My current work revolves around using satellite observations to estimate the rate of emission of carbon dioxide into the atmosphere from the land and ocean surface. The problem is interesting from a climate point of view, since carbon dioxide is the most important greenhouse gas. From a mathematical point of view, it’s even more interesting than the data assimilation problem in numerical weather prediction, because the fluxes from the surface must be approximated at all model times, which implies correlation between errors at different times. This makes the typical sequential methods at the very least intellectually unsatisfying, though operational products often use them as a way to better approximate poorly understood error correlations.
Sean M. R. Crowell 