Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 14
Articles | Volume 15, issue 14
https://doi.org/10.5194/gmd-15-5511-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-5511-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 14
Development and technical paper
 | 
19 Jul 2022
Development and technical paper |  | 19 Jul 2022

Improving the joint estimation of CO2 and surface carbon fluxes using a constrained ensemble Kalman filter in COLA (v1.0)

Zhiqiang Liu, Ning Zeng, Yun Liu, Eugenia Kalnay, Ghassem Asrar, Bo Wu, Qixiang Cai, Di Liu, and Pengfei Han

Data sets

The Gaussian Approach to Adaptive Covariance Inflation and Its Implementation with the Local Ensemble Transform Kalman Filter (https://github.com/takemasa-miyoshi/letkf) Takemasa Miyoshi https://doi.org/10.1175/2010MWR3570.1

Model code and software

The Constrained Ensemble Kalman Filter used in the COLA data assimilation system Zhiqiang Liu and Ning Zeng https://doi.org/10.5281/zenodo.5746140

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Short summary
We described the application of a constrained ensemble Kalman filter (CEnKF) in a joint CO2 and surface carbon fluxes estimation study. By assimilating the pseudo-surface and OCO-2 observations, the annual global flux estimation is significantly biased without mass conservation. With the additional CEnKF process, the CO2 mass is strictly constrained, and the estimation of annual fluxes is significantly improved.
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