Dynamical contribution of mean potential vorticity pseudo-observations derived from MetOp/GOME2 ozone data into short-range weather forecast during high precipitation events

  • Authors

    • Siham Sbii National Center for Meteorological Research, National Meteorological Service, Casablanca
    • Mimoun Zazoui University of Hassan II Mohammedia, Faculty of sciences and techniques, Laboratory of condensed matter, Renewable Energy, Mohammedia,
    • Noureddine Semane National Center for Meteorological Research, National Meteorological Service, Casablanca
  • Atmospheric Dynamics, Data Assimilation, High Precipitation Events, Numerical Weather Prediction, Ozone.
  • Satellites are uniquely capable of providing uniform data coverage globally. Motivated by such capability, this study builds on a previously described methodology that generates numerical weather prediction initial conditions from satellite total column ozone data. The methodology is based on two principal steps. Firstly, the studied linear regression between vertical (100hPa-500hPa) Mean Potential Vorticity (MPV) and MetOp/GOME2 total ozone data (O3) generates MPV pseudo-observations. Secondly, the 3D variational (3D-Var) assimilation method is designed to take into account MPV pseudo-observations in addition to conventional observations.

    After a successful assimilation of MPV pseudo-observations using a 3D-Var approach within the Moroccan version of the ALADIN limited-area model, the present study aims to assess the dynamical behavior of the short-range forecast at upper levels during heavy precipitation events (HPEs). It is found that MPV assimilation offers the possibility to internally monitor the model upper-level dynamics in addition to the use of Water Vapor Satellite images.

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  • How to Cite

    Sbii, S., Zazoui, M., & Semane, N. (2015). Dynamical contribution of mean potential vorticity pseudo-observations derived from MetOp/GOME2 ozone data into short-range weather forecast during high precipitation events. International Journal of Basic and Applied Sciences, 4(2), 206-215. https://doi.org/10.14419/ijbas.v4i2.4435