Integrating Eddy Covariance Information with Beps Model Using a Variational Assimilation Scheme for Improving Temporally Continuous Gpp Estimation

Abstract

The gross primary productivity (GPP) is an essential parameter of terrestrial carbon cycle, and simulation of GPP through terrestrial ecosystem process model usually needs a specification of model parameter. However, estimating model parameters in situ field or laboratory is a laborious and tedious work, causing a general lack of data. In this study, a reliable variational data assimilation scheme integrating Boreal Ecosystem Productivity Simulator (BEPS) with eddy covariance fluxes, was proposed to account for the seasonal variations of model parameters and improve temporally continuous GPP estimation. Results suggested that the proposed variational assimilation scheme in our study could effectively track the seasonal variations of model parameters. With optimal temporally continuous values of parameters, BEPS model had a better performance and potential ability for the GPP estimation.