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We developed a data assimilation system based on a particle filter\udapproach with the spatially explicit individual-based dynamic global\udvegetation model (SEIB-DGVM). We first performed an idealized observing\udsystem simulation experiment to evaluate the impact of assimilating the leaf\udarea index (LAI) data every 4 days, simulating the satellite-based LAI.\udAlthough we assimilated only LAI as a whole, the tree and grass LAIs were\udestimated separately with high accuracy. Uncertain model parameters and\udother state variables were also estimated accurately. Therefore, we extended\udthe experiment to the real world using the real Moderate Resolution Imaging\udSpectroradiometer (MODIS) LAI data and obtained promising results

Non-Gaussian data assimilation of satellite-based leaf area index observations with an individual-based dynamic global vegetation model