[1] Retrieval of abundances of atmospheric species from limb infrared emission spectra requires accurate knowledge of the pointing of the instrument in terms of elevation, as well as temperature and pressure profiles. An optimal estimation-based method is presented to infer these quantities from measured spectra. The successful and efficient joint retrieval of these largely correlated quantities depends strongly on the proper selection of the retrieval space, the selection of spectral microwindows, and the choice of reasonable constraints which force the solution to be stable. The proposed strategy was applied to limb emission spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Envisat research satellite in order to validate the instrument pointing information based on the satellite's orbit and attitude control system which uses star tracker information as a reference. Both systematic and periodic pointing calibration errors were detected, which meanwhile have been corrected to a major part. Furthermore, occasional pitch jumps were detected, which could be assigned to parameter uploads to the satellite's orbit and attitude control system. It has been shown that in general, it is justified to assume local thermodynamic equilibrium below 60 km for these purposes. The retrieval method presented has been proven to be suitable for independent monitoring of MIPAS line-of-sight pointing.

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Abstract. Global distributions of profiles of sulphur hexafluoride (SF6) have been retrieved from limb emission spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat covering the period September 2002 to March 2004. Individual SF6 profiles have a precision of 0.5 pptv below 25 km altitude and a vertical resolution of 4–6 km up to 35 km altitude. These data have been validated versus in situ observations obtained during balloon flights of a cryogenic whole-air sampler. For the tropical troposphere a trend of 0.230±0.008 pptv/yr has been derived from the MIPAS data, which is in excellent agreement with the trend from ground-based flask and in situ measurements from the National Oceanic and Atmospheric Administration Earth System Research Laboratory, Global Monitoring Division. For the data set currently available, based on at least three days of data per month, monthly 5° latitude mean values have a 1σ standard error of 1%. From the global SF6 distributions, global daily and monthly distributions of the apparent mean age of air are inferred by application of the tropical tropospheric trend derived from MIPAS data. The inferred mean ages are provided for the full globe up to 90° N/S, and have a 1σ standard error of 0.25 yr. They range between 0 (near the tropical tropopause) and 7 years (except for situations of mesospheric intrusions) and agree well with earlier observations. The seasonal variation of the mean age of stratospheric air indicates episodes of severe intrusion of mesospheric air during each Northern and Southern polar winter observed, long-lasting remnants of old, subsided polar winter air over the spring and summer poles, and a rather short period of mixing with midlatitude air and/or upward transport during fall in October/November (NH) and April/May (SH), respectively, with small latitudinal gradients, immediately before the new polar vortex starts to form. The mean age distributions further confirm that SF6 is destroyed in the mesosphere to a considerable degree. Model calculations with the Karlsruhe simulation model of the middle atmosphere (KASIMA) chemical transport model agree well with observed global distributions of the mean age only if the SF6 sink reactions in the mesosphere are included in the model.

The atmosphere of Earth has already been investigated by several spaceborne instruments, and several further instruments will be launched, e.g., NASA's Earth Observing System Aura platform and the European Space Agency's Environmental Satellite. To stabilize the results in atmospheric retrievals, constraints are used in the iteration process. Therefore hard constraints (discretization of the retrieval grid) and soft constraints (regularization operators) are included in the retrieval. Tikhonov regularization is often used as a soft constraint. In this study, different types of Tikhonov operator were compared, and several new methods were developed to determine the optimal strength of the constraint operationally. The resulting regularization parameters were applied successfully to an ozone retrieval from simulated nadir sounding spectra like those expected to be measured by the Tropospheric Emission Spectrometer, which is part of the Aura platform. Retrievals were characterized by means of estimated error, averaging kernel, vertical resolution, and degrees of freedom.

[1] In this paper, the vertical resolution for Tropospheric Emission Spectrometer (TES) nadir ozone retrievals is established and is used to assess the ability of TES to capture time variations of ozone in the troposphere. This characterization is based on retrievals of ozone using simulated radiances generated from ozonesonde profiles taken over Bermuda from 14 April to 25 May 1993. To that end, a two-step retrieval strategy that includes an initial estimate of the ''shape'' of the ozone followed by a finer-resolution estimate was developed to provide rapid and robust convergence against large deviations of ozone profiles in the troposphere and lower stratosphere relative to a climatology. An error analysis is derived that accurately accounts for representation errors of the profile, choices of regularization, and the dependence of the retrieval error on both the statistics of the profile and spectral measurement noise, as well as the sensitivity of these retrievals to errors in temperature. This analysis shows that TES should be able to retrieve ozone in the nadir with an approximately 6 km resolution in the troposphere. The root-mean square errors in estimates of the upper and lower tropospheric columns are about 1.35 Dobson units (DU) each. With this vertical resolution, TES would have the sensitivity to detect both the enhanced and reduced tropospheric ozone present in the Bermuda data set. Coupled with a 2-day near-repeat orbit and global coverage, TES retrievals of ozone could provide invaluable information to distinguish between anthropogenic and meteorological sources for the time variability of ozone in the troposphere.