Aug 25 2011
Our previous work on the remote-sensing based data assimilation framework has been extended to regional and global scales. It employs a subgrid‐scale representation of plant functional types (PFTs) and elevation classes to generate a globally applicable phenological parameter set. We are able to predict (or hindcast) a 50 year long (1960–2009) daily 1° × 1° global phenology climate …
Nov 26 2008
We have developed a computational framework for data assimilation of Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) and Leaf Area Index (LAI) from the MODerate Resolution Imaging Spectroradiometer (MODIS) to constrain empirical temperature, light, moisture and structural vegetation parameters in a prognostic phenology model. It uses the Ensemble Kalman Filter (EnKF) after …