Publication Abstracts
Franke et al. 2020
Franke, J., C. Müller, J. Elliott, , , A. Snyder, M. Dury, P. Falloon, C. Folberth, L. François, T. Hank, R.C. Izaurralde, I. Jacquemin, C. Jones, M. Li, W. Liu, S. Olin, M. Phillips, T.A.M. Pugh, A. Reddy, K. Williams, Z. Wang, F. Zabel, and E. Moyer, 2020: The GGCMI phase II emulators: Global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0). Geosci. Model Dev., 13, no. 9, 3995-4018, doi:10.5194/gmd-13-3995-2020.
Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: that growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts.
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BibTeX Citation
@article{fr08300m,
author={Franke, J. and Müller, C. and Elliott, J. and Ruane, A. C. and Jägermeyr, J. and Snyder, A. and Dury, M. and Falloon, P. and Folberth, C. and François, L. and Hank, T. and Izaurralde, R. C. and Jacquemin, I. and Jones, C. and Li, M. and Liu, W. and Olin, S. and Phillips, M. and Pugh, T. A. M. and Reddy, A. and Williams, K. and Wang, Z. and Zabel, F. and Moyer, E.},
title={The GGCMI phase II emulators: Global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0)},
year={2020},
journal={Geosci. Model Dev.},
volume={13},
number={9},
pages={3995--4018},
doi={10.5194/gmd-13-3995-2020},
}
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RIS Citation
TY - JOUR ID - fr08300m AU - Franke, J. AU - Müller, C. AU - Elliott, J. AU - Ruane, A. C. AU - Jägermeyr, J. AU - Snyder, A. AU - Dury, M. AU - Falloon, P. AU - Folberth, C. AU - François, L. AU - Hank, T. AU - Izaurralde, R. C. AU - Jacquemin, I. AU - Jones, C. AU - Li, M. AU - Liu, W. AU - Olin, S. AU - Phillips, M. AU - Pugh, T. A. M. AU - Reddy, A. AU - Williams, K. AU - Wang, Z. AU - Zabel, F. AU - Moyer, E. PY - 2020 TI - The GGCMI phase II emulators: Global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0) JA - Geosci. Model Dev. VL - 13 IS - 9 SP - 3995 EP - 4018 DO - 10.5194/gmd-13-3995-2020 ER -
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