Partitioning the solar radiant fluxes in forest canopies in the presence of snow

Abstract

The main goal of this study is to help bridge the gap between available remote sensing products and large‐scale global climate models. We present results from the application of an inversion method conducted using both MODerate resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging SpectroRadiometer (MISR) derived broadband visible and near‐infrared surface albedo products. This contribution is an extension of earlier efforts to optimally retrieve land surface fluxes and associated two‐stream model parameters (Pinty et al., 2007). It addresses complex geophysical scenarios involving snow occurrence in mid and high‐latitude evergreen and deciduous forest canopy systems. The detection of snow during the winter and spring seasons is based on the MODIS snow product. This information is used by our package to adapt the prior values, specifically the maximum likelihood and width of the 2‐D probability density functions (PDF) characterizing the background conditions of the forest floor. Our results (delivered as a Gaussian approximation of the PDFs of the retrieved model parameter values and radiant fluxes) illustrate the capability of the inversion package to retrieve meaningful land vegetation fluxes and associated model parameters during the year, despite the rather high temporal variability in the input products, in large part due to the occurrence of snow events. As a matter of fact, most of this temporal variability, as well as the small differences between the MODIS and MISR broadband albedos, appear to be largely captured by the albedo of the forest canopy background.