Concerns about food security under climate change have motivated eorts to better understand the
future changes in yields by using detailed process-based models in agronomic sciences. Results of these models are often used
to inform subsequent model-based analyses in agricultural economics and integrated assessment. Fundamental feedbacks between
economic decision making and crop performance (e.g. management for intensification) is often ignored, as better integration of
the dierent model types is hampered by the computational requirements of detailed deterministic process-based crop models and
optimization-based economic modeling frameworks. Conducting a large simulation set with perturbations in atmospheric CO2 concentrations,
temperature, precipitation, and nitrogen inputs, Phase II of the Global Gridded Crop Model Intercomparison (GGCMI),
an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), constitutes an unprecedentedly data-rich
basis of projected yield changes across 12 models and five crops (maize, soy, rice, spring wheat, and winter wheat) using global
gridded simulations. Results from Phase II of the GGCMI eort, a targeted experiment aimed at understanding the interaction
between multiple climate variables (as well as management) are presented first. Then the construction of an emulator or statistical
representation of the simulated 30-year mean climatological output in each location is outlined. The emulated response surfaces
capture the details of the process-based models in a lightweight, computationally tractable form that facilitates model comparison as
well as application in subsequent modeling eorts such as integrated assessment. Results show considerable spatial heterogeneity
in sensitivity to input variables, confirming the need for a global study, as well as dierences across models. It is clear however that
models robustly produce yield responses that are nonlinear and sensitive to interactions across the input variables. Results illustrate
the utility of model emulation for climate impacts studies.
Published: March 11, 2021
Citation
Franke J., C. Muller, J. Elliott, A. Ruane, J. Jagermeyr, A.C. Snyder, and M. Dury, et al. 2020.The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0).Geoscientific Model Development 13, no. 9:3995-4018.PNNL-SA-139208.doi:10.5194/gmd-13-3995-2020