Development of a winter wheat model in the Community Land Model
Yaqiong Lu1,2, Ian N. Williams1, Justin E. Bagley1, Margaret S. Torn1, and Lara M. Kueppers11Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory 2Climate and Global Dynamics Laboratory, National Center for Atmospheric Research
Received: 19 Sep 2016 – Accepted for review: 11 Oct 2016 – Discussion started: 12 Oct 2016
Abstract. Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of earth's croplands. As such, it plays an important role in carbon cycling and land-atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under changing climate, but also for understanding the energy and water cycles for winter wheat dominated regions. We developed a new winter wheat model in the Community Land Model (CLM) to better simulate wheat growth and grain production. These included schemes to represent vernalization, as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the U.S. Southern Great Plains ARM site (US-ARM), and validated the model performance at three additional sites across the continental US. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, latent heat flux, and net ecosystem exchange during the spring growing season. The model accurately simulated the interannual variation in yield at the US-ARM site, but underestimated yield at sites and in regions (Northwestern and Southeastern US) with historically greater yields.
Lu, Y., Williams, I. N., Bagley, J. E., Torn, M. S., and Kueppers, L. M.: Development of a winter wheat model in the Community Land Model
(version 4.5), Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-245, in review, 2016.