Ensemble-based simultaneous state and parameter estimation with MM5 Academic Article uri icon

abstract

  • The performance of the ensemble Kalman filter (EnKF) under imperfect model conditions is investigated through simultaneous state and parameter estimation for a numerical weather prediction model of operational complexity (MM5). The source of model error is assumed to be the uncertainty in the vertical eddy mixing coefficient. Assimilations are performed with a 12hour interval with simulated sounding and surface observations of horizontal winds and temperature. The mean estimated parameter value nicely converges to the true value within a satisfactory level of variability due to sufficient model sensitivity to parameter uncertainty and detectable (relative to ensemble sampling noise) correlation signal between the parameter and observed variables.

published proceedings

  • GEOPHYSICAL RESEARCH LETTERS

author list (cited authors)

  • Aksoy, A., Zhang, F., & Nielsen-Gammon, J. W.

citation count

  • 102

complete list of authors

  • Aksoy, Altug||Zhang, Fuqing||Nielsen-Gammon, John W

publication date

  • June 2006