Four-dimensional local ensemble transform Kalman filter: numerical experiments with a global circulation model

Authors

  • JOHN HARLIM,

    Corresponding author
    1. Department of Mathematics and Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, USA
    Search for more papers by this author
  • BRIAN R. HUNT

    1. Department of Mathematics and Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, USA
    Search for more papers by this author

*Corresponding author.
e-mail: jharlim@cims.nyu.edu
Present address: Courant Institute of Mathematical Sciences, New York University, 251 Mercer st., New York, NY 10012, USA

ABSTRACT

We present a four-dimensional ensemble Kalman filter (4D-LETKF) that approximately and efficiently solves a variational problem similar to that solved by 4D-VAR, and report numerical results with the Simplified-Parametrized primitive Equation Dynamics model, a simplified global atmospheric model. We discuss the relationship of 4D-LETKF to other ensemble Kalman filters and, in our simulations, compare it with two simpler approaches to assimilating asynchronous observations.

 We find that 4D-LETKF significantly improves on the approach of treating asynchronous observations as if they occur at the analysis time. For a sufficiently short analysis time interval, the approach of computing innovations from the background state at the observation times and treating those innovations as if they occur at the analysis time is comparable to 4D-LETKF, but for longer analysis intervals, we find that 4D-LETKF is superior to this approach.

Ancillary