@article{23050, keywords = {Carbon exchange, Carbon modeling, Drought, Ecosystem models, Model validation, North American Carbon Program}, author = {Christopher R Schwalm and Christopher A Williams and Kevin Schaefer and Ryan Anderson and M. M Altaf Arain and Ian Baker and Alan Barr and T. T Andrew Black and Guangsheng Chen and Jing Ming Chen and Philippe Ciais and Kenneth J Davis and Ankur R Desai and Michael Dietze and Danilo Dragoni and Marc L Fischer and Lawrence B Flanagan and Robert Grant and Lianhong Gu and David Y Hollinger and R. R César Izaurralde and Chris Kucharik and Peter Lafleur and Beverly E Law and Longhui Li and Zhengpeng Li and Shuguang Liu and Erandathie Lokupitiya and Yiqi Luo and Siyan Ma and Hank Margolis and Roser Matamala and Harry McCaughey and Russell K Monson and Walter C Oechel and Changhui Peng and Benjamin Poulter and David T Price and Dan M Riciutto and William J Riley and Alok Kumar Sahoo and Michael Sprintsin and Jianfeng Sun and Hanqin Tian and Christina Tonitto and Hans Verbeeck and Shashi B Verma}, title = {A model-data intercomparison of CO2 exchange across North America: Results from the North American Carbon Program site synthesis}, 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 CO2 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.
}, year = {2010}, journal = {Journal of Geophysical Research: Biogeosciences}, volume = {115}, month = {09/2010}, doi = {10.1029/2009JG001229}, }