Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble Kalman filter

Process-based terrestrial ecosystem models have been widely used to simulate carbon cycle, climate and ecosystem interactions. Some parameters used in biological functions often change seasonally and inter-annually. In this study, sequential data assimilation with an ensemble Kalman filter is designed to optimize the key parameters of the Boreal Ecosystem Producitivity Simulator (BEPS) model, taking into account the errors in the input, …