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Variations in the isotopologic composition of water vapour are fundamental for understanding the relative importance of different mechanisms of water vapour transport from the tropical upper troposphere to the lower stratosphere. Previous comparisons obtained from observations of H2O and HDO by satellite instruments showed discrepancies. In this work, newer versions of H2O and HDO retrievals from Envisat/MIPAS and SCISAT/ACE-FTS are compared. Specifically, MIPAS-IMK V5, MIPAS-ESA V8 and ACE-FTS V4.1/4.2 for the common period from February 2004 to April 2012 are compared for the first time through a profile-to-profile approach and comparison based on climatological structures. The comparison is essential for the scientific community to assess the quality of new satellite data products, a necessary procedure to validate further scientific work. Averaged stratospheric H2O profiles reveal general good agreement between 16 and 30 km. Biases derived from the profile-to-profile comparison are around zero between 16 and 30 km for MIPAS-IMK and ACE-FTS comparison. For HDO and δD, low biases are found in the MIPAS-ESA and ACE-FTS comparison in the same range of altitudes, even if associated with a larger de-biased standard deviation. The zonally averaged cross sections of H2O and HDO exhibit the expected distribution that has been established in previous studies. For δD the tropical depletion in MIPAS-ESA occurs at the top of the dynamical tropopause, but this minimum is found at higher altitudes in the ACE-FTS and MIPAS-IMK dataset. The tape recorder signal is present in H2O and HDO for the three databases with slight quantitative differences. The δD annual variation for ACE-FTS data and MIPAS-ESA data is weaker compared to the MIPAS-IMK dataset, which shows a coherent tape recorder signal clearly detectable up to at least 30 km. The observed differences in the climatological δD composites between databases could lead to different interpretations regarding the water vapour transport processes toward the stratosphere. Therefore, it is important to further improve the quality of level 2 products.

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 Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) is currently providing the only measurements of vertically resolved chlorodifluoromethane (HCFC-22) from space. This study assesses the ACE-FTS HCFC-22 v5.2 product in the upper troposphere and lower stratosphere, as well as simulations of HCFC-22 from a 39-year specified dynamics run of the Canadian Middle Atmosphere Model (CMAM39) in the same region. In general, ACE-FTS HCFC-22 observations tend to agree with subsampled CMAM39 data to within ±5 %, except for between ∼ 15 and 25 km in the extratropical regions where ACE-FTS exhibits a negative bias of 5 %–30 % and near 6 km in the tropics where ACE-FTS exhibits a bias of −15 %. When comparing against correlative satellite, aircraft, and balloon data, ACE-FTS typically exhibits a low bias on the order of 0 %–10 % between ∼ 5 and 15 km and is within ±15 % between ∼ 15 and 25 km. ACE-FTS, CMAM39, and surface flask measurements from the NOAA Global Monitoring Laboratory's surface air-sampling network all exhibit consistent tropospheric HCFC-22 trends ranging between 6.8 and 7.8 ppt yr−1 (within 95 % confidence) for 2004–2012 and between 3.1 and 4.7 ppt yr−1 (within 95 % confidence) for 2012–2018. Interhemispheric differences (IHDs) of HCFC-22 were also derived using ACE-FTS, NOAA, and CMAM39 data, and all three yielded consistent and correlated (r≥0.42) IHD time series, with the results indicating that surface IHD values decreased at a rate of 2.2 ± 1.1 ppt per decade between 2004 and 2018.

Observational monitoring of the stratospheric transport circulation, the Brewer–Dobson circulation (BDC), is crucial to estimate any decadal to long-term changes therein, a prerequisite to interpret trends in stratospheric composition and to constrain the consequential impacts on climate. The transport time along the BDC (i.e. the mean stratospheric age of air, AoA) can best be deduced from trace gas measurements of tracers which increase linearly with time and are chemically passive. The gas sulfur hexafluoride (SF6) is often used to deduce AoA because it has been increasing monotonically since the ∼1950s, and previously its chemical sinks in the mesosphere have been assumed to be negligible for AoA estimates. However, recent studies have shown that the chemical sinks of SF6 are stronger than assumed and become increasingly relevant with rising SF6 concentrations. To adjust biases in AoA that result from the chemical SF6 sinks, we here propose a simple correction scheme for SF6-based AoA estimates accounting for the time-dependent effects of chemical sinks. The correction scheme is based on theoretical considerations with idealized assumptions, resulting in a relation between ideal AoA and apparent AoA which is a function of the tropospheric reference time series of SF6 and of the AoA-dependent effective lifetime of SF6. The correction method is thoroughly tested within a self-consistent data set from a climate model that includes explicit calculation of chemical SF6 sinks. It is shown within the model that the correction successfully reduces biases in SF6-based AoA to less than 5 % for mean ages below 5 years. Tests using only subsampled data for deriving the fit coefficients show that applying the correction scheme even with imperfect knowledge of the sink is far superior to not applying a sink correction. Furthermore, we show that based on currently available measurements, we are not able to constrain the fit parameters of the correction scheme based on observational data alone. However, the model-based correction curve lies within the observational uncertainty, and we thus recommend using the model-derived fit coefficients until more high-quality measurements are able to further constrain the correction scheme. The application of the correction scheme to AoA from satellites and in situ data suggests that it is highly beneficial to reconcile different observational estimates of mean AoA.

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.

Motivated by an improved European Space Agency (ESA) version of calibrated Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) spectra (version 8.03), we have released version 8 of MIPAS temperatures and pointing information retrieved from 2005–2012 MIPAS measurements at 12–15 µm in the Middle Atmosphere (MA), Upper Atmosphere (UA) and Noctilucent Cloud (NLC) measurement modes. The Institute of Meteorology and Climate Research–Instituto de Astrofisica de Andalucia (IMK–IAA) retrieval processor in use considers non-local thermodynamic equilibrium (non-LTE) emission explicitly for each limb scan. This non-LTE treatment is essential to obtain accurate temperatures above the mid-mesosphere because at the altitudes covered, up to 115 km, the simplified climatology-based non-LTE treatment employed for the Nominal (NOM) measurements is insufficient. Other updates in MA/UA/NLC version 8 non-LTE temperature retrievals from previous data releases include more realistic atomic oxygen and carbon dioxide abundances, an updated set of spectroscopic data, an improved spectral shift retrieval, a continuum retrieval extended to altitudes up to 58 km, consideration of an altitude-dependent radiance offset retrieval, the use of wider microwindows above 85 km to capture the offset, an improved accuracy in forward model calculations, new a priori temperature information, improved temperature horizontal gradient retrievals and the use of MIPAS version 5 interfering species where available. The resulting MIPAS MA/UA/NLC IMK–IAA temperature dataset is reliable for scientific analysis in the full measurement vertical range for the MA (18–102 km) and the NLC (39–102 km) observations and from 42 to 115 km for the UA observations. The random temperature errors, dominated by the instrumental noise, are typically less than 1 K below 60 km, 1–3 K at 60–70 km, 3–5 K at 70–90 km, 6–8 K at 90–100 km, 8–12 K at 100–105 km and 12–20 K at 105–115 km. Random pointing correction errors, also mainly arising from instrumental noise, are on average 50 m for tangent altitudes up to 60 km and decrease linearly to values smaller than 20 m for altitudes above 95 km. The vertical resolution is 3 km at altitudes below 50 km, 3–5 km at 50–70 km, 4–6 km at 70–90 km, 6–10 km at 90–100 km and 8–11 km at 100–115 km. The systematic errors in retrieved temperatures below 75 km are driven by uncertainties in the CO2 spectroscopic data and, above 80 km, by uncertainties in the non-LTE model parameters (including collisional rates and atomic oxygen abundance) and the CO2 abundance. These lead to systematic temperature errors of less than 0.7 K below 55 km, 1 K at 60–80 km, 1–2 K at 80–90 km, 3 K at 95 km, 6–8 K at 100 km, 10–20 K at 105 km and 20–30 K at 115 km. Systematic errors in the tangent altitude correction, mainly arising from CO2 spectroscopic uncertainties, are 250 m at 20 km, 200 m at 40–60 km, 100 m at 80 km and smaller than 50 m above 90 km. The consistency between the MA/UA/NLC and the NOM IMK–IAA datasets is excellent below 70 km (typical 0.5–1 K differences). The comparison of this temperature dataset with co-located Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature measurements shows excellent agreement, with differences typically within 1.5 K below 90 km, 1–3 K at 90–95 km, 1–5 K at 95–100 km, 1–8 K at 100–105 km and 1–10 K above. The agreement with SABER improves with respect to previous MIPAS IMK–IAA data versions.

