Tilman Steck

Constrained profile retrieval applied to the observation mode of the Michelson Interferometer for Passive Atmospheric Sounding

To investigate the atmosphere of Earth and to detect changes in its environment, the Environmental Satellite will be launched by the European Space Agency in a polar orbit in October 2001. One of its payload instruments is a Fourier spectrometer, the Michelson Interferometer for Passive Atmospheric Sounding, designed to measure the spectral thermal emission of molecules in the atmosphere in a limb-viewing mode. The goal of this experiment is to derive operationally vertical profiles of pressure and temperature as well as of trace gases O(3), H(2)O, CH(4), N(2)O, NO(2), and HNO(3) from spectra on a global scale. A major topic in the analysis of the computational methodology for obtaining the profiles is how available a priori knowledge can be used and how this a priori knowledge affects corresponding results. Retrieval methods were compared and it was shown that an optimal estimation formalism can be used in a highly flexible way for this kind of data analysis. Beyond this, diagnostic tools, such as estimated standard deviation, vertical resolution, or degrees of freedom, have been used to characterize the results. Optimized regularization parameters have been determined, and a great effect from the choice of regularization and discretization on the results was demonstrated. In particular, we show that the optimal estimation formalism can be used to emulate purely smoothing constraints.

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.

Tomographic retrieval of atmospheric parameters from infrared limb emission observations

Typical inversion of limb-sounding measurements assumes local horizontal homogeneity of the atmosphere. This simplification corresponds to spectral radiance errors that can exceed the noise level of a typical infrared instrument by a factor of 10 and causes errors in retrieved state parameters. To avoid these errors and to take the horizontal structure of the atmosphere into account, a two-dimensional (2D) tomographic sequential estimation approach is described. Application to temperature retrievals from simulated measurements yields typical retrieval errors of the order of 1 K, and a one-dimensional retrieval with the same synthetic measurements shows differences to the true values up to 10 K in regions with strong horizontal inhomogeneities. The horizontal resolution of the 2D retrieval is even better (up to 40 km) than the horizontal tangent point spacing.

Trace gas retrieval including horizontal gradients

Abstract The development of a software package for the retrieval of vertical trace gas profiles from limb sounding measurements led to the analysis of the radiometric effects of inhomogeneous distributions of pressure, temperature and/or trace gases within simulated atmospheric layers as seen by a limb sounding instrument. These inhomogeneities called “horizontal gradients” affect the radiance measured by the instrument and — if unaccounted for - will degrade the retrieval quality of vertical pressure, temperature and/or trace gas profiles. On the other hand, if the retrieval of the vertical profiles is able to support the determination of horizontal gradients and if sufficient additional external knowledge about these gradients is available, then this offers an opportunity to retrieve vertical temperature and trace gas profiles with high accuracy. Several examples will demonstrate typical cases where the use of optimal estimation techniques including a priori knowledge of profiles and covariance data will deliver high quality results.

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.

Sequential and Joint Retrieval of Trace Gas Profiles

Abstract A common approach within the retrieval of atmospheric trace gas VMR profiles is the prior determination of pressure and temperature followed by sequential retrievals of various species. This, however, can lead to degraded results if errors from previously retrieved profiles propagate into succeeding computations. An alternative is given by the simultaneous (i.e. joint) retrieval of species combinations if the joint retrieval leads to smaller retrieval errors. During the development of a level 2 offline processor for the MIPAS instrument (an infrared limb sounding instrument to be flown on the ENVISAT mission in 2001), a number of tests based on a preliminary set of spectral microwindows were conducted that show characteristic effects resulting from sequential versus joint retrieval. We describe typical examples of our retrieval sequencing, notably the basic retrieval scheme, sources of error propagation, cases where a joint retrieval is advantageous — in particular, a combination of temperature retrieval with trace gas determination, issues of computational efficiency and memory requirements during joint retrievals, as well as the impact of microwindows.

Scientific Concept of the MIPAS Level 2 offline processor

The MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) limb emission spectrometer will be a core payload of ESAs ENVISAT research satellite.