Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)

Abstract. Modeling and predicting changes in the function and structure of the terrestrial biosphere and its feedbacks to climate change strongly depends on our ability to accurately represent interactions of the carbon and water cycles and energy exchange. However, carbon fluxes, hydrological status, and energy exchange simulated by process-based terrestrial ecosystem models are subject to significant uncertainties, largely due to the poorly calibrated parameters. In this work, an adjoint-based data assimilation system (Nanjing University Carbon Assimilation System; NUCAS v1.0) was developed, which is capable of assimilating multiple observations to optimize process parameters of a satellite-data-driven ecosystem model – the Biosphere–atmosphere Exchange Process Simulator (BEPS). Data assimilation experiments were conducted to investigate the robustness of NUCAS and to test the feasibility and applicability of assimilating carbonyl sulfide (COS) fluxes from seven sites to enhance our understanding of stomatal conductance and photosynthesis. Results showed that NUCAS is able to achieve a consistent fit to COS observations across various ecosystems, including evergreen needleleaf forest, deciduous broadleaf forest, C3 grass, and C3 crop. Comparing model simulations with validation datasets, we found that assimilating COS fluxes notably improves the model performance in gross primary productivity and evapotranspiration, with average root-mean-square error (RMSE) reductions of 23.54 % and 16.96 %, respectively. We also showed that NUCAS is capable of constraining parameters through assimilating observations from two sites simultaneously and achieving a good consistency with single-site assimilation. Our results demonstrate that COS can provide constraints on parameters relevant to water, energy, and carbon processes with the data assimilation system and opens new perspectives for better understanding of the ecosystem carbon, water, and energy exchanges.

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Publication Details

Journal
Geoscientific model development
Published
2024-08-30
DOI
https://doi.org/10.5194/gmd-17-6337-2024
Citations
3
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
0.85

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article

Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)

Weimin Ju, Xiuli Xing, Mousong Wu, Fei Jiang et al.
3 citations
Geoscientific model development
Atmospheric and Environmental Gas Dynamics
0.85
article

Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)

Weimin Ju, Xiuli Xing, Mousong Wu, Fei Jiang, Michael Voßbeck, Jun Wang, Huajie Zhu, Thomas Kaminski, J.M. Chen
article en
3 citations

Abstract

Abstract. Modeling and predicting changes in the function and structure of the terrestrial biosphere and its feedbacks to climate change strongly depends on our ability to accurately represent interactions of the carbon and water cycles and energy exchange. However, carbon fluxes, hydrological status, and energy exchange simulated by process-based terrestrial ecosystem models are subject to significant uncertainties, largely due to the poorly calibrated parameters. In this work, an adjoint-based data assimilation system (Nanjing University Carbon Assimilation System; NUCAS v1.0) was developed, which is capable of assimilating multiple observations to optimize process parameters of a satellite-data-driven ecosystem model – the Biosphere–atmosphere Exchange Process Simulator (BEPS). Data assimilation experiments were conducted to investigate the robustness of NUCAS and to test the feasibility and applicability of assimilating carbonyl sulfide (COS) fluxes from seven sites to enhance our understanding of stomatal conductance and photosynthesis. Results showed that NUCAS is able to achieve a consistent fit to COS observations across various ecosystems, including evergreen needleleaf forest, deciduous broadleaf forest, C3 grass, and C3 crop. Comparing model simulations with validation datasets, we found that assimilating COS fluxes notably improves the model performance in gross primary productivity and evapotranspiration, with average root-mean-square error (RMSE) reductions of 23.54 % and 16.96 %, respectively. We also showed that NUCAS is capable of constraining parameters through assimilating observations from two sites simultaneously and achieving a good consistency with single-site assimilation. Our results demonstrate that COS can provide constraints on parameters relevant to water, energy, and carbon processes with the data assimilation system and opens new perspectives for better understanding of the ecosystem carbon, water, and energy exchanges.

Geoscientific model developmentVol. 17(16)
University of Toronto (CA), Ministry of Natural Resources (CN), Fudan University (CN), Nanjing University (CN)
National Natural Science Foundation of China, Nanjing University, National Key Research and Development Program of China
Openalex Percentile: Top 28%
Atmospheric and Environmental Gas Dynamics
0.85
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