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Using the IMK–IAA data processor, methane and nitrous oxide distributions were retrieved from version-8 limb emission spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). The dataset includes measurements from the nominal, upper troposphere–lower stratosphere, middle-atmosphere, upper-atmosphere and noctilucent-cloud observation modes. The processing differs from the previous version-5 data with respect to the atmospheric state variables that are jointly retrieved along with the target gases CH4 and N2O, the treatment of the radiance offset, the selection of microwindows, the regularization, the spectroscopic data used and the treatment of horizontal variability of the atmospheric state. Besides the regular data product, a coarse-grid representation of the profiles with unity averaging kernels is available, as well as a specific research product for middle-atmosphere measurements resulting from a slightly different retrieval approach. The CH4 errors are dominated by the large spectroscopic uncertainty for line intensities, which probably is too pessimistic, and estimated to be 21 %–34 % in the altitude range 6–68 km for northern midlatitude summer day conditions. The N2O errors are 7 %–17 % below 45 km. At higher altitudes they increase strongly due to nearly vanishing N2O amounts. Analysis of the horizontal averaging kernels reveals that for both gases the horizontal resolution is sampling-limited; i.e., information is not smeared over consecutive limb scans. Zonal-mean seasonal composites of both CH4 and N2O exhibit the typical distribution of source gases with strong upwelling in the tropics and subsidence above the winter poles. Comparison with the previous data version shows several improvements: first, the vertical resolution of the retrieved CH4 (N2O) profiles has generally been significantly enhanced and varies between 2.5 (2.5) and 4 (5) km at altitudes between 10 and 60 km, with the best resolution around 30 km for both species. Secondly, the number of non-converged retrievals has been clearly reduced, and thirdly, formerly strongly oscillating profiles are now considerably smoother.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat provided infrared limb emission spectra, which were used to infer global distributions of CFC-11, CFC-12, and HCFC-22. Spectra were analysed using constrained non-linear least-squares fitting. Changes with respect to earlier data versions refer to the use of version 8 spectra, the altitude range where the background continuum is considered, details of the regularization and microwindow selection, and the occasional joint fitting of interfering species, the use of new spectroscopic data, the joint fit of a tangent-height-dependent spectral offset, and the use of 2D temperature fields. In the lower stratosphere the error budget is dominated by uncertainties in spectroscopic data, while above this measurement noise is the leading error source. The vertical resolution of CFC-11 and CFC-12 is 2–3 km near the tropopause, about 4 km at 30 km altitude, and 6–10 km at 50 km. The vertical resolution of HCFC-22 is somewhat coarser, 3–4 km at the tropopause and 10–12 km at 35 km altitude. In the altitude range of interest, the horizontal resolution is typically limited by the horizontal sampling of the measurements, not by the smearing of the retrievals. Horizontal information displacement does not exceed 150 km, which can become an issue only for comparisons with model simulations with high horizontal resolution or localized in situ observations. Along with the regular data product, an alternative representation of the data on a coarser vertical grid is offered. These data can be used without consideration of the averaging kernels. The new data version provides improvement with respect to reduction of biases and improved consistency between the full- and reduced-resolution mission period of MIPAS.

We present a new version of O3 data retrieved from the three Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) observation modes that we refer to for simplicity as the modes of the middle atmosphere (middle atmosphere, MA; upper atmosphere, UA; and noctilucent cloud, NLC). The O3 profiles cover altitudes from 20 up to 100 km for the daytime and up to 105 km at nighttime, for all latitudes, and the period 2005 until 2012. The data have been obtained with the IMK–IAA (Institute of Meteorology and Climate Research and Instituto de Astrofísica de Andalucía) MIPAS level-2 data processor and are based on ESA version-8 re-calibrated radiance spectra with improved temporal stability. The processing included several improvements with respect to the previous version, such as the consistency of the microwindows and spectroscopic data with those used in the nominal-mode V8R data, the O3 a priori profiles, and updates of the non-local thermodynamic equilibrium (non-LTE) parameters and the nighttime atomic oxygen. In particular, the collisional relaxation of O3(v1,v3) by the atomic oxygen was reduced by a factor of 2 in order to obtain a better agreement of nighttime mesospheric O3 with “non-LTE-free” measurements. Random errors are dominated by the measurement noise with 1σ values for single profiles for the daytime of < 5 % below ∼ 60 km, 5 %–10 % between 60 and 70 km, 10 %–20 % at 70–90 km, and about 30 % at 95 km. For nighttime, they are very similar below 70 km but smaller above (10 %–20 % at 75–95 km, 20 %–30 % at 95–100 km and larger than 30 % above 100 km). The systematic error is ∼ 6 % below ∼ 60 km (dominated by uncertainties in spectroscopic data) and 8 %–12 % above ∼ 60 km, mainly caused by non-LTE uncertainties. The systematic errors in the 80–100 km range are significantly smaller than in the previous version. The major differences with respect to the previous version are as follows: (1) the new retrievals provide O3 abundances in the 20–50 km altitude range that are larger by about 2 %–5 % (0.2–0.5 ppmv); (2) O3 abundances were reduced by ∼ 2 %–4 % between 50 and 60 km in the tropics and mid-latitudes; (3) O3 abundances in the nighttime O3 minimum just below 80 km were reduced, leading to a more realistic diurnal variation; (4) daytime O3 concentrations in the secondary maximum at the tropical and middle latitudes (∼ 40 %, 0.2–0.3 ppmv) were larger; and (5) nighttime O3 abundances in the secondary maximum were reduced by 10 %–30 %. The O3 profiles retrieved from the nominal mode (NOM) and the middle-atmosphere modes are fully consistent in their common altitude range (20–70 km). Only at 60–70 km does daytime O3 of NOM seem to be larger than that of MA/UA by 2 %–10 %. Compared to other satellite instruments, MIPAS seems to have a positive bias of 5 %–8 % below 70 km. Noticeably, the new version of MIPAS data agrees much better than before with all instruments in the upper mesosphere–lower thermosphere, reducing the differences from ∼± 20 % to ∼± 10 %. Further, the diurnal variation in O3 in the upper mesosphere (near 80 km) has been significantly improved.

