Exploring the Potential Application of MetOp/GOME2 Ozone Data to Weather Analysis
In this study, a methodology of constructing and incorporating potential-vorticity (PV) data
into initial conditions of a limited-area model is proposed.
This methodology is based on the linear correlation between vertical (100hPa-500hPa) mean PV (MPV) and MetOp/GOME2 total ozone (O3) data. On one hand, a linear regression model is implemented to generate MPV from O3 data. On the other hand, a 3D-variational
method is designed to assimilate MPV pseudo-observations as a first step
toward investigating their dynamical impact.
Keywords: Remote Sensing, Ozone, Meteorology, Data assimilation, Numerical Weather Prediction.
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ABOUT THE AUTHORS
Siham Sbii
Centre National de Recherches Météorologiques, Direction de la Météorologie Nationale, Casablanca, Morocco.
Mimoune Zazoui
University of Hassan II, Faculty of sciences and techniques, Laboratory of condensed matter, Renewable Energy, Mohammedia, Morocco.
Noureddine Semane
ECMWF, Reading, UK.
Yann Michel
CNRM-GAME, Météo-France/CNRS, Toulouse, France.
Philippe Arbogast
CNRM-GAME, Météo-France/CNRS, Toulouse, France.
Siham Sbii
Centre National de Recherches Météorologiques, Direction de la Météorologie Nationale, Casablanca, Morocco.
Mimoune Zazoui
University of Hassan II, Faculty of sciences and techniques, Laboratory of condensed matter, Renewable Energy, Mohammedia, Morocco.
Noureddine Semane
ECMWF, Reading, UK.
Yann Michel
CNRM-GAME, Météo-France/CNRS, Toulouse, France.
Philippe Arbogast
CNRM-GAME, Météo-France/CNRS, Toulouse, France.
