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Evaluation of continental carbon cycle simulations with North American flux tower observations

Brett M Raczka, Kenneth J Davis, Deborah Huntzinger, Ronald P Neilson, Benjamin Poulter, Andrew D Richardson, Jingfeng Xiao, Ian Baker, Philippe Ciais, Trevor F Keenan, et al. (2013) ECOLOGICAL MONOGRAPHS. 83(4). p.531-556
abstract
Terrestrial biosphere models can help identify physical processes that control carbon dynamics, including land-atmosphere CO2 fluxes, and have great potential to predict the terrestrial ecosystem response to changing climate. The skill of models that provide continental-scale carbon flux estimates, however, remains largely untested. This paper evaluates the performance of continental-scale flux estimates from 17 models against observations from 36 North American flux towers. Fluxes extracted from regional model simulations were compared with co-located flux tower observations at monthly and annual time increments. Site-level model simulations were used to help interpret sources of the mismatch between the regional simulations and site-based observations. On average, the regional model runs overestimated the annual gross primary productivity (5%) and total respiration (15%), and they significantly underestimated the annual net carbon uptake (64%) during the time period 2000-2005. Comparison with site-level simulations implicated choices specific to regional model simulations as contributors to the gross flux biases, but not the net carbon uptake bias. The models performed the best at simulating carbon exchange at deciduous broadleaf sites, likely because a number of models used prescribed phenology to simulate seasonal fluxes. The models did not perform as well for crop, grass, and evergreen sites. The regional models matched the observations most closely in terms of seasonal correlation and seasonal magnitude of variation, but they have very little skill at interannual correlation and minimal skill at interannual magnitude of variability. The comparison of site vs. regional-level model runs demonstrated that (1) the interannual correlation is higher for site-level model runs, but the skill remains low; and (2) the underestimation of year-to-year variability for all fluxes is an inherent weakness of the models. The best-performing regional models that did not use flux tower calibration were CLM-CN, CASA-GFEDv2, and SIB3.1. Two flux tower calibrated, empirical models, EC-MOD and MOD17 broken vertical bar, performed as well as the best process-based models. This suggests that (1) empirical, calibrated models can perform as well as complex, process-based models and (2) combining process-based model structure with relevant constraining data could significantly improve model performance.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
flux towers, carbon fluxes, model-data comparison, terrestrial biosphere models, NET PRIMARY PRODUCTIVITY, ATMOSPHERE CO2 EXCHANGE, COMPARING GLOBAL-MODELS, INTERANNUAL VARIABILITY, ECOSYSTEM EXCHANGE, DECIDUOUS FOREST, DIOXIDE EXCHANGE, BIOSPHERE MODEL, ENERGY FLUXES, UNITED-STATES
journal title
ECOLOGICAL MONOGRAPHS
Ecol. Monogr.
