[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.

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.

Abstract. The climate models used in the IPCC AR4 show large differences in monthly mean ice water path (IWP). The most valuable source of information that can be used to potentially constrain the models is global satellite data. The satellite datasets also have large differences. The retrieved IWP depends on the technique used, as retrievals based on different techniques are sensitive to different parts of the cloud column. Building on the foundation of Waliser et al. (2009), this article provides a more comprehensive comparison between satellite datasets. IWP data from the CloudSat cloud profiling radar provide the most advanced dataset on clouds. For all its unmistakable value, CloudSat data are too short and too sparse to assess climatic distributions of IWP, hence the need to also use longer datasets. We evaluate satellite datasets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, in order to determine the differences and relate them to the sensitivity of the instrument used in the retrievals. This information is also used to evaluate the climate models, to the extent that is possible.ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the better of the two. Additionally PATMOS-x and ISCCP, which have a temporal range long enough to capture the inter-annual variability of IWP, are used in conjunction with CloudSat IWP (after removing profiles that contain precipitation) to assess the IWP Correspondence to: S. Eliasson (s.eliasson@ltu.se) variability and mean of the climate models. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is probably the GCM from IPCC AR4 closest to satellite observations.

Abstract.We have used high spectral resolution spectroscopic measurements from the MIPAS instrument on the Envisat satellite to simultaneously retrieve vertical profiles of H 2 O and HDO in the stratosphere and uppermost troposphere. Variations in the deuterium content of water are expressed in the common δ notation, where δD is the deviation of the Deuterium/Hydrogen ratio in a sample from a standard isotope ratio. A thorough error analysis of the retrievals confirms that reliable δD data can be obtained up to an altitude of ∼45 km. Averaging over multiple orbits and thus over longitudes further reduces the random part of the error. The absolute total error of averaged δD is between 36‰ and 111‰. With values lower than 42‰ the total random error is significantly smaller than the natural variability of δD. The data compare well with previous investigations. The MIPAS measurements now provide a unique global data set of highquality δD data that will provide novel insight into the stratospheric water cycle.