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    Description of algorithms for co-locating and comparing gridded model data with remote-sensing observations

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    Langerock(2015).pdf (204.1Kb)
    Authors
    Langerock, B.
    De Maziere, M.
    Hendrick, F.
    Vigouroux, C.
    Desmet, F.
    Dils, B.
    Niemeijer, S.
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    Discipline
    Earth and related Environmental sciences
    Subject
    algorithm
    atmospheric modeling
    comparative study
    European Union
    forecasting method
    instrumentation
    model validation
    monitoring system
    qualitative analysis
    remote sensing
    uncertainty analysis
    Audience
    Scientific
    Date
    2015
    Metadata
    Show full item record
    Description
    MACC-II,III, Monitoring Atmospheric Composition and Climate, is the current pre-operational Copernicus Atmosphere Monitoring Service (CAMS). It provides data records on atmospheric composition for recent years, present conditions and forecasts (a few days ahead). To support the quality assessment of the CAMS products, the EU FP7 project Network Of ground-based Remote-Sensing Observations (NORS) created a server to validate the gridded MACC-II,III/CAMS model data against remote-sensing observations from the Network for the Detection of Atmospheric Composition Change (NDACC), for a selected set of target species and pilot stations. This paper describes in detail the algorithms used in this validation server. Amongst others, the algorithms take into account the horizontal displacement of the measured profiles from the location of the instrument, the vertical averaging and uncertainty propagation.
    Citation
    Langerock, B.; De Maziere, M.; Hendrick, F.; Vigouroux, C.; Desmet, F.; Dils, B.; Niemeijer, S. (2015). Description of algorithms for co-locating and comparing gridded model data with remote-sensing observations. , Geoscientific Model Development, Vol. 8, Issue 3, 911-921, DOI: 10.5194/gmd-8-911-2015.
    Identifiers
    uri: https://orfeo.belnet.be/handle/internal/2716
    doi: http://dx.doi.org/10.5194/gmd-8-911-2015
    scopus: 2-s2.0-84926160859
    Type
    Article
    Peer-Review
    Yes
    Language
    eng
    Links
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