Abstract: Given a nonlinear dynamical systems with chaotic solution behaviour, we consider tracking a (unknown) reference solution using partial observations of the system. The talks will focus on sequential filtering/data assimilation algorithms based on ensembles of stochastic particles. Building on the popularity of the ensemble Kalman filter as well as its known limitations, I will discuss other variants of ensemble transform filters which do not rely on a Gaussian approximation to the ensemble of particles.