  Spatially dependent parameters of a two-component chaotic reaction-diffusion
PDE model describing ocean ecology are observed by sampling a single species.
We estimate model parameters and the other species in the system by
autosynchronization, where quantities of interest are evolved according to
misfit between model and observations, to only partially observed data. Our
motivating example comes from oceanic ecology as viewed by remote sensing data,
but where noisy occluded data are realized in the form of cloud cover. We
demonstrate a method to learn a large-scale coupled synchronizing system that
represents spatio-temporal dynamics and apply a network approach to analyze
manifold stability.
