Lawrence, M. G. et al. Evaluating climate geoengineering proposals in the context of the Paris Agreement temperature goals. Nat. Commun. 9, 3734 (2018).
Google Scholar
MacMartin, D. G., Ricke, K. L. & Keith, D. W. Solar geoengineering as part of an overall strategy for meeting the 1.5 °C Paris target. Phil. Trans. R. Soc. A 376, 20160454 (2018).
Google Scholar
Crutzen, P. J. Albedo enhancement by stratospheric sulfur injections: a contribution to resolve a policy dilemma? Climatic Change 77, 211–220 (2006).
Google Scholar
Ahlm, L. et al. Marine cloud brightening—as effective without clouds. Atmos. Chem. Phys. 17, 13071–13087 (2017).
Google Scholar
Muri, H. et al. Climate response to aerosol geoengineering: a multimethod comparison. J. Clim. 31, 6319–6340 (2018).
Google Scholar
Kravitz, B. et al. The Geoengineering Model Intercomparison Project (GeoMIP). Atmos. Sci. Lett. 12, 162–167 (2011).
Google Scholar
Robock, A., Oman, L. & Stenchikov, G. L. Regional climate responses to geoengineering with tropical and Arctic SO2 injections. J. Geophys. Res. Atmos. 113, D16101 (2008).
Google Scholar
Tjiputra, J. F., Grini, A. & Lee, H. Impact of idealized future stratospheric aerosol injection on the large-scale ocean and land carbon cycles. J. Geophys. Res. Biogeosci. 121, 2015JG003045 (2016).
Russell, L. M. et al. Ecosystem impacts of geoengineering: a review for developing a science plan. Ambio 41, 350–369 (2012).
Google Scholar
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).
Google Scholar
Zhan, P., Zhu, W., Zhang, T., Cui, X. & Li, N. Impacts of sulfate geoengineering on rice yield in china: results from a multimodel ensemble. Earth Future 7, 395–410 (2019).
Google Scholar
Parkes, B., Challinor, A. & Nicklin, K. Crop failure rates in a geoengineered climate: impact of climate change and marine cloud brightening. Environ. Res. Lett. 10, 084003 (2015).
Yang, H. et al. Potential negative consequences of geoengineering on crop production: a study of Indian groundnut. Geophys. Res. Lett. 43, 11786–11795 (2016).
Google Scholar
Pongratz, J., Lobell, D. B., Cao, L. & Caldeira, K. Crop yields in a geoengineered climate. Nat. Clim. Change 2, 101–105 (2012).
Google Scholar
Proctor, J., Hsiang, S., Burney, J., Burke, M. & Schlenker, W. Estimating global agricultural effects of geoengineering using volcanic eruptions. Nature 560, 480–483 (2018).
Google Scholar
Tjiputra, J. F. et al. Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM). Geosci. Model Dev. 6, 301–325 (2013).
Google Scholar
MacMartin, D. G. & Kravitz, B. Mission-driven research for stratospheric aerosol geoengineering. Proc. Natl Acad. Sci. USA 116, 1089–1094 (2019).
Google Scholar
Lombardozzi, D. L. et al. Simulating agriculture in the community land model version 5. J. Geophys. Res. Biogeosci. 125, e2019JG005529 (2020).
Google Scholar
Popp, A. et al. Land-use futures in the shared socio-economic pathways. Glob. Environ. Change 42, 331–345 (2017).
O’Neill, B. C. et al. The scenario model intercomparison project (ScenarioMIP) for CMIP6. Geosci. Model Dev. 9, 3461–3482 (2016).
Google Scholar
IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).
FAOSTAT (FAO, 2019); http://www.fao.org/faostat/en/?#data/QC
Tai, A. P. K., Martin, M. V. & Heald, C. L. Threat to future global food security from climate change and ozone air pollution. Nat. Clim. Change 4, 817–821 (2014).
Google Scholar
Hsiao, J., Swann, A. L. S. & Kim, S.-H. Maize yield under a changing climate: the hidden role of vapor pressure deficit. Agric. For. Meteorol. 279, 107692 (2019).
Google Scholar
Grossiord, C. et al. Plant responses to rising vapor pressure deficit. New Phytol. https://doi.org/10.1111/nph.16485 (2020).
Rigden, A. J., Mueller, N. D., Holbrook, N. M., Pillai, N. & Huybers, P. Combined influence of soil moisture and atmospheric evaporative demand is important for accurately predicting US maize yields. Nat. Food 1, 127–133 (2020).
Konings, A. G., Williams, A. P. & Gentine, P. Sensitivity of grassland productivity to aridity controlled by stomatal and xylem regulation. Nat. Geosci. 10, 284–288 (2017).
Google Scholar
Novick, K. A. et al. The increasing importance of atmospheric demand for ecosystem water and carbon fluxes. Nat. Clim. Change 6, 1023–1027 (2016).
Google Scholar
Ainsworth, E. A. & Long, S. P. What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2: Tansley review. New Phytol. 165, 351–372 (2004).
Bishop, K. A., Leakey, A. D. B. & Ainsworth, E. A. How seasonal temperature or water inputs affect the relative response of C3 crops to elevated CO2: a global analysis of open top chamber and free air CO2 enrichment studies. Food Energy Secur. 3, 33–45 (2014).