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.

Satellite data records of stratospheric water vapour have been compared to balloon-borne frost point hygrometer (FP) profiles that are coincident in space and time. The satellite data records of 15 different instruments cover water vapour data available from January 2000 through December 2016. The hygrometer data are from 27 stations all over the world in the same period. For the comparison, real or constructed averaging kernels have been applied to the hygrometer profiles to adjust them to the measurement characteristics of the satellite instruments. For bias evaluation, we have compared satellite profiles averaged over the available temporal coverage to the means of coincident FP profiles for individual stations. For drift determinations, we analysed time series of relative differences between spatiotemporally coincident satellite and hygrometer profiles at individual stations. In a synopsis we have also calculated the mean biases and drifts (and their respective uncertainties) for each satellite record over all applicable hygrometer stations in three altitude ranges (10–30 hPa, 30–100 hPa, and 100 hPa to tropopause). Most of the satellite data have biases % and average drifts % yr−1 in at least one of the respective altitude ranges. Virtually all biases are significant in the sense that their uncertainty range in terms of twice the standard error of the mean does not include zero. Statistically significant drifts (95 % confidence) are detected for 35 % of the ≈ 1200 time series of relative differences between satellites and hygrometers.

New global nitric oxide (NO) volume mixing ratio and lower-thermospheric temperature data products, retrieved from Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) spectra with the Institute of Meteorology and Climate Research and Instituto de Astrofísica de Andalucía (IMK-IAA) MIPAS data processor, have been released. The dataset covers the entire Envisat mission lifetime and includes retrieval results from all MIPAS observation modes. The data are based on European Space Agency (ESA) version 8 calibration and were processed using an improved retrieval approach compared to previous versions, specifically regarding the choice and construction of the a priori and atmospheric parameter profiles, the treatment of horizontal inhomogeneities, the treatment of the radiance offset correction, and the selection of optimized numerical settings. NO retrieval errors in individual observations are dominated by measurement noise and range from 5 % to 50 % in the stratosphere and thermosphere and reach 40 % to 90 % in the mesosphere. Systematic errors are typically within 10 %–30 %. Lower-thermospheric temperature errors are 5 to 50 K with a systematic component of around 20 K, the latter being dominated by non-thermodynamic equilibrium (non-LTE)-related uncertainties. NO data from different observation modes are consistent within 5 %–10 %. MIPAS version 8 temperatures have a better representation of the diurnal tide in the lower thermosphere compared to previous data versions. The new MIPAS temperatures are systematically warmer than results from the empirical US Naval Research Laboratory Mass Spectrometer Incoherent Scatter Radar (NRLMSIS) version 2.0 model by 30 to 80 K in the 100–120 km region and are colder above.

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 paper describes the error estimation for temperature and trace gas mixing ratios retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb emission spectra. The following error sources are taken into account: measurement noise, propagated temperature and pointing noise, uncertainties in the abundances of spectrally interfering species, instrument line shape errors, and spectroscopic data uncertainties in terms of line intensities and broadening coefficients. Furthermore, both the direct impact of volatile and persistent gain calibration uncertainties, offset calibration, and spectral calibration uncertainties, as well as their impact through propagated calibration-related temperature and pointing uncertainties, are considered. An error source specific to the MIPAS upper atmospheric observation mode is the propagation of the smoothing error crosstalk of the combined NO and temperature retrieval. Whenever non-local thermodynamic equilibrium modelling is used in the retrieval, related kinetic constants and mixing ratios of species involved in the modelling of populations of excitational states also contribute to the error budget. Both generalized Gaussian error propagation and perturbation studies are used to estimate the error components. Error correlations are taken into account. Estimated uncertainties are provided for a multitude of atmospheric conditions. Some error sources were found to contribute both to the random and the systematic component of the total estimated error. The sequential nature of the MIPAS retrievals gives rise to entangled errors. These are caused by error sources that affect the uncertainty in the final data product via multiple pathways, i.e., on the one hand, directly, and, on the other hand, via errors caused in a preceding retrieval step. These errors tend to partly compensate for each other. The hard-to-quantify effect of the horizontally non-homogeneous atmosphere and unknown error correlations of spectroscopic data are considered to be the major limitations of the MIPAS error estimation.

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.

Measurements of long-lived trace gases (SF6, CFC-11, CFC-12, HCFC-22, CCl4, N2O, CH4, H2O, and CO) performed with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) have been used to infer the stratospheric and mesospheric meridional circulation. The MIPAS data set covers the time period from July 2002 to April 2012. The method used for this purpose was the direct inversion of the two-dimensional continuity equation for the concentrations of trace gases and air density. This inversion predicts an “effective velocity” that gives the best fit for the evolution of the concentrations on the assumption that an explicit treatment of Fickian diffusion can be neglected. These effective velocity fields are used to characterize the mean meridional circulation. Multiannual monthly mean effective velocity fields are presented, along with their variabilities. According to this measure, the stratospheric circulation is found to be highly variable over the year, with a quite robust annual cycle. The new method allows us to track the evolution of various circulation patterns over the year in more detail than before. According to the effective velocity characterization of the circulation, the deep branch of the Brewer–Dobson circulation and the mesospheric overturning pole-to-pole circulation are not separate but intertwined phenomena. The latitude of stratospheric uplift in the middle and upper stratosphere is found to be quite variable and is not always found at equatorial latitudes. The usual schematic of stratospheric circulation with the deep and the shallow branch of the Brewer–Dobson circulation and the mesospheric overturning circulation is an idealization which best describes the observed atmosphere around equinox. Sudden stratospheric warmings and the quasi-biennial oscillation cause a pronounced year-to-year variability of the meridional circulation.

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.

A ground-based, high-spectral-resolution Fourier transform infrared (FTIR) spectrometer has been operational in Addis Ababa, Ethiopia (9.01∘ N latitude, 38.76∘ E longitude; 2443 m altitude above sea level), since May 2009 to obtain information on column abundances and profiles of various constituents in the atmosphere. Vertical profile and column abundances of methane and nitrous oxide are derived from solar absorption measurements taken by FTIR for a period that covers May 2009 to March 2013 using the retrieval code PROFFIT (V9.5). A detailed error analysis of CH4 and N2O retrieval are performed. Averaging kernels of the target gases shows that the major contribution to the retrieved information comes from the measurement. Thus, average degrees of freedom for signals are found to be 2.1 and 3.4, from the retrieval of CH4 and N2O for the total observed FTIR spectra. Methane and nitrous oxide volume mixing ratio (VMR) profiles and column amounts retrieved from FTIR spectra are compared with data from the reduced spectral resolution Institute of Meteorology and Climate Research/Instituto de Astrofísica de Andalucía (IMK/IAA) MIPAS (Version V5R_CH4_224 and V5R_N2O_224), the Microwave Limb Sounder (MLS) (MLS v3.3 of N2O and CH4 derived from MLS v3.3 products of CO, N2O, and H2O), and the Atmospheric Infrared Sounder (AIRS) sensors on board satellites. The averaged mean relative difference between FTIR methane and the three correlative instruments MIPAS, MLS, and AIRS are 4.2 %, 5.8 %, and 5.3 % in the altitude ranges of 20 to 27 km, respectively. However, the biases below 20 km are negative, which indicates the profile of CH4 from FTIR is less than the profiles derived from correlative instruments by −4.9 %, −1.8 %, and −2.8 %. The averaged positive bias between FTIR nitrous oxide and correlative instrument, MIPAS, in the altitude range of 20 to 27 km is 7.8 %, and a negative bias of −4 % at altitudes below 20 km. An averaged positive bias of 9.3 % in the altitude range of 17 to 27 km is obtained for FTIR N2O with MLS. In all the comparisons of CH4 from FTIR with data from MIPAS, MLS, and AIRS, sensors on board satellites indicate a negative bias below 20 km and a positive bias above 20 km. The mean error between partial-column amounts of methane from MIPAS and the ground-based FTIR is −5.5 %, with a standard deviation of 5 % that shows very good agreement as exhibited by relative differences between vertical profiles. Thus, the retrieved CH4 and N2O VMR and column amounts from Addis Ababa, tropical site, is found to exhibit very good agreement with all coincident satellite observations. Therefore, the bias obtained from the comparison is comparable to the precision of FTIR measurement, which allows the use of data in further scientific studies as it represents a unique environment of tropical Africa, a region poorly investigated in the past.

