Siegfried Hilgers

Multi-parameter regularization method for atmospheric remote sensing

Abstract The iteratively regularized Gauss–Newton algorithm with simple bounds on the variables is extended to the multi-parameter case. The global regularization matrix is computed by using the L-curve method for a sequence of one-parameter regularization problems. Numerical results concerning the joint retrieval of O 3 and NO 2 profiles using the scattered light from the limb of the atmosphere are presented.

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.

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.