• Open Access

Potential of shipborne GPS atmospheric delay data for prediction of Mediterranean intense weather events

Authors

  • K. Boniface,

    Corresponding author
    1. Géosciences Montpellier, Université Montpellier II/CNRS, UMR 5243, CC 60, Place E. Bataillon 34095, Montpellier Cedex 5, France
    Current affiliation:
    1. Environment Canada, Data Assimilation and Satellite Meteorology Research Section, 2121 Transcanada, H9P 1J3 Dorval, QC, Canada
    • Géosciences Montpellier, Université Montpellier II/CNRS, UMR 5243, CC 60, Place E. Bataillon, 34095 Montpellier Cedex 5, France.
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  • C. Champollion,

    1. Géosciences Montpellier, Université Montpellier II/CNRS, UMR 5243, CC 60, Place E. Bataillon 34095, Montpellier Cedex 5, France
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  • J. Chery,

    1. Géosciences Montpellier, Université Montpellier II/CNRS, UMR 5243, CC 60, Place E. Bataillon 34095, Montpellier Cedex 5, France
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  • V. Ducrocq,

    1. CNRM-GAME, Météo-France/CNRS, 42 Avenue G. Coriolis, 31057 Toulouse Cedex, France
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  • C. Rocken,

    1. GPS Solutions, Inc., 1320 Pearl Street, Suite 310, Boulder, Colorado 80302, USA
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  • E. Doerflinger,

    1. Géosciences Montpellier, Université Montpellier II/CNRS, UMR 5243, CC 60, Place E. Bataillon 34095, Montpellier Cedex 5, France
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  • P. Collard

    1. Géosciences Montpellier, Université Montpellier II/CNRS, UMR 5243, CC 60, Place E. Bataillon 34095, Montpellier Cedex 5, France
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Abstract

High spatial and temporal variability of mesoscale moisture fields is still a challenge for quantitative precipitation forecast within numerical weather prediction (NWP) models especially over ocean regions where observations are lacking. This study presents the comparison between integrated water vapor over the Mediterranean Sea determined from shipborne GPS, the NWP ALADIN/Météo-France model and MODIS retrieval during a 4-month campaign (autumn 2008).

While moisture prediction of the NWP remains accurate during most of the observation period, there are significant periods with offsets between GPS data and model predictions. We analyze such events and discuss the associated meteorological situation. Copyright © 2012 Royal Meteorological Society

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