Physical Sciences Division
Published March 11, 2024 | Version v1
Journal article Open

Substantial Differences in Crop Yield Sensitivities Between Models Call for Functionality-Based Model Evaluation

Creators

  • 1. Potsdam Institute for Climate Impact Research
  • 2. University of Chicago
  • 3. NASA Goddard Institute for Space Studies
  • 4. International Institute for Applied Systems Analysis
  • 5. Laboratoire des Sciences du Climat et de l'Environnement
  • 6. University of Liège
  • 7. Met Office Hadley Centre
  • 8. Ludwig‐Maximilians‐Universität
  • 9. Georg‐August‐University Goettingen
  • 10. University of Maryland
  • 11. International Institutefor Applied Systems Analysis
  • 12. China Agricultural University
  • 13. Lund University
  • 14. Peking University
  • 15. Federation of American Scientists

Description

Crop models are often used to project future crop yield under climate and global change and typically show a broad range of outcomes. To understand differences in modeled responses, we analyzed modeled crop yield response types using impact response surfaces along four drivers of crop yield: carbon dioxide (C), temperature (T), water (W), and nitrogen (N). Crop yield response types help to understand differences in simulated responses per driver and their combinations rather than aggregated changes in yields as the result of simultaneous changes in various drivers. We find that models' sensitivities to the individual drivers are substantially different and often more different across models than across regions. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response types across models and their configurations suggests that models need to undergo further scrutiny. We suggest establishing standards in model evaluation based on emergent functionality not only against historical yield observations but also against dedicated experiments across different drivers to analyze emergent functional patterns of crop models.

Data availability

The simulation outputs of GGCMI Phase 2 output variables that we analyze here (Balkovic et al., 2019a, 2019b, 2019c, 2019d, 2019e; Dury et al., 2019a, 2019b, 2019c, 2019d, 2019e; Elliott, 2019a, 2019b, 2019c, 2019d, 2019e; Falloon & Williams, 2019a, 2019b, 2019c, 2019d; Folberth, 2019a, 2019b, 2019c, 2019d, 2019e; Hoffmann & Koch, 2019a, 2019b, 2019c, 2019d, 2019e; W. Liu, 2019a, 2019b, 2019c, 2019d, 2019e; Müller, 2019a, 2019b, 2019c, 2019d, 2019e; Pugh et al., 2019a, 2019b, 2019c; Reddy et al., 2019a, 2019b, 2019c, 2019d, 2019e; X. Wang & Ciais, 2019a, 2019b, 2019c; Zabel et al., 2019a, 2019b, 2019c, 2019d, 2019e) are available on zenodo.org. See Table A2 for data DOIs. Due to data size, the archive had to be split in several archives. All scripts used for processing the data in this analysis are available at zenodo.org (Müller, 2024).

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Additional details

Identifiers

DOI
10.1029/2023EF003773
Other
oai:uchicago.tind.io:14052

Funding

National Science Board
DGE-1735359
National Science Board
DGE-1746045
GISS Climate Impacts Group
LUCCI
National Natural Science Foundation of China
32361143871
National Natural Science Foundation of China
42171096

UChicago Information

Division(s)
Physical Sciences Division
Department(s)
Geophysical Sciences