Abstract
A modified ensemble Kalman filter (KF) is proposed which can enhance performance for highly non-linear prognostic models. The algorithm differs from the traditional ensemble KF by the addition of an expectation maximization step, which estimates the parameters of a Gaussian mixture model for the ensemble of forecast states. The algorithm is tested in twin experiments using a simple phytoplankton—zooplankton model.