Solar coronal mass ejections can accelerate charged particles, mostly protons, to high energies, causing solar proton events (SPEs). Such energetic particles can precipitate upon the Earth's atmosphere, mostly in polar regions because of geomagnetic shielding. Here, SPE-induced chlorine activation due to ion chemistry can occur, and the activated chlorine depletes ozone in the polar middle atmosphere. We use the state-of-the-art 1D stacked-box Exoplanetary Terrestrial Ion Chemistry (ExoTIC) model of atmospheric ion and neutral composition to investigate such events in the Northern Hemisphere (NH). The Halloween SPE that occurred in late October 2003 is used as a test field for our study. This event has been extensively studied before using different 3D models and satellite observations. Our main purpose is to use such a large event that has been recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on the Environmental Satellite (ENVISAT) to evaluate the performance of the ion chemistry model. Sensitivity tests were carried out for different model settings with a focus on the chlorine species of HOCl and ClONO2 as well as O3 and reactive nitrogen, NOy. The model simulations were performed in the Northern Hemisphere at a high latitude of 67.5∘ N, inside the polar cap. Comparison of the simulated effects against MIPAS observations for the Halloween SPE revealed rather good temporal agreement, also in terms of altitude range for HOCl, O3 and NOy. For ClONO2, good agreement was found in terms of altitude range. The model showed ClONO2 enhancements after the peak of the event. The best model setting was the one with full ion chemistry where O(1D) was set to photo-chemical equilibrium. HOCl and ozone changes are very well reproduced by the model, especially for nighttime. HOCl was found to be the main active chlorine species under nighttime conditions, resulting in an increase of more than 0.2 ppbv. Further, ClONO2 enhancements of 0.2–0.3 ppbv have been observed during both daytime and nighttime. Model settings that compared best with MIPAS observations were applied to an extreme solar event that occurred in AD 775, presumably once in a 1000-year event. With the model applied to this scenario, an assessment can be made about what is to be expected at worst for the effects of a SPE on the middle atmosphere, concentrating on the effects of ion chemistry compared to crude parameterizations. Here, a systematic analysis comparing the impact of the Halloween SPE and the extreme event on the Earth's middle atmosphere is presented. As seen from the model simulations, both events were able to perturb the polar stratosphere and mesosphere with a high production of NOy and HOx. Longer-lasting and stronger stratospheric ozone loss was seen for the extreme event. A qualitative difference between the two events and a long-lasting impact on HOCl and HCl for the extreme event were found. Chlorine ion chemistry contributed to stratospheric ozone losses of 2.4 % for daytime and 10 % for nighttime during the Halloween SPE, as seen with time-dependent ionization rates applied to the model. Furthermore, while comparing the Halloween SPE and the extreme scenario, with ionization rate profiles applied just for the event day, the inclusion of chlorine ion chemistry added ozone losses of 10 % and 20 % respectively.

In this paper, we present the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments – SAGE II (Stratospheric Aerosol and Gases Experiment II), OSIRIS (Optical Spectrograph and InfraRed Imaging System), MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), SCIAMACHY (SCanning Imaging Spectrometer for Atmospheric CHartographY), GOMOS (Global Ozone Monitoring by Occultation of Stars), ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer), OMPS-LP (Ozone Monitor Profiling Suite Limb Profiler), POAM (Polar Ozone and Aerosol Measurement) III, and SAGE III/ISS (Stratospheric Aerosol and Gases Experiment III on the International Space Station). Compared to the original version of the SAGE-CCI-OMPS dataset (Sofieva et al., 2017b), the update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP). In this paper, we show detailed intercomparisons of ozone profiles from different instruments and data versions, with a focus on the detection of possible drifts in the datasets. The SAGE-CCI-OMPS+ dataset has a better coverage of polar regions and of the upper troposphere and the lower stratosphere (UTLS) than the previous dataset. We also studied the influence of including new datasets on ozone trends, which are estimated using multiple linear regression. The changes in the merged dataset do not change the overall morphology of post-1997 ozone trends; statistically significant trends are observed in the upper stratosphere. The largest changes in ozone trends are observed in polar regions, especially in the Southern Hemisphere. The updated SAGE-CCI-OMPS+ dataset contains profiles of deseasonalized anomalies and ozone concentrations from 1984 to 2021, in 10∘ latitude bins from 90∘ S to 90∘ N and in the altitude range from 10 to 50 km. The dataset is open access and available at https://climate.esa.int/en/projects/ozone/data/ (last access: 9 March 2023) and at ftp://cci_web@ftp-ae.oma.be/esacci (ESA Climate Office; last access: 9 March 2023).