The annual variation of δD in the tropical lower stratosphere is a critical indicator for the relative importance of different processes contributing to the transport of water vapour through the cold tropical tropopause region into the stratosphere. Distinct observational discrepancies of the δD annual variation were visible in the works of Steinwagner et al. (2010) and Randel et al. (2012). Steinwagner et al. (2010) analysed MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) observations retrieved with the IMK/IAA (Institut für Meteorologie und Klimaforschung in Karlsruhe, Germany, in collaboration with the Instituto de Astrofísica de Andalucía in Granada, Spain) processor, while Randel et al. (2012) focused on ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Here we reassess the discrepancies based on newer MIPAS (IMK/IAA) and ACE-FTS data sets, also showing for completeness results from SMR (Sub-Millimetre Radiometer) observations and a ECHAM/MESSy (European Centre for Medium-Range Weather Forecasts Hamburg and Modular Earth Submodel System) Atmospheric Chemistry (EMAC) simulation (Eichinger et al., 2015b). Similar to the old analyses, the MIPAS data set yields a pronounced annual variation (maximum about 75 ‰), while that derived from the ACE-FTS data set is rather weak (maximum about 25 ‰). While all data sets exhibit the phase progression typical for the tape recorder, the annual maximum in the ACE-FTS data set precedes that in the MIPAS data set by 2 to 3 months. We critically consider several possible reasons for the observed discrepancies, focusing primarily on the MIPAS data set. We show that the δD annual variation in the MIPAS data up to an altitude of 40 hPa is substantially impacted by a “start altitude effect”, i.e. dependency between the lowermost altitude where MIPAS retrievals are possible and retrieved data at higher altitudes. In itself this effect does not explain the differences with the ACE-FTS data. In addition, there is a mismatch in the vertical resolution of the MIPAS HDO and H2O data (being consistently better for HDO), which actually results in an artificial tape-recorder-like signal in δD. Considering these MIPAS characteristics largely removes any discrepancies between the MIPAS and ACE-FTS data sets and shows that the MIPAS data are consistent with a δD tape recorder signal with an amplitude of about 25 ‰ in the lowermost stratosphere.

We have performed backward trajectory calculations and simulations with the three-dimensional Chemical Lagrangian Model of the Stratosphere (CLaMS) for two succeeding monsoon seasons using artificial tracers of air mass origin. With these tracers we trace back the origin of young air masses (age  months) at the top of the Asian monsoon anticyclone and of air masses within the tropical pipe (6 months < age  months) during summer 2008. The occurrence of young air masses ( months) at the top of the Asian monsoon anticyclone up to ∼460 K is in agreement with satellite measurements of chlorodifluoromethane (HCFC-22) by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument. HCFC-22 can be considered as a regional tracer for continental eastern Asia and the Middle East as it is mainly emitted in this region. Our findings show that the transport of air masses from boundary layer sources in the region of the Asian monsoon into the tropical pipe occurs in three distinct steps. First, very fast uplift in “a convective range” transports air masses up to 360 K potential temperature within a few days. Second, air masses are uplifted from about 360 K up to 460 K within “an upward spiralling range” within a few months. The large-scale upward spiral extends from northern Africa to the western Pacific. The air masses are transported upwards by diabatic heating with a rate of up to 1–1.5 K per day, implying strong vertical transport above the Asian monsoon anticyclone. Third, transport of air masses occurs within the tropical pipe up to 550 K associated with the large-scale Brewer–Dobson circulation within ∼1 year. In the upward spiralling range, air masses are uplifted by diabatic heating across the (lapse rate) tropopause, which does not act as a transport barrier, in contrast to the extratropical tropopause. Further, in the upward spiralling range air masses from inside the Asian monsoon anticyclone are mixed with air masses convectively uplifted outside the core of the Asian monsoon anticyclone in the tropical adjacent regions. Moreover, the vertical transport of air masses from the Asian monsoon anticyclone into the tropical pipe is weak in terms of transported air masses compared to the transport from the monsoon anticyclone into the northern extratropical lower stratosphere. Air masses from the Asian monsoon anticyclone (India/China) contribute a minor fraction to the composition of air within the tropical pipe at 550 K (6 %), and the major fractions are from Southeast Asia (16 %) and the tropical Pacific (15 %).

Within the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), profile-to-profile comparisons of stratospheric and lower mesospheric water vapour were performed by considering 33 data sets derived from satellite observations of 15 different instruments. These comparisons aimed to provide a picture of the typical biases and drifts in the observational database and to identify data-set-specific problems. The observational database typically exhibits the largest biases below 70 hPa, both in absolute and relative terms. The smallest biases are often found between 50 and 5 hPa. Typically, they range from 0.25 to 0.5 ppmv (5 % to 10 %) in this altitude region, based on the 50 % percentile over the different comparison results. Higher up, the biases increase with altitude overall but this general behaviour is accompanied by considerable variations. Characteristic values vary between 0.3 and 1 ppmv (4 % to 20 %). Obvious data-set-specific bias issues are found for a number of data sets. In our work we performed a drift analysis for data sets overlapping for a period of at least 36 months. This assessment shows a wide range of drifts among the different data sets that are statistically significant at the 2σ uncertainty level. In general, the smallest drifts are found in the altitude range between about 30 and 10 hPa. Histograms considering results from all altitudes indicate the largest occurrence for drifts between 0.05 and 0.3 ppmv decade−1. Comparisons of our drift estimates to those derived from comparisons of zonal mean time series only exhibit statistically significant differences in slightly more than 3 % of the comparisons. Hence, drift estimates from profile-to-profile and zonal mean time series comparisons are largely interchangeable. As for the biases, a number of data sets exhibit prominent drift issues. In our analyses we found that the large number of MIPAS data sets included in the assessment affects our general results as well as the bias summaries we provide for the individual data sets. This is because these data sets exhibit a relative similarity with respect to the remaining data sets, despite the fact that they are based on different measurement modes and different processors implementing different retrieval choices. Because of that, we have by default considered an aggregation of the comparison results obtained from MIPAS data sets. Results without this aggregation are provided on multiple occasions to characterise the effects due to the numerous MIPAS data sets. Among other effects, they cause a reduction of the typical biases in the observational database.

Within the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), we evaluated five data sets of δD(H2O) obtained from observations by Odin/SMR (Sub-Millimetre Radiometer), Envisat/MIPAS (Environmental Satellite/Michelson Interferometer for Passive Atmospheric Sounding), and SCISAT/ACE-FTS (Science Satellite/Atmospheric Chemistry Experiment – Fourier Transform Spectrometer) using profile-to-profile and climatological comparisons. These comparisons aimed to provide a comprehensive overview of typical uncertainties in the observational database that could be considered in the future in observational and modelling studies. Our primary focus is on stratospheric altitudes, but results for the upper troposphere and lower mesosphere are also shown. There are clear quantitative differences in the measurements of the isotopic ratio, mainly with regard to comparisons between the SMR data set and both the MIPAS and ACE-FTS data sets. In the lower stratosphere, the SMR data set shows a higher depletion in δD than the MIPAS and ACE-FTS data sets. The differences maximise close to 50 hPa and exceed 200 ‰. With increasing altitude, the biases decrease. Above 4 hPa, the SMR data set shows a lower δD depletion than the MIPAS data sets, occasionally exceeding 100 ‰. Overall, the δD biases of the SMR data set are driven by HDO biases in the lower stratosphere and by H2O biases in the upper stratosphere and lower mesosphere. In between, in the middle stratosphere, the biases in δD are the result of deviations in both HDO and H2O. These biases are attributed to issues with the calibration, in particular in terms of the sideband filtering, and uncertainties in spectroscopic parameters. The MIPAS and ACE-FTS data sets agree rather well between about 100 and 10 hPa. The MIPAS data sets show less depletion below approximately 15 hPa (up to about 30 ‰), due to differences in both HDO and H2O. Higher up this behaviour is reversed, and towards the upper stratosphere the biases increase. This is driven by increasing biases in H2O, and on occasion the differences in δD exceed 80 ‰. Below 100 hPa, the differences between the MIPAS and ACE-FTS data sets are even larger. In the climatological comparisons, the MIPAS data sets continue to show less depletion in δD than the ACE-FTS data sets below 15 hPa during all seasons, with some variations in magnitude. The differences between the MIPAS and ACE-FTS data have multiple causes, such as differences in the temporal and spatial sampling (except for the profile-to-profile comparisons), cloud influence, vertical resolution, and the microwindows and spectroscopic database chosen. Differences between data sets from the same instrument are typically small in the stratosphere. Overall, if the data sets are considered together, the differences in δD among them in key areas of scientific interest (e.g. tropical and polar lower stratosphere, lower mesosphere, and upper troposphere) are too large to draw robust conclusions on atmospheric processes affecting the water vapour budget and distribution, e.g. the relative importance of different mechanisms transporting water vapour into the stratosphere.

