Estimating the spatial exchange of carbon through the assimilation of earth observation derived products using an ensemble Kalman filter

This paper explores the potential to improve spatial estimates of key carbon fluxes by combining Earth Observation data with a simple ecosystem model. Spatial estimates of Leaf Area Index from MODIS at the kilometre scale over a coniferous forest site in Oregon are assimilated into an ecosystem model with an Ensemble Kalman filter. Results show that assimilating EO data improves the magnitude of estimates of Net Ecosystem Productivity relative to running the model alone, however the uncertainty is not significantly constrained. Spatially there is an underestimate in modelled carbon fluxes. This is attributed to error in the EO data which induces an underestimate in model stock estimates, as well as inadequacies in the model parameterisation.4 page(s