Optimal climate intervention scenarios for crop production vary by nation.
Journal
Nature food
ISSN: 2662-1355
Titre abrégé: Nat Food
Pays: England
ID NLM: 101761102
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
received:
01
10
2022
accepted:
07
09
2023
medline:
1
11
2023
pubmed:
6
10
2023
entrez:
5
10
2023
Statut:
ppublish
Résumé
Stratospheric aerosol intervention (SAI) is a proposed strategy to reduce the effects of anthropogenic climate change. There are many temperature targets that could be chosen for a SAI implementation, which would regionally modify climatically relevant variables such as surface temperature, precipitation, humidity, total solar radiation and diffuse radiation. In this work, we analyse impacts on national maize, rice, soybean and wheat production by looking at output from 11 different SAI scenarios carried out with a fully coupled Earth system model coupled to a crop model. Higher-latitude nations tend to produce the most calories under unabated climate change, while midlatitude nations maximize calories under moderate SAI implementation and equatorial nations produce the most calories from crops under high levels of SAI. Our results highlight the challenges in defining 'globally optimal' SAI strategies, even if such definitions are based on just one metric.
Identifiants
pubmed: 37798559
doi: 10.1038/s43016-023-00853-3
pii: 10.1038/s43016-023-00853-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
902-911Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer Nature Limited.
Références
Fugile, P. Climate change upsets agriculture. Nat. Clim. Change 11, 293–299 (2021).
Kummu, M., Heino, M., Taka, M., Varis, O. & Viviroli, D. Climate change risks pushing one-third of global food production outside the safe climatic space. One Earth 4, 720–729 (2021).
doi: 10.1016/j.oneear.2021.04.017
pubmed: 34056573
pmcid: 8158176
Rosenzweig, C. et al. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc. Natl Acad. Sci. USA 111, 3268–3273 (2014).
doi: 10.1073/pnas.1222463110
pubmed: 24344314
Crutzen, P. J. Albedo enhancement by stratospheric sulfur injections: a contribution to resolve a policy dilemma? Climatic Change 77, 211–220 (2006).
doi: 10.1007/s10584-006-9101-y
Wigley, T. M. A combined mitigation/geoengineering approach to climate stabilization. Science 314, 452–454 (2006).
doi: 10.1126/science.1131728
pubmed: 16973840
National Academies of Sciences, Engineering, and Medicine Reflecting Sunlight: Recommendations for Solar Geoengineering Research and Research Governance (National Academies Press, 2021); https://doi.org/10.17226/25762
Robock, A. 20 reasons why geoengineering may be a bad idea. Bull. At. Sci. 64, 14–18 (2008).
doi: 10.1080/00963402.2008.11461140
Rasch, P. J., Crutzen, P. J. & Coleman, D. B. Exploring the geoengineering of climate using stratospheric sulfate aerosols: the role of particle size. Geophys. Res. Lett. 35, L02809 (2008).
doi: 10.1029/2007GL032179
Jägermeyr, J. et al. Climate impacts on global agriculture emerge earlier in new generation of climate and crop models. Nat. Food 2, 873–885 (2021).
doi: 10.1038/s43016-021-00400-y
pubmed: 37117503
Farquhar, G., Caemmerer, S. & Berry, J. A biochemical model of photosynthetic CO
doi: 10.1007/BF00386231
pubmed: 24306196
Collatz, G. J., Ribas-Carbo, M. & Berry, J. A. Coupled photosynthesis–stomatal conductance model for leaves of C
doi: 10.1071/PP9920519
Bala, G., Duffy, P. B. & Taylor, K. E. Impact of geoengineering schemes on the global hydrological cycle. Proc. Natl Acad. Sci. USA 105, 7664–7669 (2008).
doi: 10.1073/pnas.0711648105
pubmed: 18505844
pmcid: 2409412
Proctor, J. et al. Estimating global agricultural effects of geoengineering using volcanic eruptions. Nature 560, 480–483 (2018).
doi: 10.1038/s41586-018-0417-3
pubmed: 30089909
Pongratz, J., Lobell, D. B., Cao, L. & Caldeira, K. Crop yields in a geoengineered climate. Nat. Clim. Change 2, 101–105 (2012).
doi: 10.1038/nclimate1373
Xia, L. et al. Solar radiation management impacts on agriculture in China: a case study in the Geoengineering Model Intercomparison Project (GeoMIP). J. Geophys. Res. Atmos. 119, 8695–8711 (2014).
doi: 10.1002/2013JD020630
Zhan, P. et al. Impacts of sulfate geoengineering on rice yield in China: results from a multimodel ensemble. Earth’s Future 7, 395–410 (2019).
doi: 10.1029/2018EF001094
Fan, Y. et al. Solar geoengineering can alleviate climate change pressures on crop yields. Nat. Food 2, 373–381 (2021).
doi: 10.1038/s43016-021-00278-w
pubmed: 37117731
Tilmes, S. et al. Reaching 1.5 and 2.0 °C global surface temperature targets using stratospheric aerosol geoengineering. Earth Syst. Dynam. 11, 579–601 (2020).
