Articles | Volume 12, issue 4
https://doi.org/10.5194/bg-12-1131-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-12-1131-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 Feb 2015
Research article |
| 24 Feb 2015
A global carbon assimilation system based on a dual optimization method
H. Zheng
Department of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China
Y. Li
CORRESPONDING AUTHOR
Department of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China
J. M. Chen
CORRESPONDING AUTHOR
Department of Geography and Program in Planning, University of Toronto, Toronto, M5S 3G3, Canada
International Institute of Earth System Science, Nanjing University, Nanjing 210093, China
Department of Mathematics and Statistics, University of Otago, Dunedin 9016, New Zealand
Q. Huang
Department of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China
W. X. Huang
Department of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China
L. H. Wang
Department of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China
S. M. Li
Department of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China
W. P. Yuan
College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
X. Zheng
College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
S. P. Zhang
College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
Z. Q. Chen
College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
International Institute of Earth System Science, Nanjing University, Nanjing 210093, China
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Cited
7 citations as recorded by crossref.
- Invert global and China's terrestrial carbon fluxes over 2019–2021 based on assimilating richer atmospheric CO2 observations J. Li et al. 10.1016/j.scitotenv.2024.172320
- The effects of spatiotemporal patterns of atmospheric CO2 concentration on terrestrial gross primary productivity estimation Z. Sun et al. 10.1007/s10584-020-02903-2
- If Some Critical Regions Achieve Carbon Neutrality, How Will the Global Atmospheric CO2 Concentration Change? J. Li et al. 10.3390/rs16091486
- Evaluation and improvement of the daily boreal ecosystem productivity simulator in simulating gross primary productivity at 41 flux sites across Europe S. Zhang et al. 10.1016/j.ecolmodel.2017.11.023
- Data assimilation method based on the constraints of confidence region Y. Li et al. 10.1007/s00376-017-7045-y
- Impacts of reduced model complexity and driver resolution on cropland ecosystem photosynthesis estimates A. Revill et al. 10.1016/j.fcr.2015.12.006
- Estimating cropland carbon fluxes: A process-based model evaluation at a Swiss crop-rotation site A. Revill et al. 10.1016/j.fcr.2019.02.006
5 citations as recorded by crossref.
- Invert global and China's terrestrial carbon fluxes over 2019–2021 based on assimilating richer atmospheric CO2 observations J. Li et al. 10.1016/j.scitotenv.2024.172320
- The effects of spatiotemporal patterns of atmospheric CO2 concentration on terrestrial gross primary productivity estimation Z. Sun et al. 10.1007/s10584-020-02903-2
- If Some Critical Regions Achieve Carbon Neutrality, How Will the Global Atmospheric CO2 Concentration Change? J. Li et al. 10.3390/rs16091486
- Evaluation and improvement of the daily boreal ecosystem productivity simulator in simulating gross primary productivity at 41 flux sites across Europe S. Zhang et al. 10.1016/j.ecolmodel.2017.11.023
- Data assimilation method based on the constraints of confidence region Y. Li et al. 10.1007/s00376-017-7045-y
2 citations as recorded by crossref.
Saved (final revised paper)
Saved (preprint)
Latest update: 02 Nov 2024
Short summary
Ecological models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) for an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a dual optimization method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state on 1 degree grid cells simultaneously.
Ecological models often suffer from substantial biases due to inaccurate simulations of complex...
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