A new global O3 data product retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) spectra with the IMK–IAA MIPAS data processor has been released. These data are based on ESA version 8 recalibrated radiance spectra with improved temporal stability. Changes in the level-2 processing with respect to previous data versions include the following: (1) the retrievals use improved temperature data and thus suffer less from the propagation of related errors. (2) The background continuum is now considered up to 58 km. (3) A priori information is now used to constrain the retrieval of the radiance offset. (4) Water vapour is fitted jointly with ozone to minimize the impact of interfering water lines. (5) A more adequate regularization has been chosen. (6) Ozone absorption lines in the MIPAS A band (685–980 cm−1) are used almost exclusively because of inconsistencies in spectroscopic data in the MIPAS AB band (1010–1180 cm−1). Only at altitudes above 50 km, where A-band ozone lines do not provide sufficient information, are ozone lines in the MIPAS AB band used. (7) Temperature-adjusted climatologies of vibrational temperatures of O3 and CO2 are considered to account for non-local thermodynamic equilibrium radiation. Ozone errors are estimated to be less than 10 % in the altitude range 20–50 km. The error budget is dominated by the spectroscopic errors, followed by the uncertainty of the instrumental line shape function, the gain calibration error, and the spectral noise. The error contribution of interfering gases is almost negligible. The vertical resolution depends on altitude and atmospheric conditions. In 2002–2004 it varies between 2.5 km at the lowest altitudes and 6 km at 70 km, while in 2005–2012 it covers 2 to 5.5 km in the same altitude range. The horizontal smearing in terms of the full width at half maximum of the horizontal component of the two-dimensional averaging kernel matrix is smaller than, or approximately equal to, the distance between two subsequent limb scans at all altitudes. This implies that the horizontal resolution is sampling-limited or optimal, respectively. An additional data version is made available that is free of the formal a priori information and thus more user-friendly for certain applications. Version 8 ozone results show a better consistency between the two MIPAS measurement periods. They seem to be more realistic than preceding data versions in terms of long-term stability, as at least a part of the drift is corrected. Further, the representation of elevated stratopause situations is improved.

This study presents an error budget assessment for the ozone profiles retrieved at the University of Bremen through limb observations of the Ozone Mapper and Profiler Suite – Limb Profiler Suomi National Polar-orbiting Partnership (OMPS-LP SNPP) satellite instrument. The error characteristics are presented in a form that aims at being compliant with the recommendations and the standardizing effort of the Towards Unified Error Reporting (TUNER) project. Besides the retrieval noise, contributions from retrieval parameters are extensively discussed and quantified by using synthetic retrievals performed with the SCIATRAN radiative transfer model. For this investigation, a representative set of OMPS-LP measurements is selected to provide a reliable estimation of the uncertainties as a function of latitude and season. Errors originating from model approximations and spectroscopic data are also taken into account and found to be non-negligible. The choice of the ozone cross section is found to be relevant, as expected. Overall, we classify the estimated errors as random or systematic and investigate correlations between errors from different sources. After summing up the relevant error components, we present an estimate of the total random uncertainty on the retrieved ozone profiles, which is found to be in the 5 %–30 % range in the lower stratosphere, 3 %–5 % in the middle stratosphere, and 5 %–7 % at upper altitudes. The systematic uncertainty is mainly due to cloud contamination and model errors in the lower stratosphere and due to the retrieval bias at higher altitudes. The corresponding total bias exceeds 5 % only above 50 km and below 20 km. After computing the estimate of the overall random and systematic error components, we also provide an ex-post assessment of the uncertainties using self-collocated OMPS-LP observations and collocated Microwave Limb Sounder (MLS) data in a χ2 fashion.

High-resolution model data are used to estimate the statistically typical mixing ratio variabilities of trace species as a function of distance and time separation. These estimates can be used to explain the fact that some of the differences between observations made with different observing systems are due to the less-than-perfect co-location of the measurements. The variability function is approximated by a two-parameter regression function, and lookup tables of the natural variability values as a function of distance separation and time separation are provided. In addition, a reparametrization of the variability values as a function of latitudinal gradients is proposed, and the seasonal independence of the linear approximation of such a function is demonstrated.

A new global set of atmospheric temperature profiles is retrieved from recalibrated radiance spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Changes with respect to previous data versions include a new radiometric calibration considering the time dependency of the detector nonlinearity and a more robust frequency calibration scheme. Temperature is retrieved using a smoothing constraint, while tangent altitude pointing information is constrained using optimal estimation. ECMWF ERA-Interim is used as a priori temperature below 43 km. Above, a priori data are based on data from the Whole Atmosphere Community Climate Model Version 4 (WACCM4). Bias-corrected fields from specified dynamics runs, sampled at the MIPAS times and locations, are used, blended with ERA-Interim between 43 and 53 km. Horizontal variability of temperature is considered by scaling an a priori 3D temperature field in the orbit plane in a way that the horizontal structure is provided by the a priori while the vertical structure comes from the measurements. Additional microwindows with better sensitivity at higher altitudes are used. The background continuum is jointly fitted with the target parameters up to 58 km altitude. The radiance offset correction is strongly regularized towards an empirically determined vertical offset profile. In order to avoid the propagation of uncertainties of O3 and H2O a priori assumptions, the abundances of these species are retrieved jointly with temperature. The retrieval is based on HITRAN 2016 spectroscopic data, with a few amendments. Temperature-adjusted climatologies of vibrational populations of CO2 states emitting in the 15 µm region are used in the radiative transfer modeling in order to account for non-local thermodynamic equilibrium. Numerical integration in the radiative transfer model is now performed at higher accuracy. The random component of the temperature uncertainty typically varies between 0.4 and 1 K, with occasional excursions up to 1.3 K above 60 km altitude. The leading sources of the random component of the temperature error are measurement noise, gain calibration uncertainty, spectral shift, and uncertain CO2 mixing ratios. The systematic error is caused by uncertainties in spectroscopic data and line shape uncertainties. It ranges from 0.2 K at 20 km altitude for northern midlatitude summer conditions to 2.3 K at 12 km for tropical conditions. The estimated total uncertainty amounts to values between 0.6 K at 20 km for midlatitude summer conditions to 2.5 K at 12–15 km for tropical conditions. The vertical resolution varies around 3 km for altitudes below 50 km. The long-term drift encountered in the previous temperature product has been largely reduced. The consistency between high spectral resolution results from 2002 to 2004 and the reduced spectral resolution results from 2005 to 2012 has been largely improved. As expected, most pronounced temperature differences between version 8 and previous data versions are found in elevated stratopause situations. The fact that the phase of temperature waves seen by MIPAS is not locked to the wave phase found in ECMWF analyses demonstrates that our retrieval provides independent information and does not merely reproduce the prior information.

