The infrared emission limb sounder MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) will be operated as an ESA core instrument on the ENVISAT-1 satellite. Near real time retrieval of pressure, temperature (p,T) and volume mixing ratio (VMR) of six key species (O 3 , H 2 O, HNO 3 , CH 4 , N 2 O and NO 2 ) from calibrated spectra will be performed in the Level 2 processor of the ENVISAT Payload Data Segment. An ESA supported study was carried out for the development of an optimized (with respect to speed and accuracy) retrieval algorithm suitable for the implementation in MIPAS Level 2 processor. In the framework of this study, an optimized forward / retrieval code was implemented based on the global fit approach. In this approach all the spectra of a limb-scanning sequence are simultaneously fitted in order to correctly account for error correlations in the altitude domain. Besides, only spectral intervals which are sensitive to the retrieved parameters are analyzed by using a microwindow approach. This also minimizes interferences of spectral signatures from atmospheric species with unknown concentration. Finally, a sequential retrieval of the target species VMR profiles is performed. The trade-off between run time and accuracy of the retrieval was optimized from both the physical and mathematical point of view, with optimizations in the program structure, in the radiative transfer model and in the computation of the retrieval Jacobian. The attained performances of the retrieval code are: noise error on temperature < 2 K at all the altitudes covered by the typical MIPAS scan (8-53 km with 3 km resolution), noise error on tangent pressure < 3 % , noise error on VMR of the target species < 5 % at most of the altitudes covered by the standard MIPAS scan. The run-time required to perform p,T and VMR retrieval of the five MIPAS target species from a limb-scanning sequence of 16 limb-views is less than 1 minute on a modern work-station.

Abstract. The MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument has been operating on-board the ENVISAT satellite since March 2002. In the first two years, it acquired in a nearly continuous manner high resolution (0.025 cm−1 unapodised) emission spectra of the Earth's atmosphere at limb in the middle infrared region. This paper describes the level 2 near real-time (NRT) and off-line (OL) ESA processors that have been used to derive level 2 geophysical products from the calibrated and geolocated level 1b spectra. The design of the code and the analysis methodology have been driven by the requirements for NRT processing. This paper reviews the performance of the optimised retrieval strategy that has been implemented to achieve these requirements and provides estimated error budgets for the target products: pressure/temperature, O3, H2O, CH4, HNO3, N2O and NO2, in the altitude measurement range from 6 to 68 km. From application to real MIPAS data, it was found that no change was needed in the developed code although an external algorithm was introduced to identify clouds with high opacity and to exclude affected spectra from the analysis. In addition, a number of updates were made to the set-up parameters and to auxiliary data. In particular, a new version of the MIPAS dedicated spectroscopic database was used and, in the OL analysis, the retrieval range was extended to reduce errors due to uncertainties in extrapolation of the profile outside the retrieval range and more stringent convergence criteria were implemented. A statistical analysis on the χ2 values obtained in one year of measurements shows good agreement with the a priori estimate of the forward model errors. On the basis of the first two years of MIPAS measurements the estimates of the forward model and instrument errors are in general found to be conservative with excellent performance demonstrated for frequency calibration. It is noted that the total retrieval error is limited by forward model errors which make useless a further reduction of random errors. However, such a reduction is within the capabilities of MIPAS measurements, which contain many more spectral signatures of the target species than what currently used. Further work is needed to reduce the amplitude of the forward model errors, so that the random error and the total error budget can be reduced accordingly. The importance of the Averaging kernels for a full characterisation of the target products is underlined and the equations are provided for their practical applications.

