Amal El Akkraoui

Amal El Akkraoui

  • SUPPORT SCIENTIST
  • 301.614.5500
  • NASA/GSFC
  • Mail Code: 610.1
  • Greenbelt , MD 20771
  • Employer: SCIENCE SYSTEMS AND APPLICATIONS INC
  • Brief Bio

    Research scientist in atmospheric data assimilation at GMAO-NASA since 2010. PhD in astmospheric and oceanic sciences from McGill University (Canada), and joint engineering degree in meteorology from EHTP (Morocco), and ENM (France). Worked on various variational methods such as the primal 3D/4D-Var, the dual 3D/4D-PSAS, as well as the primal and dual weak-constraint 4D-Var/PSAS. Currently focusing on hybrid approaches, combining deterministic variational and probabilistic ensemble techniques.

    Research Interests

    - Variational and hybrid data assimilation. - Weak-constraint formulation of variational data assimilation. - Modelling and estimation of background and model error statistics. - Iterative Minimization techniques for solving large linear systems: the Conjugate and Bi- Conjugate Gradient, Minres and GMRES.


    Positions/Employment

    2010 - Present

    Research Scientist in atmospheric data assimilation.

    Science Systems and Applications Inc., NASA Goddard Space flight center, Greenbelt, Maryland. Global Modeling and Assimilation Office, Code 610.1
    - Implementing GMAO's 3D and 4D hybrid data assimilation system.
    - Upgrading the background error covariance statistics.
    - Implemented a new minimization technique (Bi-Conjugate Gradient) for solving variational analysis problem and worked on improving the preconditioning of the minimization.

    Education

    PhD Atmospheric and Oceanic Sciences
    McGill University, Canada, 2010.

    Project Management Professional Certification (PMP)

    Project Management Institute, 2018


    Master and Engineering Degree - meteorology
    National School of Meteorology (Ecole Nationale de la Meteorologie - ENM), Toulouse, France, 2004.

    Engineering Degree - meteorology
    Hassania School of Civil Engineering (Ecole Hassania des Travaux publics - EHTP), Casablanca, Morocco. Joint degree with ENM, 2004.
     

    Teaching Experience

    Teaching Assistant at McGill University for various classes:

    “Atmospheric and oceanic dynamics”, “Introduction to oceanic studies”, “Introduction to atmospheric studies”.

    Other Professional Information

    Fluent in Arabic and French.

    Publications

    Refereed

    Privé, N. C., R. M. Errico, R. Todling, and A. El Akkraoui. 2020. "Evaluation of adjoint‐based observation impacts as a function of forecast length using an Observing System Simulation Experiment." Quarterly Journal of the Royal Meteorological Society, qj.3909 [10.1002/qj.3909]

    El Akkraoui, A., Y. Tremolet, and R. Todling. 2013. "Preconditioning of variational data assimilation and the use of a bi-conjugate gradient method." Q.J.R. Meteorol. Soc., 139 (672): 731-741 [10.1002/qj.1997]

    Akkraoui, A. E., and P. Gauthier. 2010. "Convergence properties of the primal and dual forms of variational data assimilation." Quarterly Journal of the Royal Meteorological Society, 136 (646): 107-115 [10.1002/qj.545]

    El Akkraoui, A., P. Gauthier, S. Pellerin, and S. Buis. 2008. "Intercomparison of the primal and dual formulations of variational data assimilation." Quarterly Journal of the Royal Meteorological Society, 134 (633): 1015-1025 [10.1002/qj.257]

    Non-Refereed

    Todling, R., and A. El Akkraoui. 2018. "The GMAO Hybrid Ensemble-Variational Atmospheric Data Assimilation System: Version 2.0." NASA/TM-2018-104606 50: 184pp [Full Text (Link)]

    Errico, R. M., N. C. Prive, D. Carvalho, et al. M. E. Sienkiewicz, A. El Akkraoui, J. Guo, R. Todling, W. R. Mccarty, W. M. Putman, A. M. Da Silva, R. Gelaro, and I. Moradi. 2017. "Description of the GMAO OSSE for Weather Analysis Software Package: Version 3." NASA Technical Report Series on Global Modeling and Data Assimilation, NASA/TM-2017-104606 48: 156 pp. [Full Text (Link)]

    Brief Bio

    Research scientist in atmospheric data assimilation at GMAO-NASA since 2010. PhD in astmospheric and oceanic sciences from McGill University (Canada), and joint engineering degree in meteorology from EHTP (Morocco), and ENM (France). Worked on various variational methods such as the primal 3D/4D-Var, the dual 3D/4D-PSAS, as well as the primal and dual weak-constraint 4D-Var/PSAS. Currently focusing on hybrid approaches, combining deterministic variational and probabilistic ensemble techniques.

    Publications

    Refereed

    Privé, N. C., R. M. Errico, R. Todling, and A. El Akkraoui. 2020. "Evaluation of adjoint‐based observation impacts as a function of forecast length using an Observing System Simulation Experiment." Quarterly Journal of the Royal Meteorological Society qj.3909 [10.1002/qj.3909]

    El Akkraoui, A., Y. Tremolet, and R. Todling. 2013. "Preconditioning of variational data assimilation and the use of a bi-conjugate gradient method." Q.J.R. Meteorol. Soc. 139 (672): 731-741 [10.1002/qj.1997]

    Akkraoui, A. E., and P. Gauthier. 2010. "Convergence properties of the primal and dual forms of variational data assimilation." Quarterly Journal of the Royal Meteorological Society 136 (646): 107-115 [10.1002/qj.545]

    El Akkraoui, A., P. Gauthier, S. Pellerin, and S. Buis. 2008. "Intercomparison of the primal and dual formulations of variational data assimilation." Quarterly Journal of the Royal Meteorological Society 134 (633): 1015-1025 [10.1002/qj.257]

    Non-Refereed

    Todling, R., and A. El Akkraoui. 2018. "The GMAO Hybrid Ensemble-Variational Atmospheric Data Assimilation System: Version 2.0." NASA/TM-2018-104606 50 184pp [Full Text (Link)]

    Errico, R. M., N. C. Prive, D. Carvalho, et al. M. E. Sienkiewicz, A. El Akkraoui, J. Guo, R. Todling, W. R. Mccarty, W. M. Putman, A. M. Da Silva, R. Gelaro, and I. Moradi. 2017. "Description of the GMAO OSSE for Weather Analysis Software Package: Version 3." NASA Technical Report Series on Global Modeling and Data Assimilation, NASA/TM-2017-104606 48 156 pp. [Full Text (Link)]

                                                                                                                                                                                            
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