Atmospheric Water Vapour Profiling over Ocean/Land and for Clear/Cloudy Situations Using Microwave Observations View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018

AUTHORS

Filipe Aires

ABSTRACT

A water vapour retrieval algorithm has been developed that uses satellite observations in the microwave region. It is based on a neural network modelling and includes a dedicated calibration scheme of the satellite observations. The water vapour is retrieved for clear and cloudy scenes, over both ocean and land surfaces. Precipitation cases are excluded. The atmospheric relative humidity profile is retrieved on six atmospheric layers, together with the total column water vapour. The algorithm has been developed for the instruments AMSR-E/HSB (resp. AMSU-A/MHS) onboard AQUA (resp. MetOp) platforms. The principles of the inversion method are presented and the theoretical retrieval uncertainties are assessed using direct tests on simulated data as well as estimations using the traditional information content analysis. Then, the algorithm is tested using real observations from HSB/AMSRE (resp. MHS/AMSU-A) instruments on board AQUA (resp. MetOp) platforms. Results are compared to ECMWF analyses and to radiosondes. The standard deviation error for the total column water vapour is ∼4.5 kg m2 for both clear and for cloudy scenes, as compared to radiosondes over land, that include their own uncertainties. The atmospheric water vapour profile is retrieved on six atmospheric layers and the RMS error is estimated to be lower than 20% in relative humidity, even for the lower atmospheric layer over land. A posteriori validation tests on the brightness temperatures indicate an overall positive impact of the retrievals relatively to the a priori ECMWF analyses. More... »

PAGES

215-255

References to SciGraph publications

  • 2015-04. Clouds, circulation and climate sensitivity in NATURE GEOSCIENCE
  • Book

    TITLE

    Remote Sensing of Clouds and Precipitation

    ISBN

    978-3-319-72582-6
    978-3-319-72583-3

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-72583-3_9

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    http://dx.doi.org/10.1007/978-3-319-72583-3_9

    DIMENSIONS

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