Speaker
Description
Atmosperic invere modelling is a method for constraining Earth surface fluxes (sinks and sources) of green house gases using measurements of athmosperic concentrations. The (linear) link between atmospheric concentration and fluxes are provided by an atmospheric transport model. Since the number of unknown surfaces fluxes is much larger than the number of observed atmospheric concentrations, the inverse problem is ill-conditioned. Requiring further assumption on the fluxes, leading to a Bayesian model. Hitorically, fluxes are discretized to a grid and modelled by a multivariate Gaussian distribution. Instead, we define the flux on a continuous spatial domain, with fluxes modelled as Gaussian Markov Random Fields, including both spatial and temporal dependence.
