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Volume 6, issue 6
Biogeosciences, 6, 969–986, 2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
Biogeosciences, 6, 969–986, 2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

  12 Jun 2009

12 Jun 2009

Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands

E. Lokupitiya1, S. Denning1, K. Paustian2,3, I. Baker1, K. Schaefer4, S. Verma5, T. Meyers6, C. J. Bernacchi7, A. Suyker5, and M. Fischer8 E. Lokupitiya et al.
  • 1Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA
  • 2Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523, USA
  • 3Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USA
  • 4National Snow and Ice Data Center, University of Colorado, Boulder, CO 80309, USA
  • 5School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68583-0978, USA
  • 6NOAA/ARL/ATDD, Oak Ridge, TN 37830-2456, USA
  • 7Department of Plant Biology, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
  • 8Lawrence Berkeley National Laboratory, Environmental Energy Technologies Division, Atmospheric Science Department, Berkeley, CA 94720, USA

Abstract. Croplands are man-made ecosystems that have high net primary productivity during the growing season of crops, thus impacting carbon and other exchanges with the atmosphere. These exchanges play a major role in nutrient cycling and climate change related issues. An accurate representation of crop phenology and physiology is important in land-atmosphere carbon models being used to predict these exchanges. To better estimate time-varying exchanges of carbon, water, and energy of croplands using the Simple Biosphere (SiB) model, we developed crop-specific phenology models and coupled them to SiB. The coupled SiB-phenology model (SiBcrop) replaces remotely-sensed NDVI information, on which SiB originally relied for deriving Leaf Area Index (LAI) and the fraction of Photosynthetically Active Radiation (fPAR) for estimating carbon dynamics. The use of the new phenology scheme within SiB substantially improved the prediction of LAI and carbon fluxes for maize, soybean, and wheat crops, as compared with the observed data at several AmeriFlux eddy covariance flux tower sites in the US mid continent region. SiBcrop better predicted the onset and end of the growing season, harvest, interannual variability associated with crop rotation, day time carbon uptake (especially for maize) and day to day variability in carbon exchange. Biomass predicted by SiBcrop had good agreement with the observed biomass at field sites. In the future, we will predict fine resolution regional scale carbon and other exchanges by coupling SiBcrop with RAMS (the Regional Atmospheric Modeling System).

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