Abstract
Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO 2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site-years, 10 biomes, and includes two large-scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models' ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model-data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
| Original language | English (US) |
|---|---|
| Article number | G00H05 |
| Journal | Journal of Geophysical Research E: Planets |
| Volume | 115 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2010 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Soil Science
- Forestry
- Water Science and Technology
- Palaeontology
- Atmospheric Science
- Aquatic Science
- Ecology
Cite this
A model-data intercomparison of CO2 exchange across North America : Results from the North American Carbon Program site synthesis. / Schwalm, Christopher R; Williams, Christopher A.; Schaefer, Kevin; Anderson, Ryan; Arain, M. Altaf; Baker, Ian; Barr, Alan; Black, T. Andrew; Chen, Guangsheng; Chen, Jing Ming; Ciais, Philippe; Davis, Kenneth J.; Desai, Ankur; Dietze, Michael; Dragoni, Danilo; Fischer, Marc L.; Flanagan, Lawrence B.; Grant, Robert; Gu, Lianhong; Hollinger, David; Izaurralde, R. Csar; Kucharik, Chris; Lafleur, Peter; Law, Beverly E.; Li, Longhui; Li, Zhengpeng; Liu, Shuguang; Lokupitiya, Erandathie; Luo, Yiqi; Ma, Siyan; Margolis, Hank; Matamala, Roser; McCaughey, Harry; Monson, Russell K.; Oechel, Walter C.; Peng, Changhui; Poulter, Benjamin; Price, David T.; Riciutto, Dan M.; Riley, William; Sahoo, Alok Kumar; Sprintsin, Michael; Sun, Jianfeng; Tian, Hanqin; Tonitto, Christina; Verbeeck, Hans; Verma, Shashi B.
In: Journal of Geophysical Research E: Planets, Vol. 115, No. 4, G00H05, 2010.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A model-data intercomparison of CO2 exchange across North America
T2 - Results from the North American Carbon Program site synthesis
AU - Schwalm, Christopher R
AU - Williams, Christopher A.
AU - Schaefer, Kevin
AU - Anderson, Ryan
AU - Arain, M. Altaf
AU - Baker, Ian
AU - Barr, Alan
AU - Black, T. Andrew
AU - Chen, Guangsheng
AU - Chen, Jing Ming
AU - Ciais, Philippe
AU - Davis, Kenneth J.
AU - Desai, Ankur
AU - Dietze, Michael
AU - Dragoni, Danilo
AU - Fischer, Marc L.
AU - Flanagan, Lawrence B.
AU - Grant, Robert
AU - Gu, Lianhong
AU - Hollinger, David
AU - Izaurralde, R. Csar
AU - Kucharik, Chris
AU - Lafleur, Peter
AU - Law, Beverly E.
AU - Li, Longhui
AU - Li, Zhengpeng
AU - Liu, Shuguang
AU - Lokupitiya, Erandathie
AU - Luo, Yiqi
AU - Ma, Siyan
AU - Margolis, Hank
AU - Matamala, Roser
AU - McCaughey, Harry
AU - Monson, Russell K.
AU - Oechel, Walter C.
AU - Peng, Changhui
AU - Poulter, Benjamin
AU - Price, David T.
AU - Riciutto, Dan M.
AU - Riley, William
AU - Sahoo, Alok Kumar
AU - Sprintsin, Michael
AU - Sun, Jianfeng
AU - Tian, Hanqin
AU - Tonitto, Christina
AU - Verbeeck, Hans
AU - Verma, Shashi B.
PY - 2010
Y1 - 2010
N2 - Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO 2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site-years, 10 biomes, and includes two large-scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models' ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model-data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
AB - Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO 2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site-years, 10 biomes, and includes two large-scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models' ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model-data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
UR - http://www.scopus.com/inward/record.url?scp=78650291361&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650291361&partnerID=8YFLogxK
U2 - 10.1029/2009JG001229
DO - 10.1029/2009JG001229
M3 - Article
AN - SCOPUS:78650291361
VL - 115
JO - Journal of Geophysical Research
JF - Journal of Geophysical Research
SN - 0148-0227
IS - 4
M1 - G00H05
ER -