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 %.

Time series of stratospheric and lower mesospheric water vapour using 33 data sets from 15 different satellite instruments were compared in the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II). This comparison aimed to provide a comprehensive overview of the typical uncertainties in the observational database that can be considered in the future in observational and modelling studies, e.g addressing stratospheric water vapour trends. The time series comparisons are presented for the three latitude bands, the Antarctic (80°–70° S), the tropics (15° S–15° N) and the Northern Hemisphere mid-latitudes (50°–60° N) at four different altitudes (0.1, 3, 10 and 80 hPa) covering the stratosphere and lower mesosphere. The combined temporal coverage of observations from the 15 satellite instruments allowed the consideration of the time period 1986–2014. In addition to the qualitative comparison of the time series, the agreement of the data sets is assessed quantitatively in the form of the spread (i.e. the difference between the maximum and minimum volume mixing ratios among the data sets), the (Pearson) correlation coefficient and the drift (i.e. linear changes of the difference between time series over time). Generally, good agreement between the time series was found in the middle stratosphere while larger differences were found in the lower mesosphere and near the tropopause. Concerning the latitude bands, the largest differences were found in the Antarctic while the best agreement was found for the tropics. From our assessment we find that most data sets can be considered in future observational and modelling studies, e.g. addressing stratospheric and lower mesospheric water vapour variability and trends, if data set specific characteristics (e.g. drift) and restrictions (e.g. temporal and spatial coverage) are taken into account.

Trend estimates with different signs are reported in the literature for lower stratospheric water vapour considering the time period between the late 1980s and 2010. The NOAA (National Oceanic and Atmospheric Administration) frost point hygrometer (FPH) observations at Boulder (Colorado, 40.0° N, 105.2° W) indicate positive trends (about 0.1 to 0.45 ppmv decade−1). On the contrary, negative trends (approximately −0.2 to −0.1 ppmv decade−1) are derived from a merged zonal mean satellite data set for a latitude band around the Boulder latitude. Overall, the trend differences between the two data sets range from about 0.3 to 0.5 ppmv decade−1, depending on altitude. It has been proposed that a possible explanation for these discrepancies is a different temporal behaviour at Boulder and the zonal mean. In this work we investigate trend differences between Boulder and the zonal mean using primarily simulations from ECHAM/MESSy (European Centre for Medium-Range Weather Forecasts Hamburg/Modular Earth Submodel System) Atmospheric Chemistry (EMAC), WACCM (Whole Atmosphere Community Climate Model), CMAM (Canadian Middle Atmosphere Model) and CLaMS (Chemical Lagrangian Model of the Stratosphere). On shorter timescales we address this aspect also based on satellite observations from UARS/HALOE (Upper Atmosphere Research Satellite/Halogen Occultation Experiment), Envisat/MIPAS (Environmental Satellite/Michelson Interferometer for Passive Atmospheric Sounding) and Aura/MLS (Microwave Limb Sounder). Overall, both the simulations and observations exhibit trend differences between Boulder and the zonal mean. The differences are dependent on altitude and the time period considered. The model simulations indicate only small trend differences between Boulder and the zonal mean for the time period between the late 1980s and 2010. These are clearly not sufficient to explain the discrepancies between the trend estimates derived from the FPH observations and the merged zonal mean satellite data set. Unless the simulations underrepresent variability or the trend differences originate from smaller spatial and temporal scales than resolved by the model simulations, trends at Boulder for this time period should also be quite representative for the zonal mean and even other latitude bands. Trend differences for a decade of data are larger and need to be kept in mind when comparing results for Boulder and the zonal mean on this timescale. Beyond that, we find that the trend estimates for the time period between the late 1980s and 2010 also significantly differ among the simulations. They are larger than those derived from the merged satellite data set and smaller than the trend estimates derived from the FPH observations.

Stratospheric transport in global circulation models and chemistry–climate models is an important component in simulating the recovery of the ozone layer as well as changes in the climate system. The Brewer–Dobson circulation is not well constrained by observations and further investigation is required to resolve uncertainties related to the mechanisms driving the circulation. This study has assessed the specified dynamics mode of the Canadian Middle Atmosphere Model (CMAM30) by comparing to the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) profile measurements of CFC-11 (CCl3F), CFC-12 (CCl2F2), and N2O. In the CMAM30 specified dynamics simulation, the meteorological fields are nudged using the ERA-Interim reanalysis and a specified tracer was employed for each species, with hemispherically defined surface measurements used as the boundary condition. A comprehensive sampling technique along the line of sight of the ACE-FTS measurements has been utilized to allow for direct comparisons between the simulated and measured tracer concentrations. The model consistently overpredicts tracer concentrations of CFC-11, CFC-12, and N2O in the lower stratosphere, particularly in the northern hemispheric winter and spring seasons. The three mixing barriers investigated, including the polar vortex, the extratropical tropopause, and the tropical pipe, show that there are significant inconsistencies between the measurements and the simulations. In particular, the CMAM30 simulation underpredicts mixing efficiency in the tropical lower stratosphere during the June–July–August season.

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.

As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC) and provide datasets that can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated with respect to both the Aura Microwave Limb Sounder (MLS; from 2004 onwards) and each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically ∼ 1%. Most of the datasets start in or after 2004 and show annual increases in H2O of 0–1 % yr−1. In particular, MLS shows a trend of between 0.5 % yr−1 and 0.7 % yr−1 at the comparison sites. However, the two longest measurement datasets used here, with measurements back to 1996, show much smaller trends of +0.1 % yr−1 (at Mauna Loa, Hawaii) and −0.1 % yr−1 (at Lauder, New Zealand).

In response to global warming, the Brewer–Dobson circulation in the stratosphere is expected to accelerate and the mean transport time of air along this circulation to decrease. This would imply a negative stratospheric age of air trend, i.e. an air parcel would need less time to travel from the tropopause to any point in the stratosphere. Age of air as inferred from tracer observations, however, shows zero to positive trends in the northern mid-latitude stratosphere and zonally asymmetric patterns. Using satellite observations and model calculations we show that the observed latitudinal and vertical patterns of the decadal changes of age of air in the lower to middle stratosphere during the period 2002–2012 are predominantly caused by a southward shift of the circulation pattern by about 5°. After correction for this shift, the observations reveal a hemispherically almost symmetric decrease of age of air in the lower to middle stratosphere up to 800 K of up to −0.25 years over the 2002–2012 period with strongest decrease in the northern tropics. This net change is consistent with long-term trends from model predictions.

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.

