ALBERT

Description: In this work, we analyze the seasonal dependence of ozone trends in the stratosphere using four long-term merged data sets, SAGE-CCI-OMPS, SAGE-OSIRIS-OMPS, GOZCARDS, and SWOOSH, which provide more than 30 years of monthly zonal mean ozone profiles in the stratosphere. We focus here on trends between 2000 and 2018. All data sets show similar results, although some discrepancies are observed. In the upper stratosphere, the trends are positive throughout all seasons and the majority of latitudes. The largest upper-stratospheric ozone trends are observed during local winter (up to 6 % per decade) and equinox (up to 3 % per decade) at mid-latitudes. In the equatorial region, we find a very strong seasonal dependence of ozone trends at all altitudes: the trends vary from positive to negative, with the sign of transition depending on altitude and season. The trends are negative in the upper-stratospheric winter (−1 % per decade to −2 % per decade) and in the lower-stratospheric spring (−2 % per decade to −4 % per decade), but positive (2 % per decade to 3 % per decade) at 30–35 km in spring, while the opposite pattern is observed in summer. The tropical trends below 25 km are negative and maximize during summer (up to −2 % per decade) and spring (up to −3 % per decade). In the lower mid-latitude stratosphere, our analysis points to a hemispheric asymmetry: during local summers and equinoxes, positive trends are observed in the south (+1 % per decade to +2 % per decade), while negative trends are observed in the north (−1 % per decade to −2 % per decade). We compare the seasonal dependence of ozone trends with available analyses of the seasonal dependence of stratospheric temperature trends. We find that ozone and temperature trends show positive correlation in the dynamically controlled lower stratosphere and negative correlation above 30 km, where photochemistry dominates. Seasonal trend analysis gives information beyond that contained in annual mean trends, which can be helpful in order to better understand the role of dynamical variability in short-term trends and future ozone recovery predictions.

Description: Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. Reported characterization data should be intercomparable between different instruments, empirically validatable, grid-independent, usable without detailed knowledge of the instrument or retrieval technique, traceable and still have reasonable data volume. The latter may force one to work with representative rather than individual characterization data. Many errors derive from approximations and simplifications used in real-world retrieval schemes, which are reviewed in this paper, along with related error estimation schemes. The main sources of uncertainty are measurement noise, calibration errors, simplifications and idealizations in the radiative transfer model and retrieval scheme, auxiliary data errors, and uncertainties in atmospheric or instrumental parameters. Some of these errors affect the result in a random way, while others chiefly cause a bias or are of mixed character. Beyond this, it is of utmost importance to know the influence of any constraint and prior information on the solution. While different instruments or retrieval schemes may require different error estimation schemes, we provide a list of recommendations which should help to unify retrieval error reporting.

Description: Global Ozone Monitoring by Occultation of Stars (GOMOS) on board Envisat has performed about 440 000 nighttime occultations during 2002–2012. Self-calibrating measurement principle, good vertical resolution, excellent pointing accuracy, and the wide vertical range from the troposphere up to the lower thermosphere make GOMOS profiles interesting for different analyses. The GOMOS ozone data are of high quality in the stratosphere and the mesosphere, but the current operational retrieval algorithm (IPF v6) is not optimized for retrievals in the upper troposphere–lower stratosphere (UTLS). In particular, validation of GOMOS profiles against ozonesonde data has revealed a substantial positive bias (up to 100 %) in the UTLS region. The retrievals in the UTLS are challenging because of low signal-to-noise ratio and the presence of clouds. In this work, we discuss the reasons for the systematic uncertainties in the UTLS with the IPF v6 algorithm or its modifications based on simultaneous retrievals of several constituents using the full visible wavelength range. The main reason is high sensitivity of the UTLS retrieval algorithms to an assumed aerosol extinction model. We have developed a new ozone profile inversion algorithm for GOMOS data (ALGOM2s version 1.0), which is optimized in the UTLS and uses IPF v6 advantages in the middle atmosphere. The ozone retrievals in the whole altitude range from the troposphere to the lower thermosphere are performed in two steps, as in the operational algorithm: spectral inversion followed by the vertical inversion. The spectral inversion is enhanced by using a DOAS-type method at visible wavelengths for the UTLS region. This method uses minimal assumptions about the atmospheric profiles. The vertical inversion is performed as in IPF v6 with the Tikhonov-type regularization according to the target resolution. The validation of new retrieved ozone profiles with ozonesondes shows a dramatic reduction of GOMOS ozone biases in the UTLS. The new GOMOS ozone profiles are also in a very good agreement with measurements by MIPAS, ACE-FTS, and OSIRIS satellite instruments in the UTLS. It is also shown that the known geophysical phenomena in the UTLS ozone are well reproduced with the new GOMOS data.