In this paper, we present the MErged GRIdded Dataset of Ozone Profiles (MEGRIDOP) in the stratosphere with a resolved longitudinal structure, which is derived from data from six limb and occultation satellite instruments: GOMOS, SCIAMACHY and MIPAS on Envisat, OSIRIS on Odin, OMPS on Suomi-NPP, and MLS on Aura. The merged dataset was generated as a contribution to the European Space Agency Climate Change Initiative Ozone project (Ozone_cci). The period of this merged time series of ozone profiles is from late 2001 until the end of 2018. The monthly mean gridded ozone profile dataset is provided in the altitude range from 10 to 50 km in bins of 10∘ latitude × 20∘ longitude. The merging is performed using deseasonalized anomalies. The created MEGRIDOP dataset can be used for analyses that probe our understanding of stratospheric chemistry and dynamics. To illustrate some possible applications, we created a climatology of ozone profiles with resolved longitudinal structure. We found zonal asymmetry in the climatological ozone profiles at middle and high latitudes associated with the polar vortex. At northern high latitudes, the amplitude of the seasonal cycle also has a longitudinal dependence. The MEGRIDOP dataset has also been used to evaluate regional vertically resolved ozone trends in the stratosphere, including the polar regions. It is found that stratospheric ozone trends exhibit longitudinal structures at Northern Hemisphere middle and high latitudes, with enhanced trends over Scandinavia and the Atlantic region. This agrees well with previous analyses and might be due to changes in dynamical processes related to the Brewer–Dobson circulation.

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.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) was an infrared limb emission spectrometer on the Envisat platform. From 2002 to 2012, it performed pole-to-pole measurements during day and night, producing more than 1000 profiles per day. The European Space Agency (ESA) recently released the new version 7 of Level 1B MIPAS spectra, in which a new set of time-dependent correction coefficients for the nonlinearity in the detector response functions was implemented. This change is expected to reduce the long-term drift of the MIPAS Level 2 data. We evaluate the long-term stability of ozone Level 2 data retrieved from MIPAS v7 Level 1B spectra with the IMK/IAA scientific level 2 processor. For this, we compare MIPAS data with ozone measurements from the Microwave Limb Sounder (MLS) instrument on NASA's Aura satellite, ozonesondes and ground-based lidar instruments. The ozonesondes and lidars alone do not allow us to conclude with enough significance that the new version is more stable than the previous one, but a clear improvement in long-term stability is observed in the satellite-data-based drift analysis. The results of ozonesondes, lidars and satellite drift analysis are consistent: all indicate that the drifts of the new version are less negative/more positive nearly everywhere above 15 km. The 10-year MIPAS ozone trends calculated from the old and the new data versions are compared. The new trends are closer to old drift-corrected trends than the old uncorrected trends were. From this, we conclude that the nonlinearity correction performed on Level 1B data is an improvement. These results indicate that MIPAS data are now even more suited for trend studies, alone or as part of a merged data record.

Discrepancies in ozone retrievals in MIPAS channels A (685–970 cm−1) and AB (1020–1170 cm−1) have been a long-standing problem in MIPAS data analysis, amounting to an interchannel bias (AB–A) of up to 8 % between ozone volume mixing ratios in the altitude range 30–40 km. We discuss various candidate explanations, among them forward model and retrieval algorithm errors, interchannel calibration inconsistencies and spectroscopic data inconsistencies. We show that forward-modelling errors as well as errors in the retrieval algorithm can be ruled out as an explanation because the bias can be reproduced with an entirely independent retrieval algorithm (GEOFIT), relying on a different forward radiative transfer model. Instrumental and calibration issues can also be refuted as an explanation because ozone retrievals based on balloon-borne measurements with a different instrument (MIPAS-B) and an independent level-1 data processing scheme produce a rather similar interchannel bias. Thus, spectroscopic inconsistencies in the MIPAS database used for ozone retrieval are practically the only reason left. To further investigate this issue, we performed retrievals using additional spectroscopic databases. Various versions of the HITRAN database generally produced rather similar channel AB–A differences. Use of a different database, namely GEISA-2015, led to similar results in channel AB, but to even higher ozone volume mixing ratios for channel A retrievals, i.e. to a reversal of the bias. We show that the differences in MIPAS channel A retrievals result from about 13 % lower air-broadening coefficients of the strongest lines in the GEISA-2015 database. Since the errors in line intensity of the major lines used in MIPAS channels A and AB are reported to be considerably lower than the observed bias, we posit that a major part of the channel AB–A differences can be attributed to inconsistent air-broadening coefficients as well. To corroborate this assumption we show some clearly inconsistent air-broadening coefficients in the HITRAN-2008 database. The interchannel bias in retrieved ozone amounts can be reduced by increasing the air-broadening coefficients of the lines in MIPAS channel AB in the HITRAN-2008 database by 6 %–8 %.

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.

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.