We compare simulations from three high-top (with upper lid above 120 km) and five medium-top (with upper lid around 80 km) atmospheric models with observations of odd nitrogen (NOx = NO + NO2), temperature, and carbon monoxide from seven satellite instruments (ACE-FTS on SciSat, GOMOS, MIPAS, and SCIAMACHY on Envisat, MLS on Aura, SABER on TIMED, and SMR on Odin) during the Northern Hemisphere (NH) polar winter 2008/2009. The models included in the comparison are the 3-D chemistry transport model 3dCTM, the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model, FinROSE, the Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA), the modelling tools for SOlar Climate Ozone Links studies (SOCOL and CAO-SOCOL), and the Whole Atmosphere Community Climate Model (WACCM4). The comparison focuses on the energetic particle precipitation (EPP) indirect effect, that is, the polar winter descent of NOx largely produced by EPP in the mesosphere and lower thermosphere. A particular emphasis is given to the impact of the sudden stratospheric warming (SSW) in January 2009 and the subsequent elevated stratopause (ES) event associated with enhanced descent of mesospheric air. The chemistry climate model simulations have been nudged toward reanalysis data in the troposphere and stratosphere while being unconstrained above. An odd nitrogen upper boundary condition obtained from MIPAS observations has further been applied to medium-top models. Most models provide a good representation of the mesospheric tracer descent in general, and the EPP indirect effect in particular, during the unperturbed (pre-SSW) period of the NH winter 2008/2009. The observed NOx descent into the lower mesosphere and stratosphere is generally reproduced within 20 %. Larger discrepancies of a few model simulations could be traced back either to the impact of the models' gravity wave drag scheme on the polar wintertime meridional circulation or to a combination of prescribed NOx mixing ratio at the uppermost model layer and low vertical resolution. In March–April, after the ES event, however, modelled mesospheric and stratospheric NOx distributions deviate significantly from the observations. The too-fast and early downward propagation of the NOx tongue, encountered in most simulations, coincides with a temperature high bias in the lower mesosphere (0.2–0.05 hPa), likely caused by an overestimation of descent velocities. In contrast, upper-mesospheric temperatures (at 0.05–0.001 hPa) are generally underestimated by the high-top models after the onset of the ES event, being indicative for too-slow descent and hence too-low NOx fluxes. As a consequence, the magnitude of the simulated NOx tongue is generally underestimated by these models. Descending NOx amounts simulated with medium-top models are on average closer to the observations but show a large spread of up to several hundred percent. This is primarily attributed to the different vertical model domains in which the NOx upper boundary condition is applied. In general, the intercomparison demonstrates the ability of state-of-the-art atmospheric models to reproduce the EPP indirect effect in dynamically and geomagnetically quiescent NH winter conditions. The encountered differences between observed and simulated NOx, CO, and temperature distributions during the perturbed phase of the 2009 NH winter, however, emphasize the need for model improvements in the dynamical representation of elevated stratopause events in order to allow for a better description of the EPP indirect effect under these particular conditions.

In the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), the amplitudes and phases of the annual, semi-annual and quasi-biennial variation in stratospheric and lower mesospheric water were compared using 30 data sets from 13 different satellite instruments. These comparisons aimed to provide a comprehensive overview of the typical uncertainties in the observational database which can be considered in subsequent observational and modelling studies. For the amplitudes, a good agreement of their latitude and altitude distribution was found. Quantitatively there were differences in particular at high latitudes, close to the tropopause and in the lower mesosphere. In these regions, the standard deviation over all data sets typically exceeded 0.2 ppmv for the annual variation and 0.1 ppmv for the semi-annual and quasi-biennial variation. For the phase, larger differences between the data sets were found in the lower mesosphere. Generally the smallest phase uncertainties can be observed in regions where the amplitude of the variability is large. The standard deviations of the phases for all data sets were typically smaller than a month for the annual and semi-annual variation and smaller than 5 months for the quasi-biennial variation. The amplitude and phase differences among the data sets are caused by a combination of factors. In general, differences in the temporal variation of systematic errors and in the observational sampling play a dominant role. In addition, differences in the vertical resolution of the data, the considered time periods and influences of clouds, aerosols as well as non-local thermodynamic equilibrium (NLTE) effects cause differences between the individual data sets.

We present a global carbonyl sulfide (OCS) data set covering the period June 2002 to April 2012, derived from FTIR (Fourier transform infrared) limb emission spectra measured with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on the ENVISAT satellite. The vertical resolution is 4–5 km in the height region 6–15 km and 15 at 40 km altitude. The total estimated error amounts to 40–50 pptv between 10 and 20 km and to 120 pptv at 40 km altitude. MIPAS OCS data show no systematic bias with respect to balloon observations, with deviations mostly below ±50 pptv. However, they are systematically higher than the OCS volume mixing ratios of the ACE-FTS instrument on SCISAT, with maximum deviations of up to 100 pptv in the altitude region 13–16 km. The data set of MIPAS OCS exhibits only moderate interannual variations and low interhemispheric differences. Average concentrations at 10 km altitude range from 480 pptv at high latitudes to 500–510 pptv in the tropics and at northern mid-latitudes. Seasonal variations at 10 km altitude amount to up to 35 pptv in the Northern and up to 15 pptv in the Southern Hemisphere. Northern hemispheric OCS abundances at 10 km altitude peak in June in the tropics and around October at high latitudes, while the respective southern hemispheric maxima were observed in July and in November. Global OCS distributions at 250 hPa (∼ 10–11 km) show enhanced values at low latitudes, peaking during boreal summer above the western Pacific and the Indian Ocean, which indicates oceanic release. Further, a region of depleted OCS amounts extending from Brazil to central and southern Africa was detected at this altitude, which is most pronounced in austral summer. This depletion is related to seasonally varying vegetative uptake by the tropical forests. Typical signatures of biomass burning like the southern hemispheric biomass burning plume are not visible in MIPAS data, indicating that this process is only a minor source of upper tropospheric OCS. At the 150 hPa level (∼ 13–14 km) enhanced amounts of OCS were also observed inside the Asian monsoon anticyclone, but this enhancement is not especially outstanding compared to other low latitude regions at the same altitude. At the 80 hPa level (∼ 17–18 km), equatorward transport of mid-latitude air masses containing lower OCS amounts around the summertime anticyclones was observed. A significant trend could not be detected in upper tropospheric MIPAS OCS amounts, which points to globally balanced sources and sinks. Simulations with the ECHAM-MESSy model reproduce the observed latitudinal cross sections fairly well.

We have used the Whole Atmosphere Community Climate Model (WACCM), with an updated treatment of loss processes, to determine the atmospheric lifetime of sulfur hexafluoride (SF6). The model includes the following SF6 removal processes: photolysis, electron attachment and reaction with mesospheric metal atoms. The Sodankylä Ion Chemistry (SIC) model is incorporated into the standard version of WACCM to produce a new version with a detailed D region ion chemistry with cluster ions and negative ions. This is used to determine a latitude- and altitude-dependent scaling factor for the electron density in the standard WACCM in order to carry out multi-year SF6 simulations. The model gives a mean SF6 lifetime over an 11-year solar cycle (τ) of 1278 years (with a range from 1120 to 1475 years), which is much shorter than the currently widely used value of 3200 years, due to the larger contribution (97.4 %) of the modelled electron density to the total atmospheric loss. The loss of SF6 by reaction with mesospheric metal atoms (Na and K) is far too slow to affect the lifetime. We investigate how this shorter atmospheric lifetime impacts the use of SF6 to derive stratospheric age of air. The age of air derived from this shorter lifetime SF6 tracer is longer by 9 % in polar latitudes at 20 km compared to a passive SF6 tracer. We also present laboratory measurements of the infrared spectrum of SF6 and find good agreement with previous studies. We calculate the resulting radiative forcings and efficiencies to be, on average, very similar to those reported previously. Our values for the 20-, 100- and 500-year global warming potentials are 18 000, 23 800 and 31 300, respectively.

