  We propose a new type of the Ensemble Kalman Filter (EnKF), which uses the
Fast Fourier Transform (FFT) for covariance estimation from a very small
ensemble with automatic tapering, and for a fast computation of the analysis
ensemble by convolution, avoiding the need to solve a sparse system with the
tapered matrix. The FFT EnKF is combined with the morphing EnKF to enable the
correction of position errors, in addition to amplitude errors, and
demonstrated on WRF-Fire, the Weather Research Forecasting (WRF) model coupled
with a fire spread model implemented by the level set method.