Ozone profile trends over the period 2000 to 2016 from several merged satellite ozone data sets and from ground-based data measured by four techniques at stations of the Network for the Detection of Atmospheric Composition Change indicate significant ozone increases in the upper stratosphere, between 35 and 48 km altitude (5 and 1 hPa). Near 2 hPa (42 km), ozone has been increasing by about 1.5 % per decade in the tropics (20° S to 20° N), and by 2 to 2.5 % per decade in the 35 to 60° latitude bands of both hemispheres. At levels below 35 km (5 hPa), 2000 to 2016 ozone trends are smaller and not statistically significant. The observed trend profiles are consistent with expectations from chemistry climate model simulations. This study confirms positive trends of upper stratospheric ozone already reported, e.g., in the WMO/UNEP Ozone Assessment 2014 or by Harris et al. (2015). Compared to those studies, three to four additional years of observations, updated and improved data sets with reduced drift, and the fact that nearly all individual data sets indicate ozone increase in the upper stratosphere, all give enhanced confidence. Uncertainties have been reduced, for example for the trend near 2 hPa in the 35 to 60° latitude bands from about ±5 % (2σ) in Harris et al. (2015) to less than ±2 % (2σ). Nevertheless, a thorough analysis of possible drifts and differences between various data sources is still required, as is a detailed attribution of the observed increases to declining ozone-depleting substances and to stratospheric cooling. Ongoing quality observations from multiple independent platforms are key for verifying that recovery of the ozone layer continues as expected.

The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). The paper discusses the many sources of error in CDRs, noting that different errors may be correlated across a wide range of timescales and space scales. Error effects that contribute negligibly to the total uncertainty in a single-satellite measurement can be the dominant sources of uncertainty in a CDR on the large space scales and long timescales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. The characterization of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the error distribution, and the propagation of the uncertainty to the geophysical variable in the CDR accounting for its error correlation properties. Uncertainty estimates can and should be validated as part of CDR validation when possible. These principles are quite general, but the approach to providing uncertainty information appropriate to different ECVs is varied, as confirmed by a brief review across different ECVs in the CCI. User requirements for uncertainty information can conflict with each other, and a variety of solutions and compromises are possible. The concept of an ensemble CDR as a simple means of communicating rigorous uncertainty information to users is discussed. Our review concludes by providing eight concrete recommendations for good practice in providing and communicating uncertainty in EO-based climate data records.

MIPAS thermal limb emission measurements were used to derive vertically resolved profiles of carbon tetrachloride (CCl4). Level-1b data versions MIPAS/5.02 to MIPAS/5.06 were converted into volume mixing ratio profiles using the level-2 processor developed at Karlsruhe Institute of Technology (KIT) Institute of Meteorology and Climate Research (IMK) and Consejo Superior de Investigaciones Científicas (CSIC), Instituto de Astrofísica de Andalucía (IAA). Consideration of peroxyacetyl nitrate (PAN) as an interfering species, which is jointly retrieved, and CO2 line mixing is crucial for reliable retrievals. Parts of the CO2 Q-branch region that overlap with the CCl4 signature were omitted, since large residuals were still found even though line mixing was considered in the forward model. However, the omitted spectral region could be narrowed noticeably when line mixing was accounted for. A new CCl4 spectroscopic data set leads to slightly smaller CCl4 volume mixing ratios. In general, latitude–altitude cross sections show the expected CCl4 features with highest values of around 90 pptv at altitudes at and below the tropical tropopause and values decreasing with altitude and latitude due to stratospheric decomposition. Other patterns, such as subsidence in the polar vortex during winter and early spring, are also visible in the distributions. The decline in CCl4 abundance during the MIPAS Envisat measurement period (July 2002 to April 2012) is clearly reflected in the altitude–latitude cross section of trends estimated from the entire retrieved data set.

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.

Profiles of CFC-11 (CCl3F) and CFC-12 (CCl2F2) of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard the European satellite Envisat have been retrieved from versions MIPAS/4.61 to MIPAS/4.62 and MIPAS/5.02 to MIPAS/5.06 level-1b data using the scientific level-2 processor run by Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK) and Consejo Superior de Investigaciones Científicas (CSIC), Instituto de Astrofísica de Andalucía (IAA). These profiles have been compared to measurements taken by the balloon-borne cryosampler, Mark IV (MkIV) and MIPAS-Balloon (MIPAS-B), the airborne MIPAS-STRatospheric aircraft (MIPAS-STR), the satellite-borne Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) and the High Resolution Dynamic Limb Sounder (HIRDLS), as well as the ground-based Halocarbon and other Atmospheric Trace Species (HATS) network for the reduced spectral resolution period (RR: January 2005–April 2012) of MIPAS. ACE-FTS, MkIV and HATS also provide measurements during the high spectral resolution period (full resolution, FR: July 2002–March 2004) and were used to validate MIPAS CFC-11 and CFC-12 products during that time, as well as profiles from the Improved Limb Atmospheric Spectrometer, ILAS-II. In general, we find that MIPAS shows slightly higher values for CFC-11 at the lower end of the profiles (below ∼ 15 km) and in a comparison of HATS ground-based data and MIPAS measurements at 3 km below the tropopause. Differences range from approximately 10 to 50 pptv ( ∼ 5–20 %) during the RR period. In general, differences are slightly smaller for the FR period. An indication of a slight high bias at the lower end of the profile exists for CFC-12 as well, but this bias is far less pronounced than for CFC-11 and is not as obvious in the relative differences between MIPAS and any of the comparison instruments. Differences at the lower end of the profile (below ∼ 15 km) and in the comparison of HATS and MIPAS measurements taken at 3 km below the tropopause mainly stay within 10–50 pptv (corresponding to ∼ 2–10 % for CFC-12) for the RR and the FR period. Between ∼ 15 and 30 km, most comparisons agree within 10–20 pptv (10–20 %), apart from ILAS-II, which shows large differences above ∼ 17 km. Overall, relative differences are usually smaller for CFC-12 than for CFC-11. For both species – CFC-11 and CFC-12 – we find that differences at the lower end of the profile tend to be larger at higher latitudes than in tropical and subtropical regions. In addition, MIPAS profiles have a maximum in their mixing ratio around the tropopause, which is most obvious in tropical mean profiles. Comparisons of the standard deviation in a quiescent atmosphere (polar summer) show that only the CFC-12 FR error budget can fully explain the observed variability, while for the other products (CFC-11 FR and RR and CFC-12 RR) only two-thirds to three-quarters can be explained. Investigations regarding the temporal stability show very small negative drifts in MIPAS CFC-11 measurements. These instrument drifts vary between ∼ 1 and 3 % decade−1. For CFC-12, the drifts are also negative and close to zero up to ∼ 30 km. Above that altitude, larger drifts of up to ∼ 50 % decade−1 appear which are negative up to ∼ 35 km and positive, but of a similar magnitude, above.