Global simulations with the Chemical Lagrangian Model of the Stratosphere (CLaMS) using artificial tracers of air mass origin are used to analyze transport mechanisms from the Asian monsoon region into the lower stratosphere. In a case study, the transport of air masses from the Asian monsoon anticyclone originating in India/China by an eastward-migrating anticyclone which broke off from the main anticyclone on 20 September 2012 and filaments separated at the northeastern flank of the anticyclone are analyzed. Enhanced contributions of young air masses (younger than 5 months) are found within the separated anticyclone confined at the top by the thermal tropopause. Further, these air masses are confined by the anticyclonic circulation and, on the polar side, by the subtropical jet such that the vertical structure resembles a bubble within the upper troposphere. Subsequently, these air masses are transported eastwards along the subtropical jet and enter the lower stratosphere by quasi-horizontal transport in a region of double tropopauses most likely associated with Rossby wave breaking events. As a result, thin filaments with enhanced signatures of tropospheric trace gases were measured in the lower stratosphere over Europe during the TACTS/ESMVal campaign in September 2012 in very good agreement with CLaMS simulations. Our simulations demonstrate that source regions in Asia and in the Pacific Ocean have a significant impact on the chemical composition of the lower stratosphere of the Northern Hemisphere. Young, moist air masses, in particular at the end of the monsoon season in September/October 2012, flooded the extratropical lower stratosphere in the Northern Hemisphere with contributions of up to ≈ 30 % at 380 K (with the remaining fraction being aged air). In contrast, the contribution of young air masses to the Southern Hemisphere is much lower. At the end of October 2012, approximately 1.5 ppmv H2O is found in the lower Northern Hemisphere stratosphere (at 380 K) from source regions both in Asia and in the tropical Pacific compared to a mean water vapor content of ≈ 5 ppmv. In addition to this main transport pathway from the Asian monsoon anticyclone to the east along the subtropical jet and subsequent transport into the northern lower stratosphere, a second horizontal transport pathway out of the anticyclone to the west into the tropics (TTL) is found in agreement with MIPAS HCFC-22 measurements.

Global distributions of the CO2 vmr (volume mixing ratio) in the mesosphere and lower thermosphere (from 70 up to ∼ 140 km) have been derived from high-resolution limb emission daytime MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) spectra in the 4.3 µm region. This is the first time that the CO2 vmr has been retrieved in the 120–140 km range. The data set spans from January 2005 to March 2012. The retrieval of CO2 has been performed jointly with the elevation pointing of the line of sight (LOS) by using a non-local thermodynamic equilibrium (non-LTE) retrieval scheme. The non-LTE model incorporates the new vibrational–vibrational and vibrational–translational collisional rates recently derived from the MIPAS spectra by [Jurado-Navarro et al.(2015)]. It also takes advantage of simultaneous MIPAS measurements of other atmospheric parameters (retrieved in previous steps), such as the kinetic temperature (derived up to ∼ 100 km from the CO2 15 µm region of MIPAS spectra and from 100 up to 170 km from the NO 5.3 µm emission of the same MIPAS spectra) and the O3 measurements (up to ∼ 100 km). The latter is very important for calculations of the non-LTE populations because it strongly constrains the O(3P) and O(1D) concentrations below ∼ 100 km. The estimated precision of the retrieved CO2 vmr profiles varies with altitude ranging from ∼ 1 % below 90 km to 5 % around 120 km and larger than 10 % above 130 km. There are some latitudinal and seasonal variations of the precision, which are mainly driven by the solar illumination conditions. The retrieved CO2 profiles have a vertical resolution of about 5–7 km below 120 km and between 10 and 20 km at 120–140 km. We have shown that the inclusion of the LOS as joint fit parameter improves the retrieval of CO2, allowing for a clear discrimination between the information on CO2 concentration and the LOS and also leading to significantly smaller systematic errors. The retrieved CO2 has an improved accuracy because of the new rate coefficients recently derived from MIPAS and the simultaneous MIPAS measurements of other key atmospheric parameters (retrieved in previous steps) needed for non-LTE modelling like kinetic temperature and O3 concentration. The major systematic error source is the uncertainty of the pressure/temperature profiles, inducing errors at midlatitude conditions of up to 15 % above 100 km (20 % for polar summer) and of ∼ 5 % around 80 km. The errors due to uncertainties in the O(1D) and O(3P) profiles are within 3–4 % in the 100–120 km region, and those due to uncertainties in the gain calibration and in the near-infrared solar flux are within ∼ 2 % at all altitudes. The retrieved CO2 shows the major features expected and predicted by general circulation models. In particular, its abrupt decline above 80–90 km and the seasonal change of the latitudinal distribution, with higher CO2 abundances in polar summer from 70 up to ∼ 95 km and lower CO2 vmr in the polar winter. Above ∼ 95 km, CO2 is more abundant in the polar winter than at the midlatitudes and polar summer regions, caused by the reversal of the mean circulation in that altitude region. Also, the solstice seasonal distribution, with a significant pole-to-pole CO2 gradient, lasts about 2.5 months in each hemisphere, while the seasonal transition occurs quickly.

The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model–TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH4 fields in place of model simulations improves the model–TCCON XCH4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 to 4.3 ppb) and LMDz (Laboratoire de Météorologie Dynamique model with zooming capability; from 6.8 to 4.3 ppb). Replacing model simulations with MIPAS stratospheric CH4 fields adjusted to ACE-FTS reduces the average XCH4 bias for ACTM (3.3 ppb), but increases the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH4 to sufficient accuracy to eliminate these biases. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH4 and, hence, its contribution to XCH4. Therefore, it would be worthwhile to analyze how individual model components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) impact the simulation of stratospheric CH4 and XCH4.

The MIPAS Fourier transform spectrometer on board Envisat has measured global distributions of the six principal reactive nitrogen (NOy) compounds (HNO3, NO2, NO, N2O5, ClONO2, and HNO4) during 2002–2012. These observations were used previously to detect regular polar winter descent of reactive nitrogen produced by energetic particle precipitation (EPP) down to the lower stratosphere, often called the EPP indirect effect. It has further been shown that the observed fraction of NOy produced by EPP (EPP-NOy) has a nearly linear relationship with the geomagnetic Ap index when taking into account the time lag introduced by transport. Here we exploit these results in a semi-empirical model for computation of EPP-modulated NOy densities and wintertime downward fluxes through stratospheric and mesospheric pressure levels. Since the Ap dependence of EPP-NOy is distorted during episodes of strong descent in Arctic winters associated with elevated stratopause events, a specific parameterization has been developed for these episodes. This model accurately reproduces the observations from MIPAS and is also consistent with estimates from other satellite instruments. Since stratospheric EPP-NOy depositions lead to changes in stratospheric ozone with possible implications for climate, the model presented here can be utilized in climate simulations without the need to incorporate many thermospheric and upper mesospheric processes. By employing historical geomagnetic indices, the model also allows for reconstruction of the EPP indirect effect since 1850. We found secular variations of solar cycle-averaged stratospheric EPP-NOy depositions on the order of 1 GM. In particular, we model a reduction of the EPP-NOy deposition rate during the last 3 decades, related to the coincident decline of geomagnetic activity that corresponds to 1.8 % of the NOy production rate by N2O oxidation. As the decline of the geomagnetic activity level is expected to continue in the coming decades, this is likely to affect the long-term NOy trend by counteracting the expected increase caused by growing N2O emissions.

We have analysed MIPAS (Michelson Interferometer for Passive Atmopheric Sounding) infrared measurements of PMCs for the summer seasons in the Northern (NH) and Southern (SH) hemispheres from 2005 to 2012. Measurements of PMCs using this technique are very useful because they are sensitive to the total ice volume and independent of particle size. For the first time, MIPAS has provided coverage of the PMC total ice volume from midlatitudes to the poles. MIPAS measurements indicate the existence of a continuous layer of mesospheric ice, extending from about ∼ 81 km up to about 88–89 km on average and from the poles to about 50–60° in each hemisphere, increasing in concentration with proximity to the poles. We have found that the ice concentration is larger in the Northern Hemisphere than in the Southern Hemisphere. The ratio between the ice water content (IWC) in both hemispheres is also latitude-dependent, varying from a NH ∕ SH ratio of 1.4 close to the poles to a factor of 2.1 around 60°. This also implies that PMCs extend to lower latitudes in the NH. A very clear feature of the MIPAS observations is that PMCs tend to be at higher altitudes with increasing distance from the polar region (in both hemispheres), particularly equatorwards of 70°, and that they are about 1 km higher in the SH than in the NH. The difference between the mean altitude of the PMC layer and the mesopause altitude increases towards the poles and is larger in the NH than in the SH. The PMC layers are denser and wider when the frost-point temperature occurs at lower altitudes. The layered water vapour structure caused by sequestration and sublimation of PMCs is present at latitudes northwards of 70° N and more pronounced towards the pole. Finally, MIPAS observations have also shown a clear impact of the migrating diurnal tide on the diurnal variation of the PMC volume ice density.

