Abstract. Reliable reference profiles and estimates of variability are a necessity for a variety of processes relating to ENVISAT including the development of key aspects and inputs for the operational processor for the Michelson Interferometer for Passive Atmospheric Sounding. MIPAS reference atmospheres have therefore been produced in two forms, namely standard atmospheres for modelling and error analysis for typical atmospheric situations and the IG2 seasonal climatologies for initial guess profiles used as part of the operational processing. The reference states cover 36 species on a common altitude, pressure, and temperature grid from 0 to 120 km, and include both means and estimates of variability (maximum, minimum and one sigma values). This paper describes V3.1 of the standard atmospheres and V4.0 of the IG2 atmospheres which are the current versions of the reference atmospheres. Particular attention is paid to the MIPAS operational geophysical products (pressure/temperature, H2O, O3, CH4, N2O, HNO3 and NO2) and to CO2 whose mixing ratio is required for the retrieval of pressure and temperature. A dynamic representation of CO2 is presented which shows the presence of CO2 gradients in the troposphere and the lower stratosphere. Since these atmospheres have been produced independently of MIPAS data, it is also possible to compare the data to the MIPAS operational products and derive valuable information on both the reference atmospheres and on MIPAS data products themselves. This process has been performed for V4.61/V4.62 data from the year 2003 as part of the MIPAS validation activity. It is demonstrated that the agreement between the MIPAS mean data and the reference atmospheres is very good in mid-latitudes and the tropics, verifying these data to first order. There is also reasonable agreement in standard deviations between the IG2 atmospheres and the corresponding sigmas calculated from the MIPAS data. Knowledge of tropospheric concentrations of CH4 and N2O is used to examine the accuracy of the MIPAS data and their susceptibility to cloud effects. It is shown that for the highest accuracy, MIPAS data should be filtered with cloud index values of 2.5 for N2O and 3.5 for CH4. Once such filtering has been performed, the MIPAS data for these species appear to be accurate to within 10% in the upper troposphere. The use of cloud index data in combination with MIPAS data is recommended for studies of the polar winter stratosphere and the upper troposphere/lower stratosphere.

The infrared limb spectra of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Envisat satellite include detailed information on tropospheric clouds and polar stratospheric clouds (PSC). However, no consolidated cloud product is available for the scientific community. Here we describe a fast prototype processor for cloud parameter retrieval from MIPAS (MIPclouds). Retrieval of parameters such as cloud top height, temperature, and extinction are implemented, as well as retrieval of microphysical parameters, e.g. effective radius and the integrated quantities over the limb path (surface area density and volume density). MIPclouds classifies clouds as either liquid or ice cloud in the upper troposphere and polar stratospheric clouds types in the stratosphere based on statistical combinations of colour ratios and brightness temperature differences. <br><br> Comparison of limb measurements of clouds with model results or cloud parameters from nadir looking instruments is often difficult due to different observation geometries. We therefore introduce a new concept, the limb-integrated surface area density path (ADP). By means of validation and radiative transfer calculations of realistic 2-D cloud fields as input for a blind test retrieval (BTR), we demonstrate that ADP is an extremely valuable parameter for future comparison with model data of ice water content, when applying limb integration (ray tracing) through the model fields. In addition, ADP is used for a more objective definition of detection thresholds of the applied detection methods. Based on BTR, a detection threshold of ADP = 10⁷ μm² cm⁻² and an ice water content of 10^&minus;5 g m⁻³ is estimated, depending on the horizontal and vertical extent of the cloud. <br><br> Intensive validation of the cloud detection methods shows that the limb-sounding MIPAS instrument has a sensitivity in detecting stratospheric and tropospheric clouds similar to that of space- and ground-based lidars, with a tendency for higher cloud top heights and consequently higher sensitivity for some of the MIPAS detection methods. For the high cloud amount (HCA, pressure levels below 440 hPa) on global scales the sensitivity of MIPAS is significantly greater than that of passive nadir viewers. This means that the high cloud fraction will be underestimated in the ISCCP dataset compared to the amount of high clouds deduced by MIPAS. Good correspondence in seasonal variability and geographical distribution of cloud occurrence and zonal means of cloud top height is found in a detailed comparison with a climatology for subvisible cirrus clouds from the Stratospheric Aerosol and Gas Experiment II (SAGE II) limb sounder. Overall, validation with various sensors shows the need to consider differences in sensitivity, and especially the viewing geometries and field-of-view size, to make the datasets comparable (e.g. applyin...

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.