We report on HCFC-22 data acquired by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) in the reduced spectral resolution nominal observation mode. The data cover the period from January 2005 to April 2012 and the altitude range from the upper troposphere (above cloud top altitude) to about 50 km. The profile retrieval was performed by constrained nonlinear least squares fitting of modelled spectra to the measured limb spectral radiances. The spectral ν4-band at 816.5 ± 13 cm−1 was used for the retrieval. A Tikhonov-type smoothing constraint was applied to stabilise the retrieval. In the lower stratosphere, we find a global volume mixing ratio of HCFC-22 of about 185 pptv in January 2005. The rate of linear growth in the lower latitudes lower stratosphere was about 6 to 7 pptv year−1 in the period 2005–2012. The profiles obtained were compared with ACE-FTS satellite data v3.5, as well as with MkIV balloon profiles and cryosampler balloon measurements. Between 13 and 22 km, average agreement within −3 to +5 pptv (MIPAS – ACE) with ACE-FTS v3.5 profiles is demonstrated. Agreement with MkIV solar occultation balloon-borne measurements is within 10–20 pptv below 30 km and worse above, while in situ cryosampler balloon measurements are systematically lower over their full altitude range by 15–50 pptv below 24 km and less than 10 pptv above 28 km. MIPAS HCFC-22 time series below 10 km altitude are shown to agree mostly well to corresponding time series of near-surface abundances from the NOAA/ESRL and AGAGE networks, although a more pronounced seasonal cycle is obvious in the satellite data. This is attributed to tropopause altitude fluctuations and subsidence of polar winter stratospheric air into the troposphere. A parametric model consisting of constant, linear, quasi-biennial oscillation (QBO) and several sine and cosine terms with different periods has been fitted to the temporal variation of stratospheric HCFC-22 for all 10°-latitude/1-to-2-km-altitude bins. The relative linear variation was always positive, with relative increases of 40–70 % decade−1 in the tropics and global lower stratosphere, and up to 120 % decade−1 in the upper stratosphere of the northern polar region and the southern extratropical hemisphere. Asian HCFC-22 emissions have become the major source of global upper tropospheric HCFC-22. In the upper troposphere, monsoon air, rich in HCFC-22, is instantaneously mixed into the tropics. In the middle stratosphere, between 20 and 30 km, the observed trend is inconsistent with the trend at the surface (corrected for the age of stratospheric air), hinting at circulation changes. There exists a stronger positive trend in HCFC-22 in the Southern Hemisphere and a more muted positive trend in the Northern Hemisphere, implying a potential change in the stratospheric circulation over the observation period.

Improved versions of CH4 and N2O profiles derived at the Institute of Meteorology and Climate Research and Instituto de Astrofísica de Andalucía (CSIC) from spectra measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) have become available. For the MIPAS full-resolution period (2002–2004) these are V5H_CH4_21 and V5H_N2O_21 and for the reduced-resolution period (2005–2012) these are V5R_CH4_224, V5R_CH4_225, V5R_N2O_224 and V5R_N2O_225. Here, we compare CH4 profiles to those measured by the Fourier Transform Spectrometer on board of the Atmospheric Chemistry Experiment (ACE-FTS), the HALogen Occultation Experiment (HALOE) and the Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY), to the Global Cooperative Air Sampling Network (GCASN) surface data. We find the MIPAS CH4 profiles below 25 km to be typically higher of the order of 0.1 ppmv for both measurement periods. N2O profiles are compared to those measured by ACE-FTS, the Microwave Limb Sounder on board of the Aura satellite (Aura-MLS) and the Sub-millimetre Radiometer on board of the Odin satellite (Odin-SMR) as well as to the Halocarbons and other Atmospheric Trace Species Group (HATS) surface data. The mixing ratios of the satellite instruments agree well with each other for the full-resolution period. For the reduced-resolution period, MIPAS produces similar values as Odin-SMR, but higher values than ACE-FTS and HATS. Below 27 km, the MIPAS profiles show higher mixing ratios than Aura-MLS, and lower values between 27 and 41 km. Cross-comparisons between the two MIPAS measurement periods show that they generally agree quite well, but, especially for CH4, the reduced-resolution period seems to produce slightly higher mixing ratios than the full-resolution data.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is an infrared (IR) limb emission spectrometer on the Envisat platform. It measures trace gas distributions during day and night, pole-to-pole, over an altitude range from 6 to 70 km in nominal mode and up to 170 km in special modes, depending on the measurement mode, producing more than 1000 profiles day−1. We present the results of a validation study of methane, version V5R_CH4_222, retrieved with the IMK/IAA (Institut für Meteorologie und Klimaforschung, Karlsruhe/Instituto de Astrofisica de Andalucia, Grenada) MIPAS scientific level 2 processor. The level 1 spectra are provided by the ESA (European Space Agency) and version 5 was used. The time period covered is 2005–2012, which corresponds to the period when MIPAS measured trace gas distributions at a reduced spectral resolution of 0.0625 cm−1. The comparison with satellite instruments includes the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the HALogen Occultation Experiment (HALOE), the Solar Occultation For Ice Experiment (SOFIE) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). Furthermore, comparisons with MkIV balloon-borne solar occultation measurements and with air sampling measurements performed by the University of Frankfurt are presented. The validation activities include bias determination, assessment of stability, precision validation, analysis of histograms and comparison of corresponding climatologies. Above 50 km altitude, MIPAS methane mixing ratios agree within 3 % with ACE-FTS and SOFIE. Between 30 and 40 km an agreement within 3 % with SCIAMACHY has been found. In the middle stratosphere, there is no clear indication of a MIPAS bias since comparisons with various instruments contradict each other. In the lower stratosphere (below 25 km) MIPAS CH4 is biased high with respect to satellite instruments, and the most likely estimate of this bias is 14 %. However, in the comparison with CH4 data obtained from cryogenic whole-air sampler (cryosampler) measurements, there is no evidence of a high bias in MIPAS between 20 and 25 km altitude. Precision validation is performed on collocated MIPAS–MIPAS pairs and suggests a slight underestimation of its uncertainties by a factor of 1.2. No significant evidence of an instrumental drift has been found.