volume
83
issue
4
pages
531 - 556
Web of Science type
Article
Web of Science id
000330526800006
JCR category
ECOLOGY
JCR impact factor
7.107 (2013)
JCR rank
8/141 (2013)
JCR quartile
1 (2013)
ISSN
0012-9615
DOI
10.1890/12-0893.1
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
4251545
handle
http://hdl.handle.net/1854/LU-4251545
date created
2014-01-27 16:23:57
date last changed
2018-06-21 07:54:52
@article{4251545,
  abstract     = {Terrestrial biosphere models can help identify physical processes that control carbon dynamics, including land-atmosphere CO2 fluxes, and have great potential to predict the terrestrial ecosystem response to changing climate. The skill of models that provide continental-scale carbon flux estimates, however, remains largely untested. This paper evaluates the performance of continental-scale flux estimates from 17 models against observations from 36 North American flux towers. Fluxes extracted from regional model simulations were compared with co-located flux tower observations at monthly and annual time increments. Site-level model simulations were used to help interpret sources of the mismatch between the regional simulations and site-based observations. On average, the regional model runs overestimated the annual gross primary productivity (5\%) and total respiration (15\%), and they significantly underestimated the annual net carbon uptake (64\%) during the time period 2000-2005. Comparison with site-level simulations implicated choices specific to regional model simulations as contributors to the gross flux biases, but not the net carbon uptake bias. The models performed the best at simulating carbon exchange at deciduous broadleaf sites, likely because a number of models used prescribed phenology to simulate seasonal fluxes. The models did not perform as well for crop, grass, and evergreen sites. The regional models matched the observations most closely in terms of seasonal correlation and seasonal magnitude of variation, but they have very little skill at interannual correlation and minimal skill at interannual magnitude of variability. The comparison of site vs. regional-level model runs demonstrated that (1) the interannual correlation is higher for site-level model runs, but the skill remains low; and (2) the underestimation of year-to-year variability for all fluxes is an inherent weakness of the models. The best-performing regional models that did not use flux tower calibration were CLM-CN, CASA-GFEDv2, and SIB3.1. Two flux tower calibrated, empirical models, EC-MOD and MOD17 broken vertical bar, performed as well as the best process-based models. This suggests that (1) empirical, calibrated models can perform as well as complex, process-based models and (2) combining process-based model structure with relevant constraining data could significantly improve model performance.},
  author       = {Raczka, Brett M and Davis, Kenneth J and Huntzinger, Deborah and Neilson, Ronald P and Poulter, Benjamin and Richardson, Andrew D and Xiao, Jingfeng and Baker, Ian and Ciais, Philippe and Keenan, Trevor F and Law, Beverly and Post, Wilfred M and Ricciuto, Daniel and Schaefer, Kevin and Tian, Hanqin and Tomelleri, Enrico and Verbeeck, Hans and Viovy, Nicolas},
  issn         = {0012-9615},
  journal      = {ECOLOGICAL MONOGRAPHS},
  keyword      = {flux towers,carbon fluxes,model-data comparison,terrestrial biosphere models,NET PRIMARY PRODUCTIVITY,ATMOSPHERE CO2 EXCHANGE,COMPARING GLOBAL-MODELS,INTERANNUAL VARIABILITY,ECOSYSTEM EXCHANGE,DECIDUOUS FOREST,DIOXIDE EXCHANGE,BIOSPHERE MODEL,ENERGY FLUXES,UNITED-STATES},
  language     = {eng},
  number       = {4},
  pages        = {531--556},
  title        = {Evaluation of continental carbon cycle simulations with North American flux tower observations},
  url          = {http://dx.doi.org/10.1890/12-0893.1},
  volume       = {83},
  year         = {2013},
}

Chicago
Raczka, Brett M, Kenneth J Davis, Deborah Huntzinger, Ronald P Neilson, Benjamin Poulter, Andrew D Richardson, Jingfeng Xiao, et al. 2013. “Evaluation of Continental Carbon Cycle Simulations with North American Flux Tower Observations.” Ecological Monographs 83 (4): 531–556.
APA
Raczka, B. M., Davis, K. J., Huntzinger, D., Neilson, R. P., Poulter, B., Richardson, A. D., Xiao, J., et al. (2013). Evaluation of continental carbon cycle simulations with North American flux tower observations. ECOLOGICAL MONOGRAPHS, 83(4), 531–556.
Vancouver
1.
Raczka BM, Davis KJ, Huntzinger D, Neilson RP, Poulter B, Richardson AD, et al. Evaluation of continental carbon cycle simulations with North American flux tower observations. ECOLOGICAL MONOGRAPHS. 2013;83(4):531–56.
MLA
Raczka, Brett M, Kenneth J Davis, Deborah Huntzinger, et al. “Evaluation of Continental Carbon Cycle Simulations with North American Flux Tower Observations.” ECOLOGICAL MONOGRAPHS 83.4 (2013): 531–556. Print.