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 SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) aboard the Envisat satellite provided measurements from August 2002 until April 2012. SCIAMACHY measured the scattered or direct sunlight using different observation geometries. The limb viewing geometry allows the retrieval of water vapour at about 10–25 km height from the near-infrared spectral range (1353–1410 nm). These data cover the upper troposphere and lower stratosphere (UTLS), a region in the atmosphere which is of special interest for a variety of dynamical and chemical processes as well as for the radiative forcing. Here, the latest data version of water vapour (V3.01) from SCIAMACHY limb measurements is presented and validated by comparisons with data sets from other satellite and in situ measurements. Considering retrieval tests and the results of these comparisons, the V3.01 data are reliable from about 11 to 23 km and the best results are found in the middle of the profiles between about 14 and 20 km. Above 20 km in the extra tropics V3.01 is drier than all other data sets. Additionally, for altitudes above about 19 km, the vertical resolution of the retrieved profile is not sufficient to resolve signals with a short vertical structure like the tape recorder. Below 14 km, SCIAMACHY water vapour V3.01 is wetter than most collocated data sets, but the high variability of water vapour in the troposphere complicates the comparison. For 14–20 km height, the expected errors from the retrieval and simulations and the mean differences to collocated data sets are usually smaller than 10 % when the resolution of the SCIAMACHY data is taken into account. In general, the temporal changes agree well with collocated data sets except for the Northern Hemisphere extratropical stratosphere, where larger differences are observed. This indicates a possible drift in V3.01 most probably caused by the incomplete treatment of volcanic aerosols in the retrieval. In all other regions a good temporal stability is shown. In the tropical stratosphere an increase in water vapour is found between 2002 and 2012, which is in agreement with other satellite data sets for overlapping time periods.

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 %.

A new and improved setup of the SF6 retrieval together with a newly calibrated version of MIPAS-ENVISAT level 1b spectra (version 5, ESA data version 5.02/5.06) was used to obtain a new global SF6 data set, covering the total observational period of MIPAS from July 2002 to April 2012 for the first time. Monthly and zonally averaged SF6 profiles were converted into mean age of air using a tropospheric SF6-reference curve. The obtained data set of age of air was compared to airborne age of air measurements. The temporal evolution of the mean age of air was then investigated in 10° latitude and 1–2 km altitude bins. A regression model consisting of a constant and a linear trend term, two proxies for the quasi-biennial oscillation variation, sinusoidal terms for the seasonal and semiannual variation and overtones was fitted to the age of air time series. The annual cycle for particular regions in the stratosphere was investigated and compared to other studies. The age of air trend over the total MIPAS period consisting of the linear term was assessed and compared to previous findings of Stiller et al. (2012). While the linear increase of mean age is confirmed to be positive for the northern midlatitudes and southern polar middle stratosphere, differences are found in the northern polar upper stratosphere, where the mean age is now found to increase as well. The magnitude of trends in the northern midlatitude middle stratosphere is slightly lower compared to the previous version and the trends fit remarkably well to the trend derived by Engel et al. (2009). Negative age of air trends found by Stiller et al. (2012) are confirmed for the lowermost tropical stratosphere and lowermost southern midlatitudinal stratosphere. Differences to the previous data versions occur in the middle tropical stratosphere around 25 km, where the trends are now negative. Overall, the new latitude–altitude distribution of trends appears to be less patchy and more coherent than the previous one. The new data provide evidence of an accelerating shallow branch of the Brewer–Dobson circulation, at least in the Southern Hemisphere. Finally the age of air decadal trends are compared to trends calculated with simulated SF6 values by the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA) and good agreement is found. The hemispheric asymmetry in the trends found in the MIPAS data is also indicated in the trends calculated with simulated SF6 values by the KASIMA model.

A merged time series of stratospheric water vapour built from the Halogen Occultation Instrument (HALOE) and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) data between 60° S and 60° N and 15 to 30 km and covering the years 1992 to 2012 was analysed by multivariate linear regression, including an 11-year solar cycle proxy. Lower stratospheric water vapour was found to reveal a phase-shifted anti-correlation with the solar cycle, with lowest water vapour after solar maximum. The phase shift is composed of an inherent constant time lag of about 2 years and a second component following the stratospheric age of air. The amplitudes of the water vapour response are largest close to the tropical tropopause (up to 0.35 ppmv) and decrease with altitude and latitude. Including the solar cycle proxy in the regression results in linear trends of water vapour being negative over the full altitude/latitude range, while without the solar proxy, positive water vapour trends in the lower stratosphere were found. We conclude from these results that a solar signal seems to be generated at the tropical tropopause which is most likely imprinted on the stratospheric water vapour abundances and transported to higher altitudes and latitudes via the Brewer–Dobson circulation. Hence it is concluded that the tropical tropopause temperature at the final dehydration point of air may also be governed to some degree by the solar cycle. The negative water vapour trends obtained when considering the solar cycle impact on water vapour abundances can possibly solve the "water vapour conundrum" of increasing stratospheric water vapour abundances despite constant or even decreasing tropopause temperatures.

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 a HCN climatology of the years 2002–2012, derived from FTIR limb emission spectra measured with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on the ENVISAT satellite, with the main focus on biomass burning signatures in the upper troposphere and lower stratosphere. HCN is an almost unambiguous tracer of biomass burning with a tropospheric lifetime of 5–6 months and a stratospheric lifetime of about 2 years. The MIPAS climatology is in good agreement with the HCN distribution obtained by the spaceborne ACE-FTS experiment and with airborne in situ measurements performed during the INTEX-B campaign. The HCN amounts observed by MIPAS in the southern tropical and subtropical upper troposphere have an annual cycle peaking in October–November, i.e. 1–2 months after the maximum of southern hemispheric fire emissions. The probable reason for the time shift is the delayed onset of deep convection towards austral summer. Because of overlap of varying biomass burning emissions from South America and southern Africa with sporadically strong contributions from Indonesia, the size and strength of the southern hemispheric plume have considerable interannual variations, with monthly mean maxima at, for example, 14 km between 400 and more than 700 pptv. Within 1–2 months after appearance of the plume, a considerable portion of the enhanced HCN is transported southward to as far as Antarctic latitudes. The fundamental period of HCN variability in the northern upper troposphere is also an annual cycle with varying amplitude, which in the tropics peaks in May after and during the biomass burning seasons in northern tropical Africa and southern Asia, and in the subtropics peaks in July due to trapping of pollutants in the Asian monsoon anticyclone (AMA). However, caused by extensive biomass burning in Indonesia and by northward transport of part of the southern hemispheric plume, northern HCN maxima also occur around October/November in several years, which leads to semi-annual cycles. There is also a temporal shift between enhanced HCN in northern low and mid- to high latitudes, indicating northward transport of pollutants. Due to additional biomass burning at mid- and high latitudes, this meridional transport pattern is not as clear as in the Southern Hemisphere. Upper tropospheric HCN volume mixing ratios (VMRs) above the tropical oceans decrease to below 200 pptv, presumably caused by ocean uptake, especially during boreal winter and spring. The tropical stratospheric tape recorder signal with an apparently biennial period, which was detected in MLS and ACE-FTS data from mid-2004 to mid-2007, is corroborated by MIPAS HCN data. The tape recorder signal in the whole MIPAS data set exhibits periodicities of 2 and 4 years, which are generated by interannual variations in biomass burning. The positive anomalies of the years 2003, 2007 and 2011 are caused by succession of strongly enhanced HCN from southern hemispheric and Indonesian biomass burning in boreal autumn and of elevated HCN from northern tropical Africa and the AMA in subsequent spring and summer. The anomaly of 2005 seems to be due to springtime emissions from tropical Africa followed by release from the summertime AMA. The vertical transport time of the anomalies is 1 month or less between 14 and 17 km in the upper troposphere and 8–11 months between 17 and 25 km in the lower stratosphere.

