Daftar Isi: The Constrained Ensemble Kalman Filter used in the COLA data assimilation system

Daftar Isi:

Atmospheric inversion of carbon dioxide (CO2) measurements to understand carbon sources and sinks has made great progress over the last two decades. However, most of the studies, including four-dimension variational (4D-Var), Ensemble Kalman filter (EnKF), and Bayesian synthesis approaches, obtains directly only fluxes while CO2 concentration is derived with the forward model as post-analysis. However, the direct update of the CO2 state will destroy the mass balance. To overcome this shortcoming, here we introduce a Constrained Ensemble Kalman Filter (CEnKF) approach to ensure the conservation of global CO2 mass. After a standard assimilation procedure, an additional assimilation process is applied to adjust CO2 at each model grid point and to ensure the consistency between the analysis and the first guess of global CO2 mass.