Characterizing the performance of ecosystem models across time scales: A spectral analysis of the North American Carbon Program site-level synthesis - Dietze, Michael C.; Vargas, Rodrigo; Richardson, Andrew D.; Stoy, Paul C.; Barr, Alan G.; Anderson, Ryan S.; Arain, M. Altaf; Baker, Ian T.; Black, T. Andrew; Chen, Jing M.; Ciais, Philippe; Flanagan, Lawrence B.; Gough, Christopher M.; Grant, Robert F.; Hollinger, David; Izaurralde, R. Cesar; Kucharik, Christopher J.; Lafleur, Peter; Liu, Shugang; Lokupitiya, E.Y.K.; Luo, Yiqi; Munger, J. William; Peng, Changhui; Poulter, Benjamin; Price, David T.; Ricciuto, Daniel M.; Riley, William J.; Sahoo, Alok Kumar; Schaefer, Kevin; Suyker, Andrew E.; Tian, Hanqin; Tonitto, Christina; Verbeeck, Hans; Verma, Shashi B.; Wang, Weifeng; Weng, Ensheng (Scientific Journal (JRNL), 2011)
diagnosing and forecasting carbon cycle dynamics across space and time. These models also play a critical role in understanding the potential responses of ecosystems to global change [VEMAP Members, 1995]. There are a large number of ecosystem models currently in use, but each makes different assumptions and was developed using different study sites and data sets. Observational and experimental data sets that provide detailed information about carbon cycle dynamics are increasingly available for almost every biome [Baldocchi, 2008] and represent an important source of data to test for ecosystem models. Despite numerous efforts to test multiple models at single sites [e.g., Hanson et al., 2004] or single models at multiple sites [e.g., Krinner et al., 2005; Poulter et al., 2009], there has not been a major synthesis effort to evaluate the performance of the community of ecosystem models at multiple sites using a standardized protocol.