My main research interest is numerical methods for partial differential equations (PDEs),
    which are clearly important for the simulation of geophysical flows. In scientific computing,
    numerous issues must be addressed (other than purely mathematical) before one asserts
    that a particular method is worthy of implementation as a numerical solver. As a post-doctoral
    fellow with the Computational Fluid Dynamics Laboratory at McGill University, my research focused
    on parallel computing, iterative solvers and domain decomposition preconditioners. As a project
    scientist at NCAR in the Computational Sciences Section (CSS) of the Scientific Computing Division (SCD),
    these basic themes have expanded to include efficient time-stepping schemes for hyperbolic systems,
    high-order space discretization schemes and adaptive mesh refinement. My overall objective is the
    discovery of novel numerical methods for the construction of atmospheric models. In particular,
    I propose to pursue the following areas of research:

    - High-order conservative methods for atmospheric general circulation models.

    - Efficient semi-implicit semi-Lagrangian time stepping schemes.

    - Applications of adaptive mesh refinement (AMR) in atmospheric modeling.

    - Preconditioned Krylov iterative solvers for elliptic problems.