Assimilating remotely sensed white-sky and black-sky albedos for the retrieval of terrestrial canopy leaf area index and the clumping factor
Earth observation datasets offer an accurate and globally rich source of information and when used in conjunction with mathematical models can improve our knowledge of the true state of Essential Climate Variables (ECVs). The Sellers model of terrestrial radiative transfer, due to its relative computational inexpensiveness, is currently used in state of the art land surface schemes including the Joint UK Land Surface Environment Simulator (JULES). One shortfall of this model is the assumption that leaves are randomly distributed; this is often not the case in nature where we see clumping of leaf elements. The Sellers model can be modified to include this clumping factor. Here we confront the modified model with remotely sensed white sky and black sky albedo products in the visible and near-infrared spectral wavebands to retrieve an optimal Leaf Area Index (LAI) time series along with improved model parameter estimates, the clumping factor and uncertainty information.
Dr. Natalie Douglas University of Surrey