  Extensive numerical evidence shows that the assimilation of observations has
a stabilizing effect on unstable dynamics, in numerical weather prediction and
elsewhere. In this paper, we apply mathematically rigorous methods to showing
why this is so. Our stabilization results do not assume a full set of
observations and we provide examples where it suffices to observe the model's
unstable degrees of freedom.