We present the strongly revised IMK/IAA MIPAS-ENVISAT CH4 and N2O data products for the MIPAS full-resolution (versions V5H_CH4_21 and V5H_N2O_21) and for the reduced-resolution period (versions V5R_CH4_224, V5R_CH4_225, V5R_N2O_224 and V5R_N2O_225). These data sets cover both MIPAS measurement periods from June 2002 until March 2004 and from January 2005 to April 2012. Differences with older retrieval versions which are known to have a high bias are discussed. The usage of the HITRAN 2008 spectroscopic data set leads to lower values for both gases in the lower part of the profile. The improved correction of additive radiance offsets and handling of background radiance continua allows for aerosol contributions at altitudes in the upper stratosphere and above. These changes lead to more plausible values, both in the radiance offset and in the profiles of the continuum absorption coefficients. They also increase the fraction of converged retrievals. Some minor changes were applied to the constraint of the inverse problem, causing small differences in the retrieved profiles, mostly due to the relaxation of off-diagonal regularisation matrix elements for the calculation of jointly retrieved absorption coefficient profiles. Spectral microwindows have been adjusted to avoid areas with saturated spectral signatures. Jointly retrieving profiles of water vapour and nitric acid serves to compensate spectroscopic inconsistencies. We discuss the averaging kernels of the profiles and their vertical resolution. The latter ranges from 2.5 to 7 km for CH4, and from 2.5 to 6 km for N2O in the reduced-resolution period. For the full-resolution period, the vertical resolution is in the order of 3 to 6 km for both gases. We find the retrieval errors in the lower part of the profiles mostly to be around 15 % for CH4 and below 10 % for N2O. The errors above 25 or 30 km increase to values between 10 and 20 %, except for CH4 from the reduced-resolution period, where the estimated errors stay below 15 %.

As part of European Space Agency's (ESA) climate change initiative, high vertical resolution ozone profiles from three instruments all aboard ESA's Envisat (GOMOS, MIPAS, SCIAMACHY) and ESA's third party missions (OSIRIS, SMR, ACE-FTS) are to be combined in order to create an essential climate variable data record for the last decade. A prerequisite before combining data is the examination of differences and drifts between the data sets. In this paper, we present a detailed analysis of ozone profile differences based on pairwise collocated measurements, including the evolution of the differences with time. Such a diagnosis is helpful to identify strengths and weaknesses of each data set that may vary in time and introduce uncertainties in long-term trend estimates. The analysis reveals that the relative drift between the sensors is not statistically significant for most pairs of instruments. The relative drift values can be used to estimate the added uncertainty in physical trends. The added drift uncertainty is estimated at about 3 % decade−1 (1σ). Larger differences and variability in the differences are found in the lowermost stratosphere (below 20 km) and in the mesosphere.

The GHG-CCI project (http://www.esa-ghg-cci.org/) is one of several projects of the European Space Agency’s (ESA) Climate Change Initiative (CCI). The goal of the CCI is to generate and deliver data sets of various satellite-derived Essential Climate Variables (ECVs) in line with GCOS (Global Climate Observing System) requirements. The “ECV Greenhouse Gases” (ECV GHG) is the global distribution of important climate relevant gases – namely atmospheric CO2 and CH4 - with a quality sufficient to obtain information on regional CO2 and CH4 sources and sinks. The main goal of GHG-CCI is to generate long-term highly accurate and precise time series of global near-surface-sensitive satellite observations of CO2 and CH4, i.e., XCO2 and XCH4, starting with the launch of ESA’s ENVISAT satellite. These products are currently retrieved from SCIAMACHY/ENVISAT (2002-2012) and TANSO-FTS/GOSAT (2009-today) nadir mode observations in the near-infrared/shortwave-infrared spectral region. In addition, other sensors (e.g., IASI and MIPAS) and viewing modes (e.g., SCIAMACHY solar occultation) are also considered and in the future also data from other satellites. The GHG-CCI data products and related documentation are freely available via the GHG-CCI website and yearly updates are foreseen. Here we present an overview about the latest data set (Climate Research Data Package No. 2 (CRDP#2)) and summarize key findings from using satellite CO2 and CH4 retrievals to improve our understanding of the natural and anthropogenic sources and sinks of these important atmospheric greenhouse gases. We also shortly mention ongoing activities related to validation and initial user assessment of CRDP#2 and future plans.

