Published May 18, 2020 | Version v1
Journal article Open

The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)

  • 1. University of Chicago
  • 2. Potsdam Institute for Climate Impact Research
  • 3. NASA Goddard Institute for Space Studies
  • 4. Comenius University in Bratislava
  • 5. Peking University
  • 6. University of Liège
  • 7. Met Office Hadley Centre
  • 8. International Institute for Applied Systems Analysis
  • 9. Ludwig-Maximilians-Universität München
  • 10. Georg-August-University Göttingen
  • 11. University of Maryland
  • 12. Swiss Federal Institute of Aquatic Science and Technology

Description

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.

Notes

Due to the large number of authors, only the first 20 and the University of Chicago authors are included on the above author list. Please download the article for the complete list of authors.

Data availability

All input data are available via zenodo at https://doi.org/10.5281/zenodo.3773827 (Müller et al., 2020). For the minimum cropland mask, choose the boolean_cropmask_ggcmi_phase2.nc4 file. Growing period data for wheat are now divided up into winter and spring wheat, whereas all other growing season data (maize, rice, soybean) are the same as in Phase 1

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Additional details

Identifiers

DOI
10.5194/gmd-13-2315-2020
Other
oai:uchicago.tind.io:14155

Funding

University of Chicago

UChicago Information

Division(s)
Physical Sciences Division
Department(s)
Computer Science, Geophysical Sciences, Statistics
Center(s) or Institute(s)
Center for Robust Decision Making on Climate and Energy Policy