Articles | Volume 9, issue 2
https://doi.org/10.5194/esd-9-479-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-9-479-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 May 2018
Research article |
| 09 May 2018
| 09 May 2018
Changes in crop yields and their variability at different levels of global warming
Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
Geography Department, Humboldt-Universität zu Berlin, Berlin, Germany
Jacob Schewe
Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
Katelin Childers
Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
Katja Frieler
Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
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Cited
29 citations as recorded by crossref.
- Projecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales S. Lange et al. 10.1029/2020EF001616
- Extreme Events and Production Shocks for Key Crops in Southern Africa Under Climate Change T. Thomas et al. 10.3389/fclim.2022.787582
- Climate change adaptation and resilience among vegetable farmers K. Arimi 10.1080/19315260.2020.1861160
- Future climate change significantly alters interannual wheat yield variability over half of harvested areas W. Liu et al. 10.1088/1748-9326/ac1fbb
- Global and regional impacts of climate change at different levels of global temperature increase N. Arnell et al. 10.1007/s10584-019-02464-z
- Surveying perceptions and practices of high-end climate change R. Taylor et al. 10.1007/s10584-020-02659-9
- Construction of indicator system of regional economic system impact factors based on fractional differential equations J. Zhang et al. 10.1016/j.chaos.2019.07.036
- The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO<sub>2</sub>, temperature, water, and nitrogen (version 1.0) J. Franke et al. 10.5194/gmd-13-3995-2020
- A crop yield change emulator for use in GCAM and similar models: Persephone v1.0 A. Snyder et al. 10.5194/gmd-12-1319-2019
- Economic impacts of climate-induced crop yield changes: evidence from agri-food industries in six countries D. Wang et al. 10.1007/s10584-021-03062-8
- Climate change impacts on flood peaks in Britain for a range of global mean surface temperature changes A. Rudd et al. 10.1111/jfr3.12863
- Decomposing crop model uncertainty: A systematic review R. Chapagain et al. 10.1016/j.fcr.2022.108448
- Global food self-sufficiency in the 21st century under sustainable intensification of agriculture A. Beltran-Peña et al. 10.1088/1748-9326/ab9388
- Climate change impacts on crop yields E. Rezaei et al. 10.1038/s43017-023-00491-0
- Parameterization-induced uncertainties and impacts of crop management harmonization in a global gridded crop model ensemble C. Folberth et al. 10.1371/journal.pone.0221862
- An empirical, Bayesian approach to modelling crop yield: Maize in USA R. Shirley et al. 10.1088/2515-7620/ab67f0
- Floral Scents in Bee-Pollinated Buckwheat and Oilseed Rape under a Global Warming Scenario G. Cordeiro & S. Dötterl 10.3390/insects14030242
- Improvement of the CERES-Rice model using controlled experiments and a Meta-analysis Q. Sun et al. 10.1007/s00704-020-03256-7
- Statistical emulators of irrigated crop yields and irrigation water requirements É. Blanc 10.1016/j.agrformet.2019.107828
- A rolling horizon simulation approach for managing demand with lead time variability F. Campuzano-Bolarín et al. 10.1080/00207543.2019.1634849
- A Delphi assessment of climate change risks in southern Africa in the 21st century R. Scholes et al. 10.1016/j.crm.2023.100566
- Plant pathogen infection risk tracks global crop yields under climate change T. Chaloner et al. 10.1038/s41558-021-01104-8
- Extending a first-principles primary production model to predict wheat yields S. Qiao et al. 10.1016/j.agrformet.2020.107932
- Pest management facing warming and chemical stresses: Multi-stress effects on the biological agent Trichogramma oleae W. Nusillard et al. 10.1016/j.scitotenv.2024.174709
- The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations W. Liu et al. 10.5194/gmd-16-7203-2023
- Comparative changes in sugars and lipids show evidence of a critical node for regeneration in safflower seeds during aging L. Zhou et al. 10.3389/fpls.2022.1020478
- On the evolution of plant thermomorphogenesis W. Ludwig et al. 10.1093/jxb/erab310
- Understanding nexuses between precipitation changes and climate change and variability in semi-arid lowlands of Mwanga District, Tanzania F. Bagambilana & W. Rugumamu 10.5897/AJEST2018.2586
- Temperature-related excess mortality in German cities at 2 °C and higher degrees of global warming V. Huber et al. 10.1016/j.envres.2020.109447
29 citations as recorded by crossref.
- Projecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales S. Lange et al. 10.1029/2020EF001616
- Extreme Events and Production Shocks for Key Crops in Southern Africa Under Climate Change T. Thomas et al. 10.3389/fclim.2022.787582
- Climate change adaptation and resilience among vegetable farmers K. Arimi 10.1080/19315260.2020.1861160
- Future climate change significantly alters interannual wheat yield variability over half of harvested areas W. Liu et al. 10.1088/1748-9326/ac1fbb
- Global and regional impacts of climate change at different levels of global temperature increase N. Arnell et al. 10.1007/s10584-019-02464-z
- Surveying perceptions and practices of high-end climate change R. Taylor et al. 10.1007/s10584-020-02659-9
- Construction of indicator system of regional economic system impact factors based on fractional differential equations J. Zhang et al. 10.1016/j.chaos.2019.07.036
- The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO<sub>2</sub>, temperature, water, and nitrogen (version 1.0) J. Franke et al. 10.5194/gmd-13-3995-2020
- A crop yield change emulator for use in GCAM and similar models: Persephone v1.0 A. Snyder et al. 10.5194/gmd-12-1319-2019
- Economic impacts of climate-induced crop yield changes: evidence from agri-food industries in six countries D. Wang et al. 10.1007/s10584-021-03062-8
- Climate change impacts on flood peaks in Britain for a range of global mean surface temperature changes A. Rudd et al. 10.1111/jfr3.12863
- Decomposing crop model uncertainty: A systematic review R. Chapagain et al. 10.1016/j.fcr.2022.108448
- Global food self-sufficiency in the 21st century under sustainable intensification of agriculture A. Beltran-Peña et al. 10.1088/1748-9326/ab9388
- Climate change impacts on crop yields E. Rezaei et al. 10.1038/s43017-023-00491-0
- Parameterization-induced uncertainties and impacts of crop management harmonization in a global gridded crop model ensemble C. Folberth et al. 10.1371/journal.pone.0221862
- An empirical, Bayesian approach to modelling crop yield: Maize in USA R. Shirley et al. 10.1088/2515-7620/ab67f0
- Floral Scents in Bee-Pollinated Buckwheat and Oilseed Rape under a Global Warming Scenario G. Cordeiro & S. Dötterl 10.3390/insects14030242
- Improvement of the CERES-Rice model using controlled experiments and a Meta-analysis Q. Sun et al. 10.1007/s00704-020-03256-7
- Statistical emulators of irrigated crop yields and irrigation water requirements É. Blanc 10.1016/j.agrformet.2019.107828
- A rolling horizon simulation approach for managing demand with lead time variability F. Campuzano-Bolarín et al. 10.1080/00207543.2019.1634849
- A Delphi assessment of climate change risks in southern Africa in the 21st century R. Scholes et al. 10.1016/j.crm.2023.100566
- Plant pathogen infection risk tracks global crop yields under climate change T. Chaloner et al. 10.1038/s41558-021-01104-8
- Extending a first-principles primary production model to predict wheat yields S. Qiao et al. 10.1016/j.agrformet.2020.107932
- Pest management facing warming and chemical stresses: Multi-stress effects on the biological agent Trichogramma oleae W. Nusillard et al. 10.1016/j.scitotenv.2024.174709
- The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations W. Liu et al. 10.5194/gmd-16-7203-2023
- Comparative changes in sugars and lipids show evidence of a critical node for regeneration in safflower seeds during aging L. Zhou et al. 10.3389/fpls.2022.1020478
- On the evolution of plant thermomorphogenesis W. Ludwig et al. 10.1093/jxb/erab310
- Understanding nexuses between precipitation changes and climate change and variability in semi-arid lowlands of Mwanga District, Tanzania F. Bagambilana & W. Rugumamu 10.5897/AJEST2018.2586
- Temperature-related excess mortality in German cities at 2 °C and higher degrees of global warming V. Huber et al. 10.1016/j.envres.2020.109447
Latest update: 26 Jul 2024
Short summary
It has been shown that regional temperature and precipitation changes in future climate change scenarios often scale quasi-linearly with global mean temperature change (∆GMT). We show that an important consequence of these physical climate changes, namely changes in agricultural crop yields, can also be described in terms of ∆GMT to a large extent. This makes it possible to efficiently estimate future crop yield changes for different climate change scenarios without need for complex models.
It has been shown that regional temperature and precipitation changes in future climate change...
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