Michael Hoepfner

Remote sensing of the middle atmosphere with MIPAS

On 1 March 2002 the Envisat research satellite has been launched successfully into its sun-synchronous orbit. One of its instruments for atmospheric composition sounding is the Michelson Interferometer for Passive Atmospheric Sounding, a limb-scanning mid-infrared Fourier transform spectrometer. Different scientific objectives of data users require different approaches to data analysis, which are discussed. A strategy on how to validate the involved algorithms and relevant strategies is presented.

Karlsruhe optimized and precise radiative transfer algorithm. Part I: requirements, justification, and model error estimation

We present the Karlsruhe Optimized and Precise Radiative transfer Algorithm (KOPRA) which has been specifically developed for data analysis of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) going to be launched on ESAs polar-orbiting Environmental Satellite 1 (ENVISAT-1) in 1999. KOPRA has been designed to account for the particular instrument requirements of MIPAS and the observation scenarii during the ENVISAT mission, in particular with respect to the viewing direction and the altitude coverage of the atmosphere. The conceptual details of KOPRA, which reflect the requirements set up by the instrument design details, the observation scenarii, and the link to a retrieval concept with high flexibility, are presented. The forward model error due to discarding individual physical processes and properties of the atmosphere as well as an over-all error budget with respect to these parameters is assessed in order to demonstrate the improvements of retrieval accuracy expected by usage of KOPRA.

Karlsruhe optimized and precise radiative transfer algorithm: II. Interface to retrieval applications

The new Karlsruhe Optimized and Precise Radiative transfer algorithm (KOPRA) is a line-by-line model for use in retrieval processors for atmospheric observations. It simulates IR spectra by taking into account physical properties of the atmospheric observations. It simulates IR spectra by taking into account physical properties of the atmosphere and of the instrument. Besides spectrum calculation, KOPRA has the capability to determine the derivatives of the spectrum with respect to many retrieval parameters. Comparisons between analytical and numerical derivatives, which are generally within a few percent, demonstrate that approximates due to run time optimized implementations are small. Furthermore, a flexible scheme is presented for handling various parameterizations of atmospheric profiles as implemented in the code in order to support different retrieval approaches.

Karlsruhe optimized and precise radiative transfer algorithm: Part III: ADDLIN and TRANSF algorithms for modeling spectral transmittance and radiance

Two sets of subroutines for calculating absorption cross section spectra and transmission or radiance fields are presented. These libraries will be used in the operational data processing of the MIPAS/ENVISAT level-2 off-line processor and are part of the Karlruhe Optimized and Precise Radiative transfer Algorithm (KOPRA). The objective in developing these libraries was to accommodate flexibility and simplicity in use without substantial loss of accuracy and efficiency. The ADDLIN library uses an efficient method for calculating absorption cross section spectra line-by-line to arbitrary high numerical accuracy. Computational efficiency is achieved by calculating each spectral line on its own optimum set of sampling points. Absorption cross section spectra are stored on flexible, non-equidistant frequency grids. The TRANSF package provides integration routines that can be quickly configured for a variety of specific applications and measurement scenarios. The routines operate on the non-equidistant frequency grids produced by ADDIN and allow the researcher to implement the radiative transfer in a simple and almost natural way. Computational efficiency results from the reduced number of sampling points on the non-equidistant frequency grids produced by ADDIN and allow the researcher to implement the radiative transfer in a simple and almost natural way. Computational efficiency results from the reduced number of sampling points on the non-equidistant frequency grids compared to equidistant frequency grids of uniform intervals.

Early IMK/IAA MIPAS/ENVISAT results

On March 1, 2002 the space-borne limb viewing mid-infrared high-resolution Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) has been brought on board the ENVISAT satellite into a polar sun-synchroneous orbit. Although the level-1 testing and validation phase has not been finished, ESA has made available datasets of 4 early orbits to several groups involved in MIPAS calibration/validation; the groups have been given the opportunity for functionality tests of their analysis codes. We here present some example results of the IMK/IAA MIPAS level-2 processor the concept of which is presented in a companion paper. Temperatures retrieved along the orbits are compared to ECMWF data. Processing parameters as chosen in pre-launch studies, such as cloud identification thresholds, microwindow selection, or instrument characteristics, are discussed. Preliminary retrievals for various atmospheric conditions are shown.