Description: The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) was an infrared (IR) limb emission spectrometer on the Envisat platform. Currently, there are four MIPAS ozone data products, including the operational Level-2 ozone product processed at ESA, with the scientific prototype processor being operated at IFAC Florence, and three independent research products developed by the Istituto di Fisica Applicata Nello Carrara (ISAC-CNR)/University of Bologna, Oxford University, and the Karlsruhe Institute of Technology–Institute of Meteorology and Climate Research/Instituto de Astrofísica de Andalucía (KIT–IMK/IAA). Here we present a dataset of ozone vertical profiles obtained by merging ozone retrievals from four independent Level-2 MIPAS processors. We also discuss the advantages and the shortcomings of this merged product. As the four processors retrieve ozone in different parts of the spectra (microwindows), the source measurements can be considered as nearly independent with respect to measurement noise. Hence, the information content of the merged product is greater and the precision is better than those of any parent (source) dataset. The merging is performed on a profile per profile basis. Parent ozone profiles are weighted based on the corresponding error covariance matrices; the error correlations between different profile levels are taken into account. The intercorrelations between the processors' errors are evaluated statistically and are used in the merging. The height range of the merged product is 20–55 km, and error covariance matrices are provided as diagnostics. Validation of the merged dataset is performed by comparison with ozone profiles from ACE-FTS (Atmospheric Chemistry Experiment–Fourier Transform Spectrometer) and MLS (Microwave Limb Sounder). Even though the merging is not supposed to remove the biases of the parent datasets, around the ozone volume mixing ratio peak the merged product is found to have a smaller (up to 0.1 ppmv) bias with respect to ACE-FTS than any of the parent datasets. The bias with respect to MLS is of the order of 0.15 ppmv at 20–30 km height and up to 0.45 ppmv at larger altitudes. The agreement between the merged data MIPAS dataset with ACE-FTS is better than that with MLS. This is, however, the case for all parent processors as well.

Description: We discuss the relationships that link the observed fluctuation spectra of the amplitude and phase of signals used for the radio occultation sounding of the Earth's atmosphere, with the spectra of atmospheric inhomogeneities. Our analysis employs the approximation of the phase screen and of weak fluctuations. We make our estimates for the following characteristic inhomogeneity types: (1) the isotropic Kolmogorov turbulence and (2) the anisotropic saturated internal gravity waves. We obtain the expressions for the variances of the amplitude and phase fluctuations of radio occultation signals as well as their estimates for the typical parameters of inhomogeneity models. From the GPS/MET observations, we evaluate the spectra of the amplitude and phase fluctuations in the altitude interval from 4 to 25 km in the middle and polar latitudes. As indicated by theoretical and experimental estimates, the main contribution into the radio signal fluctuations comes from the internal gravity waves. The influence of the Kolmogorov turbulence is negligible. We derive simple relationships that link the parameters of internal gravity waves and the statistical characteristics of the radio signal fluctuations. These results may serve as the basis for the global monitoring of the wave activity in the stratosphere and upper troposphere.

Description: In this paper we describe the stratospheric and mesospheric ozone (version V5r_O3_m22) distributions retrieved from MIPAS observations in the three middle atmosphere modes (MA, NLC, and UA) taken with an unapodized spectral resolution of 0.0625 cm−1 from 2005 until April 2012. O3 is retrieved from microwindows in the 14.8 and 10 µm spectral regions and requires non-local thermodynamic equilibrium (non-LTE) modelling of the O3 v1 and v3 vibrational levels. Ozone is reliably retrieved from 20 km in the MA mode (40 km for UA and NLC) up to ∼ 105 km during dark conditions and up to ∼ 95 km during illuminated conditions. Daytime MIPAS O3 has an average vertical resolution of 3–4 km below 70 km, 6–8 km at 70–80 km, 8–10 km at 80–90, and 5–7 km at the secondary maximum (90–100 km). For nighttime conditions, the vertical resolution is similar below 70 km and better in the upper mesosphere and lower thermosphere: 4–6 km at 70–100 km, 4–5 km at the secondary maximum, and 6–8 km at 100–105 km. The noise error for daytime conditions is typically smaller than 2 % below 50 km, 2–10 % between 50 and 70 km, 10–20 % at 70–90 km, and ∼ 30 % above 95 km. For nighttime, the noise errors are very similar below around 70 km but significantly smaller above, being 10–20 % at 75–95 km, 20–30 % at 95–100 km, and larger than 30 % above 100 km. The additional major O3 errors are the spectroscopic data uncertainties below 50 km (10–12 %) and the non-LTE and temperature errors above 70 km. The validation performed suggests that the spectroscopic errors below 50 km, mainly caused by the O3 air-broadened half-widths of the v2 band, are overestimated. The non-LTE error (including the uncertainty of atomic oxygen in nighttime) is relevant only above ∼ 85 km with values of 15–20 %. The temperature error varies from ∼ 3 % up to 80 km to 15–20 % near 100 km. Between 50 and 70 km, the pointing and spectroscopic errors are the dominant uncertainties. The validation performed in comparisons with SABER, GOMOS, MLS, SMILES, and ACE-FTS shows that MIPAS O3 has an accuracy better than 5 % at and below 50 km, with a positive bias of a few percent. In the 50–75 km region, MIPAS O3 has a positive bias of ≈ 10 %, which is possibly caused in part by O3 spectroscopic errors in the 10 µm region. Between 75 and 90 km, MIPAS nighttime O3 is in agreement with other instruments by 10 %, but for daytime the agreement is slightly larger, ∼ 10–20 %. Above 90 km, MIPAS daytime O3 is in agreement with other instruments by 10 %. At night, however, it shows a positive bias increasing from 10 % at 90 km to 20 % at 95–100 km, the latter of which is attributed to the large atomic oxygen abundance used. We also present MIPAS O3 distributions as function of altitude, latitude, and time, showing the major O3 features in the middle and upper mesosphere. In addition to the rapid diurnal variation due to photochemistry, the data also show apparent signatures of the diurnal migrating tide during both day- and nighttime, as well as the effects of the semi-annual oscillation above ∼ 70 km in the tropics and mid-latitudes. The tropical daytime O3 at 90 km shows a solar signature in phase with the solar cycle.

