Elimination of hidden a priori information from remotely sensed profile data

T. von Clarmann (1) , U. Grabowski (1)

1 Forschungszentrum Karlsruhe

Profiles of atmospheric state parameters retrieved from remote measurements often contain a priori information which causes complication in the use of data for validation, comparison with models, or data assimilation. For such applications it often is desirable to remove the a priori information from the data product. If the retrieval involves an ill-posed inversion problem, formal removal of the a priori information requires resampling of the data on a coarser grid, which, however, is a prior constraint in itself. The fact that the trace of the averaging kernel matrix of a retrieval is equivalent to the number of degrees of freedom of the retrieval is used to define an appropriate information-centered representation of the data where each data point represents one degree of freedom. Since regridding implies further degradation of the data and thus causes additional loss of information, a re-regularization scheme has been developed which allows resampling without additional loss of information. For a typical ClONO₂ profile retrieved from spectra as measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the constrained retrieval has 9.7 degrees of freedom. After application of the proposed transformation to a coarser information-centered altitude grid, there are exactly 9 degrees of freedom left, and the averaging kernel on the coarse grid is unity. Pure resampling on the information-centered grid without re-regularization would reduce the degrees of freedom to 7.1.

Domaines: Océan, Atmosphère

T. von Clarmann, U. Grabowski. Elimination of hidden a priori information from remotely sensed profile data. Atmospheric Chemistry and Physics Discussions, 2006, 6 (4), pp.6723-6751. ⟨hal-00301994⟩