Comparisons of MIPAS-observed temperature profiles with other satellite measurements

MIPAS on ENVISAT measures vertical profiles of atmospheric temperature, ozone, and other species with nearly global coverage and high accuracy/precision. The standard observation mode covers the altitude region between 6 and 68 km. The atmospheric state parameters retrieved from MIPAS measurements using the IMK data analysis processor are compared with a number of other satellite observations. Our comparisons in this paper will focus on temperatures measured by MIPAS, HALOE, SABER, and UKMO Stratospheric Assimilated Data. Both individual profiles and zonal means measured by MIPAS and other instruments at different seasons and geolocations show reasonable agreement, though some differences exist due to characteristics of the individual instruments and observation scenarios. The MIPAS measurements during the stratospheric major sudden warming during the southern hemisphere winter of 2002 are also presented to show the features of this unusual event. The analysis indicates the reliability of MIPAS-IMK data products and their capability for providing valuable scientific information.

The global picture of the atmospheric composition provided by MIPAS on Envisat

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is a mid-infrared emission spectrometer which is part of the core payload of the Envisat satellite, launched by ESA in March 2002. It provides unique observations of the atmospheric spectral radiances in the 4.15 - 14.6 μm spectral interval with innovative limb scanning capabilities for the three dimensional observation of the atmospheric composition and processes. The species, the processes and events that have been studied with this instrument in its 10 years of operation are briefly reviewed.

Optimized forward and retrieval model for MIPAS near-real-time data processing

The IR emission limb sounder MIPAS will be operated as an ESA core instrument on the ENVISAT-1 satellite. Near real time retrieval of pressure, temperature and volume mixing ratio of five key species from calibrated spectra will be performed in the Level 2 processor of the ENVISAT Payload Data Segment. In order to develop an optimized retrieval algorithm suitable for the implementation in MIPAS Level 2 processor, an ESA supported study is being carried out. In the framework of this study, an optimized forward/retrieval code based on the global fit approach was implemented. In this approach all the spectra of a limb-scanning sequence are simultaneously fitted, so that error propagation in the altitude domain is avoided. The attained accuracy performances of the retrieval code are the following: (i) temperature accuracy < 2 K at all the altitudes covered by the standard MIPAS scan; (ii) tangent pressure error: < 3 percent; (iii) error on the retrieved VMR of the key species: < 5 percent at most of the latitudes of scientific interest 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 6 minutes on a SUN SPARCstation 20. The most effective code optimization were implemented in the radiative transfer model and in the computation of the jacobian of the retrieval.

Retrieval of PSC properties from MIPAS-ENVISAT measurements

The possibility to derive microphysical properties of polar stratospheric clouds from future MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) -- ENVISAT measurements was investigated. Available refractive index data for PSC candidates were intercompared in order to estimate their reliability. Especially for NAT the laboratory measurements differ significantly and for ternary H2SO4/HNO3/H2O solutions only one source of data exists. For simulating limb-spectra, a Mie model was implemented in the forward code KOPRA (Karlsruhe Optimized and Precise Radiative transfer Algorithm) in such a way that in parallel to the radiance spectra the derivatives with respect to a variety of microphysical aerosol parameters can be generated. Broadband forward calculations for small and large aerosols were made for various refractive indices. For large particles the PSC signal in the spectrum was up to forty times larger than the noise level. The signal for small particles was around the spectral noise. By minimizing the total retrieval error an automatic microwindow selection was performed for different PSC scenarios. Under the assumption of known radius and width of the aerosol size distribution resulting errors for number density retrieval were less than 3% (9 X 10-4 cm-3) for large and around 50% (7 cm-3) for small particles. For large particles it is possible to perform a two-parameter fit of number density and mode radius with errors less than 10%. Due to the Rayleigh- limit a distinction between radius and number density is not possible for small particles. However, the volume density can be derived with 12% (0.4 micrometer3/cm-3) uncertainty for large and 20% (2.2 X 10-2 micrometer3/cm-3) for small aerosols. These conclusions are valid as long as the aerosol layer is not optically thick which in our examples was the case for water ice (type II) PSCs of number density 0.2 cm-3 and radius 2.6 micrometer.

Performance of the near-real-time code for MOIPAS data analysis

An ESA supported study was carried out for the development of an optimized code for near real time retrieval of altitude profiles of pressure, temperature (p, T) and volume mixing ratio (VMR) of five key species (O3, H2O, HNO3, CH4 and N2O) from infrared limb sounding spectra recorded by MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), which will be operated on board ENVISAT-1 satellite. The implemented model is based on the Global Fit approach, i.e. all the limb-scanning spectra are simultaneously fitted, and on the analysis in narrow spectral intervals (microwindows). The trade-off between run time and accuracy of the retrieval was optimized from both the physical and mathematical point of view, with improvements 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 as follows: noise error on temperature less than 2 K at all the altitudes covered by the standard MIPAS scan (8 - 53 km), noise error on tangent pressure less than 3%, noise error on VMR of the target species less than 5% at most of the altitudes of scientific interest covered by the standard MIPAS scan, with a total run time of less than 6 minutes on a SUN SPARC station 20.