AgMIP-Wheat - Advances in Wheat Modeling.

AgMIP-Wheat Team: S. Asseng, P. Martre, A. Maiorano, R.P. Rötter, G.J. O’Leary, G.J. Fitzgerald, C. Girousse, R. Motzo, F. Giunta, M.A. Babar, M.P. Reynolds, A.M.S. Kheir, P.J. Thorburn, K. Waha, A.C. Ruane, P.K. Aggarwal, M. Ahmed, J. Balkovič, B. Basso, C. Biernath, M. Bindi, D. Cammarano, A.J. Challinor, G. De Sanctis, B. Dumont, E. Eyshi Rezaei, E. Fereres, R. Ferrise, M. Garcia-Vila, S. Gayler, Y. Gao, H. Horan, G. Hoogenboom, R.C. Izaurralde, M. Jabloun, C.D. Jones, B.T. Kassie, K.C. Kersebaum, C. Klein, A.K. Koehler, B. Liu, S. Minoli, M. Montesino San Martin, C. Müller, S. Naresh Kumar, C. Nendel, J.E. Olesen, T. Palosuo, J.R. Porter, E. Priesack, D. Ripoche, M.A. Semenov, C. Stöckle, P. Stratonovitch, T. Streck, I. Supit, F. Tao, M. Van der Velde, D. Wallach, E. Wang, H. Webber, J. Wolf, L. Xiao, Z. Zhang, Z. Zhao, Y. Zhu and F. Ewert

 

--- Abstract: Thirty-two wheat models currently participate in the Agricultural Model Intercomparison and Improvement Project for Wheat project (AgMIP-Wheat). Model approaches vary from simple to complex, however, there is no indication that more model complexity always results in better simulation outcomes. However, if a key process is missing, adding for example a heat stress impact routine to simulate increasing temperature impacts can improve the precision of simulations when compared with field experiments. Using crop models in multi-model ensembles can also improve simulated precision by canceling out each other models noise. Applying multi-model ensembles across representative location and upscaling impacts via reported production data allow climate impact assessments across regions and the globe. Observation-driven adaptation options for crop breeding can then be translated to adaptation impacts at various scales.