We present the results of an extensive validation program of the most recent version of ozone vertical profiles retrieved with the IMK/IAA (Institute for Meteorology and Climate Research/Instituto de Astrofísica de Andalucía) MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) research level 2 processor from version 5 spectral level 1 data. The time period covered corresponds to the reduced spectral resolution period of the MIPAS instrument, i.e., January 2005–April 2012. The comparison with satellite instruments includes all post-2005 satellite limb and occultation sensors that have measured the vertical profiles of tropospheric and stratospheric ozone: ACE-FTS, GOMOS, HALOE, HIRDLS, MLS, OSIRIS, POAM, SAGE II, SCIAMACHY, SMILES, and SMR. In addition, balloon-borne MkIV solar occultation measurements and ground-based Umkehr measurements have been included, as well as two nadir sensors: IASI and SBUV. For each reference data set, bias determination and precision assessment are performed. Better agreement with reference instruments than for the previous data version, V5R_O3_220 (Laeng et al., 2014), is found: the known high bias around the ozone vmr (volume mixing ratio) peak is significantly reduced and the vertical resolution at 35 km has been improved. The agreement with limb and solar occultation reference instruments that have a known small bias vs. ozonesondes is within 7% in the lower and middle stratosphere and 5% in the upper troposphere. Around the ozone vmr peak, the agreement with most of the satellite reference instruments is within 5%; this bias is as low as 3% for ACE-FTS, MLS, OSIRIS, POAM and SBUV.

Accurate information about uncertainties is required in nearly all data analyses, e.g., inter-comparisons, data assimilation, combined use. Validation of precision estimates (viz., the random component of estimated uncertainty) is important for remote sensing measurements, which provide the information about atmospheric parameters by solving an inverse problem. For the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument, this is a real challenge, due to the dependence of the signal-to-noise ratio (and thus precision estimates) on stellar properties, small number of self-collocated measurements, and growing noise as a function of time due to instrument aging. The estimated ozone uncertainties are small in the stratosphere for bright star occultations, which complicates validation of precision values, given the natural ozone variability. In this paper, we discuss different methods for geophysical validation of precision estimates and their applicability to GOMOS data. We propose a simple method for validation of GOMOS precision estimates for ozone in the stratosphere. This method is based on comparisons of differences in sample variance with differences in uncertainty estimates for measurements from different stars selected in a region of small natural variability. For GOMOS, the difference in sample variances for different stars at tangent altitudes 25–45 km is well explained by the difference in squared precisions, if the stars are not dim. Since this is observed for several stars, and since normalized χ2 is close to 1 for these occultations in the stratosphere, we conclude that the GOMOS precision estimates are realistic in occultations of sufficiently bright stars. For dim stars, errors are overestimated due to improper accounting of the dark charge correction uncertainty in the error budget. The proposed method can also be applied to stratospheric ozone data from other instruments, including multi-instrument analyses.

In this paper, we present a HARMonized dataset of OZone profiles (HARMOZ) based on limb and occultation measurements from Envisat (GOMOS, MIPAS and SCIAMACHY), Odin (OSIRIS, SMR) and SCISAT (ACE-FTS) satellite instruments. These measurements provide high-vertical-resolution ozone profiles covering the altitude range from the upper troposphere up to the mesosphere in years 2001–2012. HARMOZ has been created in the framework of the European Space Agency Climate Change Initiative project. The harmonized dataset consists of original retrieved ozone profiles from each instrument, which are screened for invalid data by the instrument teams. While the original ozone profiles are presented in different units and on different vertical grids, the harmonized dataset is given on a common pressure grid in netCDF (network common data form)-4 format. The pressure grid corresponds to vertical sampling of ~ 1 km below 20 km and 2–3 km above 20 km. The vertical range of the ozone profiles is specific for each instrument, thus all information contained in the original data is preserved. Provided altitude and temperature profiles allow the representation of ozone profiles in number density or mixing ratio on a pressure or altitude vertical grid. Geolocation, uncertainty estimates and vertical resolution are provided for each profile. For each instrument, optional parameters, which are related to the data quality, are also included. For convenience of users, tables of biases between each pair of instruments for each month, as well as bias uncertainties, are provided. These tables characterize the data consistency and can be used in various bias and drift analyses, which are needed, for instance, for combining several datasets to obtain a long-term climate dataset. This user-friendly dataset can be interesting and useful for various analyses and applications, such as data merging, data validation, assimilation and scientific research. The dataset is available at http://www.esa-ozone-cci.org/?q=node/161 or at doi:10.5270/esa-ozone_cci-limb_occultation_profiles-2001_2012-v_1-201308.

We showed to the same observers both dynamic and static 2D patterns that can both evoke distinctive perceptions of motion or optic flow, as if moving in a tunnel or into a dark hole. At all times pupil diameters were monitored with an infrared eye tracker. We found a converging set of results indicating stronger pupil dilations to expansive growth of shapes or optic flows evoking a forward motion into a dark tunnel. Multiple regression analyses showed that the pupil responses to the illusory expanding black holes of static patterns were predicted by the individuals' pupil response to optic flows showing spiraling motion or "free fall" into a black hole. Also, individuals' pupil responses to spiraling motion into dark tunnels predicted the individuals' sense of illusory expansion with the static, illusory expanding, dark holes. This correspondence across individuals between their pupil responses to both dynamic and static, illusory expanding, holes suggests that these percepts reflect a common perceptual mechanism, deriving motion from 2D scenes, and that the observers' pupil adjustments reflect the direction and strength of motion they perceive and the expected outcome of an increase in darkness. [ABSTRACT FROM AUTHOR]