Natural Resources, School of

 

Erandathie Lokupitiya, University of ColomboFollow
A. S. Denning, Colorado State University
K. Schaefer, University of Colorado
D. Ricciuto, Oak Ridge National Laboratory
R. Anderson, University of Montana
M. A. Arain, McMaster University
Colorado State University, Colorado State University
A. G. Barr, Environment Canada, National Hydrology Research Centre
G. Chen, Auburn University
J. M. Chen, University of Toronto
P. Ciais, Laboratoire des Sciences du Climat et de l’Environnement
D. R. Cook, Argonne National Laboratory
M. Dietze, Boston University
M. El Maayar, Energy, Environment and Water Research Center, The Cyprus Institute, Nicosia, Cyprus
M. Fischer, Berkeley National LaboratoryFollow
University of Alberta, University of Alberta
D. Hollinger, USDA Forest Service, Durham, NH
C. Izaurralde, Pacific Northwest National Laboratory and University of Maryland
A. Jain, University of Illinois
C. Kucharik, University of Wisconsin - Madison
Z. Li, Teleobservation Research LLC, Columbia, MD
S. Liu, USGS, Sioux Falls, SD
L. Li, University of Technology Sydney
R. Matamala, Argonne National Laboratory
P. Peylin, Laboratoire des Sciences du Climat et de l’Environnement
D. Price, Natural Resources Canada, Northern Forestry Centre, Edmonton, AB
S. W. Running, University of Montana
A. Sahoo, Princeton University,
M. Sprintsin, Jewish National Fund-Keren Kayemet LeIsrael, Jerusalem
Andrew Suyker, University of Nebraska - LincolnFollow
H. Tian, Auburn University
C. Tonitto, Cornell University
M. Torn, Berkeley National Laboratory
Hans Verbeeck, Ghent University
Shashi Verma, University of Nebraska - LincolnFollow
Y. Xue, University of California, Los Angeles

Document Type

Article

Date of this Version

6-2016

Citation

Biogeochemistry (2016) 129:53–76

DOI 10.1007/s10533-016-0219-3

Comments

U.S. government work

Abstract

Croplands are highly productive ecosystems that contribute to land–atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fed sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO2 seasonal uptake over agricultural regions.

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