Description: Ozone forms in the Earth's atmosphere from the photodissociation of molecular oxygen, primarily in the tropical stratosphere. It is then transported to the extratropics by the Brewer–Dobson circulation (BDC), forming a protective ozone layer around the globe. Human emissions of halogen-containing ozone-depleting substances (hODSs) led to a decline in stratospheric ozone until they were banned by the Montreal Protocol, and since 1998 ozone in the upper stratosphere is rising again, likely the recovery from halogen-induced losses. Total column measurements of ozone between the Earth's surface and the top of the atmosphere indicate that the ozone layer has stopped declining across the globe, but no clear increase has been observed at latitudes between 60° S and 60° N outside the polar regions (60–90°). Here we report evidence from multiple satellite measurements that ozone in the lower stratosphere between 60° S and 60° N has indeed continued to decline since 1998. We find that, even though upper stratospheric ozone is recovering, the continuing downward trend in the lower stratosphere prevails, resulting in a downward trend in stratospheric column ozone between 60° S and 60° N. We find that total column ozone between 60° S and 60° N appears not to have decreased only because of increases in tropospheric column ozone that compensate for the stratospheric decreases. The reasons for the continued reduction of lower stratospheric ozone are not clear; models do not reproduce these trends, and thus the causes now urgently need to be established.

Description: In this paper, we present a merged dataset of ozone profiles from several satellite instruments: SAGE II on ERBS, GOMOS, SCIAMACHY and MIPAS on Envisat, OSIRIS on Odin, ACE-FTS on SCISAT, and OMPS on Suomi-NPP. The merged dataset is created in the framework of the European Space Agency Climate Change Initiative (Ozone_cci) with the aim of analyzing stratospheric ozone trends. For the merged dataset, we used the latest versions of the original ozone datasets. The datasets from the individual instruments have been extensively validated and intercompared; only those datasets which are in good agreement, and do not exhibit significant drifts with respect to collocated ground-based observations and with respect to each other, are used for merging. The long-term SAGE–CCI–OMPS dataset is created by computation and merging of deseasonalized anomalies from individual instruments. The merged SAGE–CCI–OMPS dataset consists of deseasonalized anomalies of ozone in 10° latitude bands from 90° S to 90° N and from 10 to 50 km in steps of 1 km covering the period from October 1984 to July 2016. This newly created dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997. The upper stratospheric trends are statistically significant at midlatitudes and indicate ozone recovery, as expected from the decrease of stratospheric halogens that started in the middle of the 1990s and stratospheric cooling.

Description: This paper is focusing on the representativeness of single lidar stations for zonally averaged ozone profile variations over the middle and upper stratosphere. From the lower to the upper stratosphere, ozone profiles from single or grouped lidar stations correlate well with zonal means calculated from the Solar Backscatter Ultraviolet Radiometer (SBUV) satellite overpasses. The best representativeness with significant correlation coefficients is found within ±15∘ of latitude circles north or south of any lidar station. This paper also includes a multivariate linear regression (MLR) analysis on the relative importance of proxy time series for explaining variations in the vertical ozone profiles. Studied proxies represent variability due to influences outside of the earth system (solar cycle) and within the earth system, i.e. dynamic processes (the Quasi Biennial Oscillation, QBO; the Arctic Oscillation, AO; the Antarctic Oscillation, AAO; the El Niño Southern Oscillation, ENSO), those due to volcanic aerosol (aerosol optical depth, AOD), tropopause height changes (including global warming) and those influences due to anthropogenic contributions to atmospheric chemistry (equivalent effective stratospheric chlorine, EESC). Ozone trends are estimated, with and without removal of proxies, from the total available 1980 to 2015 SBUV record. Except for the chemistry related proxy (EESC) and its orthogonal function, the removal of the other proxies does not alter the significance of the estimated long-term trends. At heights above 15 hPa an “inflection point” between 1997 and 1999 marks the end of significant negative ozone trends, followed by a recent period between 1998 and 2015 with positive ozone trends. At heights between 15 and 40 hPa the pre-1998 negative ozone trends tend to become less significant as we move towards 2015, below which the lower stratosphere ozone decline continues in agreement with findings of recent literature.