A global carbon assimilation system based on a dual optimization method
Ecological models are effective tools for simulating the distribution of global carbon sources and sinks. However, these models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) to an ecologi...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2015-02-01
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| Series: | Biogeosciences |
| Online Access: | http://www.biogeosciences.net/12/1131/2015/bg-12-1131-2015.pdf |
| _version_ | 1819242250789453824 |
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| author | H. Zheng Y. Li J. M. Chen T. Wang Q. Huang W. X. Huang L. H. Wang S. M. Li W. P. Yuan X. Zheng S. P. Zhang Z. Q. Chen F. Jiang |
| author_facet | H. Zheng Y. Li J. M. Chen T. Wang Q. Huang W. X. Huang L. H. Wang S. M. Li W. P. Yuan X. Zheng S. P. Zhang Z. Q. Chen F. Jiang |
| author_sort | H. Zheng |
| collection | DOAJ |
| description | Ecological models are effective tools for simulating the distribution
of global carbon sources and sinks. However, these models often
suffer from substantial biases due to inaccurate simulations of
complex ecological processes. We introduce a set of scaling factors
(parameters) to 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 simultaneously. We use GCAS-DOM to
estimate the global distribution of the CO<sub>2</sub> flux on
1° × 1° grid cells for the period from 2001 to
2007. Results show that land and ocean absorb −3.63 ± 0.50 and −1.82 ±
0.16 Pg C yr<sup>−1</sup>, respectively. North America, Europe
and China contribute −0.98 ± 0.15,
−0.42 ± 0.08 and −0.20 ±
0.29 Pg C yr<sup>−1</sup>, respectively. The uncertainties in
the flux after optimization by GCAS-DOM have been remarkably reduced
by more than 60%. Through parameter optimization, GCAS-DOM can
provide improved estimates of the carbon flux for each
PFT. Coniferous forest (−0.97 ± 0.27 Pg C yr<sup>−1</sup>)
is the largest contributor to the global carbon sink. Fluxes of
once-dominant deciduous forest generated by the Boreal Ecosystems
Productivity Simulator (BEPS) are reduced to
−0.78 ± 0.23 Pg C yr<sup>−1</sup>, the third largest
carbon sink. |
| first_indexed | 2024-12-23T14:36:49Z |
| format | Article |
| id | doaj.art-ec85e2bf5a084df8adf1357eb83551e2 |
| institution | Directory Open Access Journal |
| issn | 1726-4170 1726-4189 |
| language | English |
| last_indexed | 2024-12-23T14:36:49Z |
| publishDate | 2015-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Biogeosciences |
| spelling | doaj.art-ec85e2bf5a084df8adf1357eb83551e22022-12-21T17:43:21ZengCopernicus PublicationsBiogeosciences1726-41701726-41892015-02-011241131115010.5194/bg-12-1131-2015A global carbon assimilation system based on a dual optimization methodH. Zheng0Y. Li1J. M. Chen2T. Wang3Q. Huang4W. X. Huang5L. H. Wang6S. M. Li7W. P. Yuan8X. Zheng9S. P. Zhang10Z. Q. Chen11F. Jiang12Department of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, ChinaDepartment of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, ChinaDepartment of Geography and Program in Planning, University of Toronto, Toronto, M5S 3G3, CanadaDepartment of Mathematics and Statistics, University of Otago, Dunedin 9016, New ZealandDepartment of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, ChinaDepartment of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, ChinaDepartment of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, ChinaDepartment of Statistics, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, ChinaCollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaCollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaCollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaCollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaInternational Institute of Earth System Science, Nanjing University, Nanjing 210093, ChinaEcological models are effective tools for simulating the distribution of global carbon sources and sinks. However, these models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) to 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 simultaneously. We use GCAS-DOM to estimate the global distribution of the CO<sub>2</sub> flux on 1° × 1° grid cells for the period from 2001 to 2007. Results show that land and ocean absorb −3.63 ± 0.50 and −1.82 ± 0.16 Pg C yr<sup>−1</sup>, respectively. North America, Europe and China contribute −0.98 ± 0.15, −0.42 ± 0.08 and −0.20 ± 0.29 Pg C yr<sup>−1</sup>, respectively. The uncertainties in the flux after optimization by GCAS-DOM have been remarkably reduced by more than 60%. Through parameter optimization, GCAS-DOM can provide improved estimates of the carbon flux for each PFT. Coniferous forest (−0.97 ± 0.27 Pg C yr<sup>−1</sup>) is the largest contributor to the global carbon sink. Fluxes of once-dominant deciduous forest generated by the Boreal Ecosystems Productivity Simulator (BEPS) are reduced to −0.78 ± 0.23 Pg C yr<sup>−1</sup>, the third largest carbon sink.http://www.biogeosciences.net/12/1131/2015/bg-12-1131-2015.pdf |
| spellingShingle | H. Zheng Y. Li J. M. Chen T. Wang Q. Huang W. X. Huang L. H. Wang S. M. Li W. P. Yuan X. Zheng S. P. Zhang Z. Q. Chen F. Jiang A global carbon assimilation system based on a dual optimization method Biogeosciences |
| title | A global carbon assimilation system based on a dual optimization method |
| title_full | A global carbon assimilation system based on a dual optimization method |
| title_fullStr | A global carbon assimilation system based on a dual optimization method |
| title_full_unstemmed | A global carbon assimilation system based on a dual optimization method |
| title_short | A global carbon assimilation system based on a dual optimization method |
| title_sort | global carbon assimilation system based on a dual optimization method |
| url | http://www.biogeosciences.net/12/1131/2015/bg-12-1131-2015.pdf |
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