doi: 10.5194/esd-11-579-2020
Richter, J. et al. Assessing responses and impacts of solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI): protocol and initial results from the first simulations. Geosci. Model Dev. 15, 8221–8243 (2022).
doi: 10.5194/gmd-15-8221-2022
MacMartin, D. et al. Scenarios for modeling solar radiation modification. Proc. Natl Acad. Sci. USA 119, e2202230119 (2022).
doi: 10.1073/pnas.2202230119
pubmed: 35939702
pmcid: 9388149
Tilmes, S. et al. CESM1(WACCM) Stratospheric Aerosol Geoengineering Large Ensemble Project. Bull. Am. Meteorol. Soc. 99, 2361–2371 (2018).
doi: 10.1175/BAMS-D-17-0267.1
Dagon, K. & Schrag, D. P. Quantifying the effects of solar geoengineering on vegetation. Climatic Change 153, 235–251 (2019).
doi: 10.1007/s10584-019-02387-9
Kravitz, B. et al. The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): simulation design and preliminary results. Geosci. Model Dev. 8, 3379–3392 (2015).
doi: 10.5194/gmd-8-3379-2015
Danabasoglu, G. et al. The Community Earth System Model Version 2 (CESM2). J. Adv. Model. Earth Syst. 12, e2019MS001916 (2020).
doi: 10.1029/2019MS001916
Lombardozzi, D. L. et al. Simulating agriculture in the Community Land Model Version 5. J. Geophys. Res. Biogeosci. 125, e2019JG005529 (2020).
doi: 10.1029/2019JG005529
Lawrence, D. M. et al. The Community Land Model version 5: description of new features, benchmarking, and impact of forcing uncertainty. J. Adv. Model. Earth Syst. 11, 4245–4287 (2019).
doi: 10.1029/2018MS001583
Fisher, R. et al. Parametric controls on vegetation responses to biogeochemical forcing in the CLM5. J. Adv. Model. Earth Syst. 11, 2879–2895 (2019).
doi: 10.1029/2019MS001609
Dirmeyer, P. A. et al. GSWP-2: multimodel analysis and implications for our perception of the land surface. Bull. Am. Meteorol. Soc. 87, 1381–1398 (2006).
doi: 10.1175/BAMS-87-10-1381
Rabin, S. S., Sacks, W. J., Lombardozzi, D. L., Xia, L. & Robock, A. Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5). Preprint at Geoscientific Model Development https://doi.org/10.5194/gmd-2023-66 (2023).
Food Balance Spreadsheets (FAO, accessed 20 July 2022); https://www.fao.org/faostat/en/#data/FBS
Müller, C. et al. Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications. Geosci. Model Dev. 10, 1403–1422 (2017).
doi: 10.5194/gmd-10-1403-2017
Proctor, J. Atmospheric opacity has a nonlinear effect on global crop yields. Nat. Food 2, 166–173 (2021).
doi: 10.1038/s43016-021-00240-w
pubmed: 37117447
Reynolds, J. L. Solar geoengineering to reduce climate change: a review of governance proposals. Proc. R. Soc. A https://doi.org/10.1098/rspa.2019.0255 (2019).
Svoboda, T. & Irvine, P. Ethical and technical challenges in compensating for harm due to solar radiation management geoengineering. Ethics Policy Environ. 17, 157–174 (2014).
doi: 10.1080/21550085.2014.927962
Bunzl, M. Geoengineering harms and compensation. Stanf. J. Law Sci. Policy 4, 69–75 (2019).
Gettelman, A. et al. The Whole Atmosphere Community Climate Model version 6 (WACCM6). J. Geophys. Res. Atmos. 124, 12380–12403 (2019).
doi: 10.1029/2019JD030943
Liu, X. et al. Description and evaluation of a new four-mode version of the Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model. Geosci. Model Dev. 9, 505–522 (2016).
doi: 10.5194/gmd-9-505-2016
O’Neill et al. The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev. 9, 3461–3482 (2016).
doi: 10.5194/gmd-9-3461-2016
United Nations Framework Convention on Climate Change (UN General Assembly, 2015); https://unfccc.int/sites/default/files/english_paris_agreement.pdf
IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).
Kravitz, B. et al. First simulations of designing stratospheric sulfate aerosol geoengineering to meet multiple simultaneous climate objectives. J. Geophys. Res. Atmos. 122, 12,616–12,634 (2017).
doi: 10.1002/2017JD026874
Davis, N. A. et al. Climate, variability, and climate sensitivity of ‘Middle Atmosphere’ chemistry configurations of the Community Earth System Model Version 2, Whole Atmosphere Community Climate Model Version 6 (CESM2(WACCM6)). Preprint at Authorea https://doi.org/10.22541/essoar.167117634.40175082/v1 (2022).
Visioni, D. et al. Identifying the sources of uncertainty in climate model simulations of solar radiation modification with the G6sulfur and G6solar Geoengineering Model Intercomparison Project (GeoMIP) simulations. Atmos. Chem. Phys. 21, 10039–10063 (2021).
doi: 10.5194/acp-21-10039-2021