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), on-board the European ENVIronmental SATellite (ENVISAT) launched on 1 March 2002, is a middle infrared Fourier Transform spectrometer measuring the atmospheric emission spectrum in limb sounding geometry. The instrument is capable to retrieve the vertical distribution of temperature and trace gases, aiming at the study of climate and atmospheric chemistry and dynamics, and at applications to data assimilation and weather forecasting.Correspondence to: U. Cortesi (u.cortesi@ifac.cnr.it) MIPAS operated in its standard observation mode for approximately two years, from July 2002 to March 2004, with scans performed at nominal spectral resolution of 0.025 cm −1 and covering the altitude range from the mesosphere to the upper troposphere with relatively high vertical resolution (about 3 km in the stratosphere). Only reduced spectral resolution measurements have been performed subsequently. MIPAS data were re-processed by ESA using updated versions of the Instrument Processing Facility (IPF v4.61 and v4.62) (and, to a lesser extent, v4.62) O 3 VMR profiles and a comprehensive set of correlative data, including observations from ozone sondes, ground-based lidar, FTIR and microwave radiometers, remote-sensing and in situ instruments on-board stratospheric aircraft and balloons, concurrent satellite sensors and ozone fields assimilated by the European Center for Medium-range Weather Forecasting.A coordinated effort was carried out, using common criteria for the selection of individual validation data sets, and similar methods for the comparisons. This enabled merging the individual results from a variety of independent reference measurements of proven quality (i.e. well characterized error budget) into an overall evaluation of MIPAS O 3 data quality, having both statistical strength and the widest spatial and temporal coverage. Collocated measurements from ozone sondes and ground-based lidar and microwave radiometers of the Network for the Detection Atmospheric Composition Change (NDACC) were selected to carry out comparisons with time series of MIPAS O 3 partial columns and to identify groups of stations and time periods with a uniform pattern of ozone differences, that were subsequently used for a vertically resolved statistical analysis. The results of the comparison are classified according to synoptic and regional systems and to altitude intervals, showing a generally good agreement within the comparison error bars in the upper and middle stratosphere. Significant differences emerge in the lower stratosphere and are only partly explained by the larger contributions of horizontal and vertical smoothing differences and of collocation errors to the total uncertainty. Further results obtained from a purely statistical analysis of the same data set from NDACC ground-based lidar stations, as well as from additional ozone soundings at middle latitudes and from NDACC ground-based FTIR measurements, confirm the validity of MIPAS O 3 profil...

Abstract. Satellite infrared emission instruments require efficient systems that can separate and flag observations which are affected by clouds and aerosols. This paper investigates the identification of cloud and aerosols from infrared, limb sounding spectra that were recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), a high spectral resolution Fourier transform spectrometer on the European Space Agency's (ESA) ENVISAT (Now inoperative since April 2012 due to loss of contact). Specifically, the performance of an existing cloud and aerosol particle detection method is simulated with a radiative transfer model in order to establish, for the first time, confident detection limits for particle presence in the atmosphere from MIPAS data. The newly established thresholds improve confidence in the ability to detect particle injection events, plume transport in the upper troposphere and lower stratosphere (UTLS) and better characterise cloud distributions utilising MIPAS spectra. The method also provides a fast front-end detection system for the MIPClouds processor; a processor designed for the retrieval of macro-and microphysical cloud properties from the MIPAS data.It is shown that across much of the stratosphere, the threshold for the standard cloud index in band A is 5.0 although threshold values of over 6.0 occur in restricted regimes. Polar regions show a surprising degree of uncertainty at altitudes above 20 km, potentially due to changing stratospheric trace gas concentrations in polar vortex conditions and poor signal-to-noise due to cold atmospheric temperatures. The optimised thresholds of this study can be used for much of the time, but time/composition-dependent thresholds are recommended for MIPAS data for the strongly perturbed polar stratosphere. In the UT, a threshold of 5.0 applies at 12 km and above but decreases rapidly at lower altitudes. The new thresholds are shown to allow much more sensitive detection of particle distributions in the UTLS, with extinction detection limits above 13 km often better than 10 −4 km −1 , with values approaching 10 −5 km −1 in some cases.Comparisons of the new MIPAS results with cloud data from HIRDLS and CALIOP, outside of the poles, establish a good agreement in distributions (cloud and aerosol top heights and occurrence frequencies) with an offset between MIPAS and the other instruments of 0.5 km to 1 km between 12 km and 20 km, consistent with vertical oversampling of extended cloud layers within the MIPAS field of view. We conclude that infrared limb sounders provide a very consistent picture of particles in the UTLS, allowing detection limits which are consistent with the lidar observations. Investigations of MIPAS data for the Mount Kasatochi volcanic eruption on the Aleutian Islands and the Black Saturday fires in Australia are used to exemplify how useful MIPAS limb sounding data were for monitoring aerosol injections into the UTLS. It is shown that the new thresholds allowed such events to be much more effectively derived fro...