Retrieval of total leaf area index and its sunlit fraction using DSCOVR data

The Earth sensors on the Deep Space Climate Observatory (DSCOVR) platform will view the full sunlit disk of the Earth and provide surface reflectance in near retro-solar direction. In the RED spectral band due to strong absorption by leaves the single scattering dominates. The backscatters therefore are directly related to the sunlit fraction of the leaf area, a variable required by many global models of climate, hydrology, biogeochemistry, and ecology. In NIR spectral region a leaf absorbs little radiation. This gives rise to photon multiple interactions. The backscatters become dependent on both the total leaf area and its sunlit fraction due to the strong effect of multiple scattering. This feature allows us to retrieve the total leaf area index (LAI) and its sunlit fraction from DSCOVR data. The operational NASA MODIS LAI algorithm ingests up to seven atmosphere-corrected surface spectral bi-directional reflectance factors and their uncertainties and outputs the most probable values for pixel LAI and their respective dispersions. The MODIS retrieval technique is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters to adjust the LUT for sensor spectral band characteristics, data resolution and observation uncertainties. Here we will demonstrate the feasibility of adjusting the NASA operational algorithm to retrieve the total LAI and its sunlit fraction from synthetic DSCOVR data with an emphasis on achieving consistency and complementarity between DSCOVR and existing NASA land surface products.