AgMIP Crop Model Projections Featured in IPCC Synthesis Report Summary for Policymakers
By Natalie Kozlowski
22 March, 2023
A major Agricultural Model Intercomparison and Improvement Project (AgMIP) study led by Dr. Jonas Jägermeyr in collaboration with the AgMIP Global Gridded Crop Model Intercomparison (GGCMI) and the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) was featured in the Synthesis Report (SYR) released this week as the final part of the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). The IPCC is the world’s leading body assessing scientific information as a basis for international climate negotiations and the implementation of climate actions, with its findings approved by 195 countries. Its Synthesis Report represents the culmination of 6 reports (assessing 100,000+ studies) into a single ~10 page summary with 7 figures. The AgMIP maize yield maps shown in SYR Figure SPM.3, along with similar maps on ecosystem, human health, and fisheries impacts, were also included in the IPCC WGII Technical Annex I. The original study is here.
The AgMIP GGMCI organized a protocol-based, stakeholder-informed crop model ensemble to provide a synthesis-ready result presented with indications of regional model agreement. The AgMIP community is made up of more than 1,200 members and includes participation by the world’s leading crop modeling centers.
“AgMIP crop yield projections being highlighted in the IPCC AR6 Synthesis Report is a significant achievement. Through its multi-model assessments, AgMIP produces the projections of record for climate change and food. AgMIP works with a broad network of researchers to improve climate impacts science so that we can better understand how climate change will affect food security around the world,” says Dr. Cynthia Rosenzweig, co-founder of AgMIP and 2022 World Food Prize Laureate.
Dr. Jonas Jägermeyr
How Will Climate Change Impact Global Agriculture?
The maps in the IPCC’s AR6 SYR originating from Jägermeyr et al. project a general pattern of maize yield decrease in the lower to mid-latitudes with some regional deviations, and increased maize yield in high latitude regions indicated by some models. Other crops, including wheat, can benefit from increased atmospheric CO2 concentration far more than maize, leading to potential productivity increases under moderate warming, particularly in the high latitudes. In some parts of the world there is substantial model disagreement in the sign of yield change (represented as hatching in the figure), which point us to areas where improvements are needed in data and models.
Figure SPM.3 c1 shows changes in maize yield by 2080-2099 relative to 1986-2005 at three projected global warming levels (GWLs): 1.6-2.4°C (2.0°C), 3.3-4.8°C (4.1°C), and 3.9-6.0°C (4.9°C). The maps depict changes on current maize-growing regions (in areas of over 10 hectares), with the corresponding range of GWLs under socio-economic development pathways SSP1-2.6, SSP3-7.0 and SSP5-8.5, respectively. The hatched regions indicate areas where there is substantial disagreement in climate-crop models on the degree of yield change.
Climate change can lead to both gains and losses in global agriculture, and disproportionate adverse impacts in the Global South are a reason for concern. The new crop model simulations based on the latest CMIP6 climate projections highlight that the response of global agriculture to climate change is more pronounced than previously anticipated. The emergence of the climate signal in global agriculture – the time when extraordinary years become the norm – will occur within the next 10 to 15 years in many breadbasket regions. Additional assessment of climate impacts on food security using crop model projections and other methods were provided in the underlying IPCC WGII Chapter 5.
Mitigation and Adaptation are of the Essence
The crop maps show median maize yield change projections for three different future time slices spanning GWLs. The projections are based on an ensemble of 60 climate-crop model simulations composed of 12 global gridded crop models (GGCMs), each driven by bias-adjusted outputs from 5 CMIP6 climate models. The study’s results purposefully isolate the impact of climate change on maize yields and do not take additional adaptation efforts into consideration.
“In this study we exclude farm-level adaptation to understand the isolated climatic responses in global agriculture. Through this, we hope to emphasize the importance of current and future preventative mitigation actions and proactive adaptation planning. Farmers are already adapting to the changing climate to a certain extent and by alerting them to future changes we can potentially help prepare better solutions,” says Dr. Jägermeyr, lead author for the original study.
This figure taken from the original Jägermeyr et al. publication shows the productivity time series for maize (a) and wheat (b) shown as relative changes to the 1983-2013 reference period under SSP1-2.6 (green) and SSP5-8.5 (yellow). The shaded green and yellow areas represent a larger range of outcomes for all climate-crop model combinations. The horizontal solid line shows the median response and the horizontal dashed lines mark the standard deviation of historical yield variability and model uncertainty. In sum, the figure shows that the global productivity of maize decreases under projected future climate scenarios, while global wheat productivity is projected to increase in some regions.
Climate change affects simulations of maize yield in various ways, including changed precipitation patterns, CO2 concentrations, extreme heat and drought events, and importantly, accelerated crop maturity. A shorter period of time between seed and maturation means reductions in the growing season length and thus shorter grain-filling periods, which leads to lower yields.
These simulations evaluate the effects of temperature, precipitation, and CO2, among other factors, on plant growth, but do not include constraints that water resource availability places on irrigation, pests, diseases, or ozone, which can lead to an even greater reduction in crop yields. Further AgMIP research is being conducted to simulate additional climate pressures on more cropping systems, livestock, and pastures, as well as understanding the impact that climate change has across complex food systems, including biophysical and socioeconomic considerations such as nutrition and supply chains. Dr. Jägermeyr notes that decisions within the agricultural sector will be shaped by changing prices, land use, and consumer demand.
Looking to the Future of Crop Impact Modeling
Crop models, and impact models in general, still pose a large amount of uncertainty, particularly under high-emission scenarios projected farther into the future.
Dr. Jägermeyr states, “In view of the next IPCC Assessment cycle soon to begin, reducing impact uncertainty needs to be targeted deliberately through funding for the next-generation of crop model development and intercomparison.”
In ongoing projects, GGCMI develops new input data sets that help improve the simulation of representative agroecosystems around the world. These include, for example, an annual crop calendar based on observational data, or information on where and when crops are planted and harvested. Current model improvement activities are focused on the representation of future ozone stress in global agriculture and the improvement of responses to waterlogging and flooding, which are still blind spots in process-based crop modeling. However, such data and model development efforts are currently being done across individual and fragmented projects. AgMIP is building the international and cross-institutional coordination – similar to organization of the climate modeling community – that is required to reduce impact model uncertainty significantly for the next IPCC Assessment and beyond.
If you’re interested in Dr. Jägermeyr’s results with AgMIP’s GGCMI or learning more about any of AgMIP’s other teams, please go to AgMIP.org. You can also join the AgMIP community in New York (in-person or virtually) this June for AgMIP’s 9th Global Workshop (AgMIP9) where you can learn how to participate in some of its 50+ activities, including future modeling and assessment efforts.
Additional Resources:
The IPCC Synthesis Report: https://www.ipcc.ch/report/ar6/syr/
The crop projection maps in Figure SPM.3 row c1: https://www.ipcc.ch/report/ar6/syr/figures/summary-for-policymakers/figure-spm-3/
Jägermeyr et al.’s original publication in Nature Food: https://www.nature.com/articles/s43016-021-00400-y
Contact info:
Dr. Jonas Jägermeyr – jonas.jaegermeyr@columbia.edu
Dr. Cynthia Rosenzweig – crr2@columbia.edu
Dr. Alex Ruane – alexander.c.ruane@nasa.gov
Natalie Kozlowski – n.kozlowski@columbia.edu