We use NO, NO2 and CO from MIPAS/ENVISAT to investigate the impact of energetic particle precipitation onto the NOx budget from the stratosphere to the lower mesosphere in the period from October 2003 to March 2004, a time of high solar and geomagnetic activity. We find that in the winter hemisphere the indirect effect of auroral electron precipitation due to downwelling of upper mesospheric/lower thermospheric air into the stratosphere prevails. Its effect exceeds even the direct impact of the very large solar proton event in October/November 2003 by nearly 1 order of magnitude. Correlations of NOx and CO show that the unprecedented high NOx values observed in the Northern Hemisphere lower mesosphere and upper stratosphere in late January and early February are fully consistent with transport from the upper mesosphere/lower thermosphere and subsequent mixing at lower altitudes. In the polar summer Southern Hemisphere, we observed an enhanced variability of NO and NO2 on days with enhanced geomagnetic activity, but this seems to indicate enhanced instrument noise rather than a direct increase due to electron precipitation. A direct effect of electron precipitation onto NOx can not be ruled out, but, if any, it is lower than 3 ppbv in the altitude range 40–56 km and lower than 6 ppbv in the altitude range 56–64 km. An additional significant source of NOx due to local production by precipitating electrons below 70 km exceeding several parts per billion as discussed in previous publications appears unlikely.

Drifts, trends and periodic variations were calculated from monthly zonally averaged ozone profiles. The ozone profiles were derived from level-1b data of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) by means of the scientific level-2 processor run by the Karlsruhe Institute of Technology (KIT), Institute for Meteorology and Climate Research (IMK). All trend and drift analyses were performed using a multilinear parametric trend model which includes a linear term, several harmonics with period lengths from 3 to 24 months and the quasi-biennial oscillation (QBO). Drifts at 2-sigma significance level were mainly negative for ozone relative to Aura MLS and Odin OSIRIS and negative or near zero for most of the comparisons to lidar measurements. Lidar stations used here include those at Hohenpeissenberg (47.8° N, 11.0° E), Lauder (45.0° S, 169.7° E), Mauna Loa (19.5° N, 155.6° W), Observatoire Haute Provence (43.9° N, 5.7° E) and Table Mountain (34.4° N, 117.7° W). Drifts against the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) were found to be mostly insignificant. The assessed MIPAS ozone trends cover the time period of July 2002 to April 2012 and range from −0.56 ppmv decade−1 to +0.48 ppmv decade−1 (−0.52 ppmv decade−1 to +0.47 ppmv decade−1 when displayed on pressure coordinates) depending on altitude/pressure and latitude. From the empirical drift analyses we conclude that the real ozone trends might be slightly more positive/less negative than those calculated from the MIPAS data, by conceding the possibility of MIPAS having a very small (approximately within −0.3 ppmv decade−1) negative drift for ozone. This leads to drift-corrected trends of −0.41 ppmv decade−1 to +0.55 ppmv decade−1 (−0.38 ppmv decade−1 to +0.53 ppmv decade−1 when displayed on pressure coordinates) for the time period covered by MIPAS Envisat measurements, with very few negative and large areas of positive trends at mid-latitudes for both hemispheres around and above 30 km (~10 hPa). Negative trends are found in the tropics around 25 and 35 km (~25 and 5 hPa), while an area of positive trends is located right above the tropical tropopause. These findings are in good agreement with the recent literature. Differences of the trends compared with the recent literature could be explained by a possible shift of the subtropical mixing barriers. Results for the altitude–latitude distribution of amplitudes of the quasi-biennial, annual and the semi-annual oscillation are overall in very good agreement with recent findings.

Middle atmospheric water vapour can be used as a tracer for dynamical processes. It is mainly measured by satellite instruments and ground-based microwave radiometers. Ground-based instruments capable of measuring middle-atmospheric water vapour are sparse but valuable as they complement satellite measurements, are relatively easy to maintain and have a long lifetime. MIAWARA-C is a ground-based microwave radiometer for middle-atmospheric water vapour designed for use on measurement campaigns for both atmospheric case studies and instrument intercomparisons. MIAWARA-C's retrieval version 1.1 (v1.1) is set up in a such way as to provide a consistent data set even if the instrument is operated from different locations on a campaign basis. The sensitive altitude range for v1.1 extends from 4 hPa (37 km) to 0.017 hPa (75 km). For v1.1 the estimated systematic error is approximately 10% for all altitudes. At lower altitudes it is dominated by uncertainties in the calibration, with altitude the influence of spectroscopic and temperature uncertainties increases. The estimated random error increases with altitude from 5 to 25%. MIAWARA-C measures two polarisations of the incident radiation in separate receiver channels, and can therefore provide two measurements of the same air mass with independent instrumental noise. The standard deviation of the difference between the profiles obtained from the two polarisations is in excellent agreement with the estimated random measurement error of v1.1. In this paper, the quality of v1.1 data is assessed for measurements obtained at two different locations: (1) a total of 25 months of measurements in the Arctic (Sodankylä, 67.37° N, 26.63° E) and (2) nine months of measurements at mid-latitudes (Zimmerwald, 46.88° N, 7.46° E). For both locations MIAWARA-C's profiles are compared to measurements from the satellite experiments Aura MLS and MIPAS. In addition, comparisons to ACE-FTS and SOFIE are presented for the Arctic and to the ground-based radiometer MIAWARA for the mid-latitude campaigns. In general, all intercomparisons show high correlation coefficients, confirming the ability of MIAWARA-C to monitor temporal variations of the order of days. The biases are generally below 13% and within the estimated systematic uncertainty of MIAWARA-C. No consistent wet or dry bias is identified for MIAWARA-C. In addition, comparisons to the reference instruments indicate the estimated random error of v1.1 to be a realistic measure of the random variation on the retrieved profile between 45 and 70 km.

We present altitude-dependent lifetimes of NOx, determined with MIPAS/ENVISAT (the Michelson Interferometer for Passive Atmospheric Sounding/the European Environment Satellite), for the Southern polar region after the solar proton event in October–November 2003. Between 50° S and 90° S and decreasing in altitude they range from about two days at 64 km to about 20 days at 44 km. The lifetimes are controlled by transport, mixing and photochemistry. We infer estimates of dynamical lifetimes by comparison of the observed decay to photochemical lifetimes calculated with the SLIMCAT 3-D Model. Photochemical loss contributes to the observed NOx depletion by 0.1% at 44 km, increasing with altitude to 45% at 64 km. In addition, we show the correlation of modelled ionization rates and observed NOx densities under consideration of the determined lifetimes of NOx, and calculate altitude-dependent effective production rates of NOx due to ionization. For that we compare ionization rates of the AIMOS data base with the MIPAS measurements from 15 October–31 December 2003. We derive effective NOx-production rates to be applied to the AIMOS ionization rates which range from about 0.2 NOx-molecules per ion pair at 44 km to 0.7 NOx-molecules per ion pair at 62 km. These effective production rates are considerably lower than predicted by box model simulations which could hint at an overestimation of the modelled ionization rates.

Since May 2009, high-resolution Fourier Transform Infrared (FTIR) solar absorption spectra have been recorded at Addis Ababa (9.01° N latitude, 38.76° E longitude, 2443 m altitude above sea level), Ethiopia. The vertical profiles and total column amounts of ozone (O3) are deduced from the spectra by using the retrieval code PROFFIT (V9.5) and regularly determined instrumental line shape (ILS). A detailed error analysis of the O3 retrieval is performed. Averaging kernels of the target gas shows that the major contribution to the retrieved information comes from the measurement. The degrees of freedom for signals is found to be 2.1 on average for the retrieval of O3 from the observed FTIR spectra. The ozone Volume Mixing Ratio (VMR) profiles and column amounts retrieved from FTIR spectra are compared with the coincident satellite observations of Microwave Limb Sounding (MLS), Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), Tropospheric Emission Spectrometer (TES), Ozone Monitoring Instrument (OMI), Atmospheric Infrared Sounding (AIRS) and Global Ozone Monitoring Experiment (GOME-2) instruments. The mean relative differences in ozone profiles of FTIR from MLS and MIPAS are generally lower than 15% within the altitude range of 27 to 36 km, whereas difference from TES is lower than 1%. Comparisons of measurements of column amounts from the satellite and the ground-based FTIR show very good agreement as exhibited by relative differences within +0.2% to +2.8% for FTIR versus MLS and GOME-2; and −0.9 to −9.0% for FTIR versus OMI, TES and AIRS. The corresponding standard deviations are within 2.0 to 2.8% for FTIR versus MLS and GOME-2 comparisons whereas that of FTIR versus OMI, TES and AIRS are within 3.5 to 7.3%. Thus, the retrieved O3 VMR and column amounts from a tropical site, Addis Ababa, is found to exhibit very good agreement with all coincident satellite observations over an approximate 3-yr period.