Publication Abstracts
Franke et al. 2020
Franke, J., C. Müller, J. Elliott, , , J. Balkovic, P. Ciais, M. Dury, P. Falloon, C. Folberth, L. François, T. Hank, M. Hoffmann, C. Izaurralde, I. Jacquemin, C. Jones, N. Khabarov, M. Koch, M. Li, W. Liu, S. Olin, , T.A.M. Pugh, A. Reddy, X. Wang, K. Williams, F. Zabel, and E. Moyer, 2020: The GGCMI Phase II experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0). Geosci. Model Dev., 13, no. 5, 2315-2336, doi:10.5194/gmd-13-2315-2020.
Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen ("CTWN") for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.
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BibTeX Citation
@article{fr04300i,
author={Franke, J. and Müller, C. and Elliott, J. and Ruane, A. and Jägermeyr, J. and Balkovic, J. and Ciais, P. and Dury, M. and Falloon, P. and Folberth, C. and François, L. and Hank, T. and Hoffmann, M. and Izaurralde, C. and Jacquemin, I. and Jones, C. and Khabarov, N. and Koch, M. and Li, M. and Liu, W. and Olin, S. and Phillips, M. and Pugh, T. A. M. and Reddy, A. and Wang, X. and Williams, K. and Zabel, F. and Moyer, E.},
title={The GGCMI Phase II experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)},
year={2020},
journal={Geosci. Model Dev.},
volume={13},
number={5},
pages={2315--2336},
doi={10.5194/gmd-13-2315-2020},
}
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RIS Citation
TY - JOUR ID - fr04300i AU - Franke, J. AU - Müller, C. AU - Elliott, J. AU - Ruane, A. AU - Jägermeyr, J. AU - Balkovic, J. AU - Ciais, P. AU - Dury, M. AU - Falloon, P. AU - Folberth, C. AU - François, L. AU - Hank, T. AU - Hoffmann, M. AU - Izaurralde, C. AU - Jacquemin, I. AU - Jones, C. AU - Khabarov, N. AU - Koch, M. AU - Li, M. AU - Liu, W. AU - Olin, S. AU - Phillips, M. AU - Pugh, T. A. M. AU - Reddy, A. AU - Wang, X. AU - Williams, K. AU - Zabel, F. AU - Moyer, E. PY - 2020 TI - The GGCMI Phase II experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0) JA - Geosci. Model Dev. VL - 13 IS - 5 SP - 2315 EP - 2336 DO - 10.5194/gmd-13-2315-2020 ER -
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