements were made. The number of screening recommendations is reduced to three, which mainly remove ozone values that are affected by high aerosol loading and are therefore not reliable measurements. More data remain when applying these new recommendations compared to the rules that are currently being used, leading to more data being available for scientific studies. The SAGE II ozone data set used here is publicly available at https://doi.org/10.5281/zenodo.3710518 (Kremser et al., 2020). The complete SAGE II version 7.00 data set, which includes other variables in addition to ozone, is available at https://eosweb.larc.nasa.gov/project/sage2/sage2_v7_table (last access: December 2019), https://doi.org/10.5067/ERBS/SAGEII/SOLAR_BINARY_L2-V7.0 (SAGE II Science Team, 2012; Damadeo et al., 2013).

Data Fusion Analysis of Sentinel-4 and Sentinel-5 Simulated Ozone Data

The complete data fusion method, generalized to the case of fusing profiles of atmospheric variables retrieved on different vertical grids and referred to different true values, is applied to ozone profiles retrieved from simulated measurements in the ultraviolet, visible, and thermal infrared spectral ranges for the Sentinel-4 and Sentinel-5 missions of the Copernicus program. In this study, the production and characterization of combined low Earth orbit (Sentinel-5) and geostationary Earth orbit (Sentinel-4) fused ozone data is performed. Fused and standard products have been compared and a performance assessment of the generalized complete data fusion is presented. The analysis of the output products of the complete data fusion algorithm and of the standard processing using quality quantifiers demonstrates that the generalized complete data fusion algorithm provides products of better quality when compared with standard products.

Occurrence of discontinuities in the ozone concentration data from three reanalyses

<p>The aim of this presentation is to compare the occurrence of discontinuities in the ozone concentration data from the MERRA-2, ERA-5 and JRA-55 reanalyse, with the help of the Pettitt homogeneity test. We distinguish between the significant and insignificant discontinuities, according to the relation between the dispersion and the average ozone values before and after the discontinuity.    This occurrence is important for trend analyses, because the presence of discontinuities influences the values of trends and their significance. Discontinuities arise from the changing in the assimilation procedure, introducing new observation to the reanalyse, and changing of data quality. We search for their spatial, temporal and geographical occurrence. There are differences among these reanalyses. In the case of the MERRA-2 data, the transition from SBUV to EOS Aura data in 2004 has great impact on discontinuity behaviour. The frequent occurrence of discontinuities is seen in the uppermost model layers. The uppermost MERRA-2 layer is 0.1 hPa, while for ERA-5 this layer is 1 hPa. So there are differences in the vertical distribution of discontinuities among the reanalyses. The ozone data with the strong occurrence of the significant discontinuities is not suitable for trend analyses.   </p>