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Elimination of hidden a priori information from remotely sensed profile data

Clarmann, T. von; Grabowski, U. 1
1 Forschungszentrum Karlsruhe (FZKA)


Profiles of atmospheric state variables retrieved from remote measurements often contain a priori information which causes complication in the statistical use of data and in the comparison with other measured or modeled data. 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 in some sense, 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 informationcentered 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. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/110068110
Veröffentlicht am 27.04.2018
DOI: 10.5194/acp-7-397-2007
Zitationen: 27
Web of Science
Zitationen: 28
Zitationen: 41
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2007
Sprache Englisch
Identifikator ISSN: 1680-7316, 1680-7324
KITopen-ID: 110068110
HGF-Programm 12.04.02 (POF I, LK 01) Dynamik und Chemie der Stratosphäre
Erschienen in Atmospheric chemistry and physics
Verlag European Geosciences Union (EGU)
Band 7
Heft 2
Seiten 397-408
Externe Relationen Abstract/Volltext
Nachgewiesen in Dimensions
Web of Science
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