Abstract. The MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument has been operating on-board the ENVISAT satellite since March 2002. In the first two years, it acquired in a nearly continuous manner high resolution (0.025 cm −1 unapodized) emission spectra of the Earth's atmosphere at limb in the middle infrared region. This paper describes the level 2 near real-time (NRT) and offline (OL) ESA processors that have been used to derive level 2 geophysical products from the calibrated and geolocated level 1b spectra. The design of the code and the analysis methodology have been driven by the requirements for NRT processing. This paper reviews the performance of the optimized retrieval strategy that has been implemented to achieve these requirements and provides estimated error budgets for the target products: pressure, temperature, O 3 , H 2 O, CH 4 , HNO 3 , N 2 O and NO 2 , in the altitude measurement range from 6 to 68 km.From application to real MIPAS data, it was found that no change was needed in the developed code although an external algorithm was introduced to identify clouds with high opacity and to exclude affected spectra from the analysis. In addition, a number of updates were made to the set-up parameters and to auxiliary data. In particular, a new version of the MIPAS dedicated spectroscopic database was used and, in the OL analysis, the retrieval range was extended to reduce errors due to uncertainties in extrapolation of the profile outside the retrieval range and more stringent convergence criteria were implemented.Correspondence to: P. Raspollini (p.raspollini@ifac.cnr.it) A statistical analysis on the χ 2 values obtained in one year of measurements shows good agreement with the a priori estimate of the forward model errors. On the basis of the first two years of MIPAS measurements the estimates of the forward model and instrument errors are in general found to be conservative with excellent performance demonstrated for frequency calibration. It is noted that the total retrieval error is limited by forward model errors which make effectless a further reduction of random errors. However, such a reduction is within the capabilities of MIPAS measurements, which contain many more spectral signatures of the target species than what has currently been used. Further work is needed to reduce the amplitude of the forward model errors, so that the random error and the total error budget can be reduced accordingly.The importance of the Averaging kernels for a full characterization of the target products is underlined and the equations are provided for their practical applications.

Abstract. The MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument on the Envisat (Environmental satellite) satellite has provided vertical profiles of the atmospheric composition on a global scale for almost ten years. The MIPAS mission is divided in two phases: the full resolution phase, from 2002 to 2004, and the optimized resolution phase, from 2005 to 2012, which is characterized by a finer vertical and horizontal sampling attained through a reduction of the spectral resolution. While the description and characterization of the products of the ESA processor for the full resolution phase has been already described in previous papers, in this paper we focus on the performances of the latest version of the ESA (European Space Agency) processor, named ML2PP V6 (MIPAS Level 2 Prototype Processor), which has been used for reprocessing the entire mission. The ESA processor had to perform the operational near real time analysis of the observations and its products needed to be available for data assimilation. Therefore, it has been designed for fast, continuous and automated analysis of observations made in quite different atmospheric conditions and for a minimum use of external constraints in order to avoid biases in the products. The dense vertical sampling of the measurements adopted in the second phase of the MIPAS mission resulted in sampling intervals finer than the instantaneous field of view of the instrument. Together with the choice of a retrieval grid aligned with the vertical sampling of the measurements, this made ill-conditioned the retrieval problem of the MIPAS operational processor. This problem has been handled with minimal changes to the original retrieval approach but with significant improvements nonetheless. The Levenberg–Marquardt method, already present in the retrieval scheme for its capability to provide fast convergence for nonlinear problems, is now also exploited for the reduction of the ill-conditioning of the inversion. An expression specifically designed for the regularizing Levenberg–Marquardt method has been implemented for the computation of the covariance matrices and averaging kernels of the retrieved products. The regularization of the Levenberg–Marquardt method is controlled by the convergence criteria and is deliberately kept weak. The resulting oscillations of the retrieved profile are a posteriori damped by an innovative self-adapting Tikhonov regularization. The convergence criteria and the weakness of the self-adapting regularization ensure that minimum constraints are used and the best vertical resolution obtainable from the measurements is achieved in all atmospheric conditions. Random and systematic errors, as well as vertical and horizontal resolution are compared in the two phases of the mission for all products, namely: temperature, H2O, O3, HNO3, CH4, N2O, NO2, CFC-11, CFC-12, N2O5 and ClONO2. The use in the two phases of the mission of different optimized sets of spectral intervals ensures that, despite the different spectral resolutions, comparable performances are obtained in the whole MIPAS mission in terms of random and systematic errors, while the vertical resolution and the horizontal resolution are significantly better in the case of the optimized resolution measurements.

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