Ainsworth, E. A. et al. A meta-analysis of elevated CO2 effects on soybean (Glycine max) physiology, growth and yield. Glob. Change Biol. 8, 695–709 (2002).
Google Scholar
Leakey, A. D. B. Rising atmospheric carbon dioxide concentration and the future of C4 crops for food and fuel. Proc. R. Soc. B 276, 2333–2343 (2009).
Google Scholar
Ainsworth, E. A. & Rogers, A. The response of photosynthesis and stomatal conductance to rising CO2: mechanisms and environmental interactions. Plant Cell Environ. 30, 258–270 (2007).
Google Scholar
National Research Council Climate Intervention: Reflecting Sunlight to Cool Earth (National Academies, 2015); https://doi.org/10.17226/18988
Lutsko, N. J., Seeley, J. T. & Keith, D. W. Estimating impacts and trade-offs in solar geoengineering scenarios with a moist energy balance model. Geophys. Res. Lett. 47, e2020GL087290 (2020).
Google Scholar
Friedlingstein, P. et al. Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks. J. Clim. 27, 511–526 (2014).
Google Scholar
Tilmes, S. et al. The hydrological impact of geoengineering in the geoengineering model intercomparison project (GeoMIP). J. Geophys. Res. Atmos. 118, 11,036–11,058 (2013).
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).
Google Scholar
Fisher, R. A. et al. Parametric controls on vegetation responses to biogeochemical forcing in the CLM5. J. Adv. Model. Earth Syst. 11, 2879–2895 (2019).
Google Scholar
Bonan, G. B. et al. Model structure and climate data uncertainty in historical simulations of the terrestrial carbon cycle (1850–2014). Glob. Biogeochem. Cycles 33, 1310–1326 (2019).
Google Scholar
Osborne, T., Rose, G. & Wheeler, T. Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation. Agric. For. Meteorol. 170, 183–194 (2013).
Google Scholar
Peng, B. et al. Improving maize growth processes in the community land model: implementation and evaluation. Agric. For. Meteorol. 250–251, 64–89 (2018).
Google Scholar
Buzan, J. R. & Huber, M. Moist heat stress on a hotter earth. Annu. Rev. Earth Planet. Sci. 48, 623–655 (2020).
Google Scholar
Wieder, W. R. et al. Beyond static benchmarking: using experimental manipulations to evaluate land model assumptions. Glob. Biogeochem. Cycles 33, 1289–1309 (2019).
Google Scholar
Mercado, L. M. et al. Impact of changes in diffuse radiation on the global land carbon sink. Nature 458, 1014–1017 (2009).
Google Scholar
Cheng, S. J. et al. Variations in the influence of diffuse light on gross primary productivity in temperate ecosystems. Agric. For. Meteorol. 201, 98–110 (2015).
Google Scholar
Shao, L. et al. The fertilization effect of global dimming on crop yields is not attributed to an improved light interception. Glob. Change Biol. 26, 1697–1713 (2020).
Google Scholar
Vattioni, S. et al. Exploring accumulation-mode H2SO4 versus SO2 stratospheric sulfate geoengineering in a sectional aerosol–chemistry–climate model. Atmos. Chem. Phys. 19, 4877–4897 (2019).
Google Scholar
Levis, S., Badger, A., Drewniak, B., Nevison, C. & Ren, X. CLMcrop yields and water requirements: avoided impacts by choosing RCP 4.5 over 8.5. Climatic Change 146, 501–515 (2018).
Google Scholar
Fricko, O. et al. The marker quantification of the Shared Socioeconomic Pathway 2: a middle-of-the-road scenario for the 21st century. Glob. Environ. Change 42, 251–267 (2017).
Lauvset, S. K., Tjiputra, J. & Muri, H. Climate engineering and the ocean: effects on biogeochemistry and primary production. Biogeosciences 14, 5675–5691 (2017).
Google Scholar
Hurtt, G. C. et al. Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Climatic Change 109, 117–161 (2011).
Google Scholar
West, T. O. et al. Cropland carbon fluxes in the United States: increasing geospatial resolution of inventory-based carbon accounting. Ecol. Appl. 20, 1074–1086 (2010).
Lobell, D. B., Schlenker, W. & Costa-Roberts, J. Climate trends and global crop production since 1980. Science 333, 616–620 (2011).
Google Scholar
Farquhar, G., von Caemmerer, Svon & Berry, J. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149, 78–90 (1980).
Google Scholar
Collatz, G. J., Ribas-Carbo, M. & Berry, J. A. Coupled photosynthesis-stomatal conductance model for leaves of C4 plants. Funct. Plant Biol. 19, 519–538 (1992).
Medlyn, B. E. et al. Reconciling the optimal and empirical approaches to modelling stomatal conductance. Glob. Change Biol. 17, 2134–2144 (2011).
Google Scholar
Long, S. P., Ainsworth, E. A., Leakey, A. D. B., Nösberger, J. & Ort, D. R. Food for thought: lower-than-expected crop yield stimulation with rising CO2 concentrations. Science 312, 1918–1921 (2006).
Google Scholar
The NCAR Command Language (NCL, Version 6.5.0) (UCAR, NCAR, CISL, TDD, 2018); https://doi.org/10.5065/D6WD3XH5
Source: Ecology - nature.com