  Numerical solvers using adaptive meshes can focus computational power on
important regions of a model domain capturing important or unresolved physics.
The adaptation can be informed by the model state, external information, or
made to depend on the model physics. In this latter case, one can think of the
mesh configuration {\it as part of the model state}. If observational data is
to be assimilated into the model, the question of updating the mesh
configuration with the physical values arises. Adaptive meshes present
significant challenges when using popular ensemble Data Assimilation (DA)
methods. We develop a novel strategy for ensemble-based DA for which the
adaptive mesh is updated along with the physical values. This involves
including the node locations as a part of the model state itself allowing them
to be updated automatically at the analysis step. This poses a number of
challenges which we resolve to produce an effective approach that promises to
apply with some generality. We evaluate our strategy with two testbed models in
1-d comparing to a strategy that does not update the mesh configuration. We
find updating the mesh improves the fidelity and convergence of the filter.
