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    A Revised Cross-Section Database for Gas Retrieval in the UV-Visible-Near IR Range, Applied to the GOMOS Retrieval Algorithm AerGOM

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    Authors
    Bingen, C.
    Robert, C.
    Hermans, C.
    Vanhellemont, F.
    Mateshvili, N.
    Dekemper, E.
    Fussen, D.
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    Discipline
    Earth and related Environmental sciences
    Subject
    absorption cross-section
    aerosol scattering
    GOMOS
    trace gas retrieval
    aerosol retrieval
    spectral inversion
    remote sensing
    Audience
    Scientific
    Date
    2019
    Metadata
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    Description
    In this paper, we present the revision of the cross-section database used for the retrieval of aerosol and gas species from remote sensing measurements by the GOMOS instrument onboard ENVISAT. The absorption cross-section spectra concern ozone, nitrogen dioxide and nitrogen trioxide, for which improved datasets have been published since the implementation of the original GOMOS cross-section database in preparation of the ENVISAT mission. We evaluate the molecular absorption cross-section spectra currently available for O3, NO2 and NO3, and we present and discuss our selection of datasets and the set-up of the revised absorption cross-section database, with the focus on these three gases. The objective is to provide an optimal characterization of their absorption spectrum over the UV-visible-near IR range used by AerGOM, a retrieval algorithm that was designed to optimize the retrieval of aerosol species from GOMOS measurements. Despite its application to the specific case of GOMOS, it is the aim of this work to cover a more general scope than this particular mission, and to provide an evaluation applicable to any other case of remote sensing experiment covering the UV to near IR range, possibly with a high spectral resolution.
    Citation
    Bingen, C.; Robert, C.; Hermans, C.; Vanhellemont, F.; Mateshvili, N.; Dekemper, E.; Fussen, D. (2019). A Revised Cross-Section Database for Gas Retrieval in the UV-Visible-Near IR Range, Applied to the GOMOS Retrieval Algorithm AerGOM. , Frontiers in Environmental Science, Vol. 118, Issue 7, A118, DOI: 10.3389/fenvs.2019.00118.
    Identifiers
    uri: https://orfeo.belnet.be/handle/internal/7346
    doi: http://dx.doi.org/10.3389/fenvs.2019.00118
    Type
    Article
    Peer-Review
    Yes
    Language
    eng
    Links
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