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ABSTRACT Solar radiation modification (SRM) is a potential strategy to rapidly mitigate global warming by reflecting more sunlight into space. However, its impact on tropical hydrological cycles remains underexplored. This study investigates the potential effects of SRM on streamflow in the Kelantan River Basin (KRB) by incorporating climate projections from the Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6) into the Soil and Water Assessment Tool plus (SWAT+) model. Results indicate that UKESM1-0-LL and MPI-ESM1-2-LR exhibit higher uncertainty in representing KRB's climate compared to CNRM-ESM2-1 and IPSL-CM6A-LR. Under SSP5-8.5, maximum and minimum temperatures are projected to increase by up to 3.52 °C by the late 21st century, while SRM scenarios may limit warming to 1.72-2.33 °C, similar to 1.96-2.22 °C under SSP2-4.5. The multi-model ensemble mean projected an inverse V-shaped trend in annual precipitation, with a peak in the mid-21st century before declining, except for G6sulfur, which exhibits a steady decrease. Increases in monthly precipitation from November to January during the 2045-2064 period under all evaluated scenarios may intensify flooding in the KRB. Meanwhile, decreases in streamflow during dry months are projected for the periods 2045-2064 and 2065-2085 under G6sulfur, particularly in the middle and upper basins. 

Abstract Climate change poses significant threats to global agriculture, impacting food quantity, quality, and safety. The world is far from meeting crucial climate targets, prompting the exploration of alternative strategies such as stratospheric aerosol intervention (SAI) to reduce the impacts. This study investigates the potential impacts of SAI on rice and wheat production in India, a nation highly vulnerable to climate change given its substantial dependence on agriculture. We compare the results from the Assessing Responses and Impacts of Solar climate intervention on the Earth system with Stratospheric Aerosol Injection‐1.5°C (ARISE‐SAI‐1.5) experiment, which aims to keep global average surface air temperatures at 1.5°C above preindustrial in the Shared Socioeconomic Pathway 2‐4.5 (SSP2‐4.5) global warming scenario. Yield results show ARISE‐SAI‐1.5 leads to higher production for rainfed rice and wheat. We use 10 agroclimatic indices during the vegetative, reproductive, and ripening stages to evaluate these yield changes. ARISE‐SAI‐1.5 benefits rainfed wheat yields the most, compared to rice, due to its ability to prevent rising winter and spring temperatures while increasing wheat season precipitation. For rice, SSP2‐4.5 leads to many more warm extremes than the control period during all three growth stages and may cause a delay in the monsoon. ARISE‐SAI‐1.5 largely preserves monsoon rainfall, improving yields for rainfed rice in most regions. Even without the use of SAI, adaptation strategies such as adjusting planting dates could offer partial relief under SSP2‐4.5 if it is feasible to adjust established rice‐wheat cropping systems. 

Abstract Uttar Pradesh, with a population of 237 million, is the largest agrarian state in India, located in the Indo‐Gangetic plains. Rice cultivation is widespread across all districts of Uttar Pradesh, which have varying climate regimes, irrigation infrastructures, crop management practices, and farm sizes. The state is characterized by different agroecological zones (AEZs) with semi‐arid to sub‐humid climates with significant variability in monsoon rainfall. In this study, the impact of climate change on Kharif‐season rice is estimated using crop‐climate scenarios in Uttar Pradesh. A process‐based Crop Simulation Model, Crop Estimation through Resource and Environment Synthesis‐Rice, was simulated with bias‐corrected and downscaled climate data for historical (1995–2014) and three future periods (the 2030s, 2050s, and 2090s) for two mitigation pathways (SSP2‐4.5 and SSP5‐8.5) from the Coupled Model Intercomparison Project 6. Phenology, irrigation amount, crop evapotranspiration, yield, and water use efficiency were evaluated and assessed for all AEZs. Based on the ensemble of 16 climate models, rainfed rice yield increased in the AEZs of western Uttar Pradesh due to increased rainfall, while in eastern Uttar Pradesh yield decreased, under both shared socioeconomic pathways (SSPs). Irrigated rice yield decreased in all AEZs under both SSPs due to an increase in temperature and a decrease in the length of the growing period, with reductions of up to 20% by the 2090s. Irrigation requirements decreased from the 2030s to the 2090s due to increased rainfall and decreased crop evapotranspiration. Despite the projected increase in rainfed yield, the overall rice yield is expected to decrease in the future under both SSPs. 

Abstract As the severity of climate change and its associated impacts continue to worsen, schemes for artificially cooling surface temperatures via planetary albedo modification are being studied. The method with the most attention in the literature is stratospheric sulfate aerosol intervention (SAI). Placing reflective aerosols in the stratosphere would have profound impacts on the entire Earth system, with potentially far‐reaching societal impacts. How global crop productivity would be affected by such an intervention strategy is still uncertain, and existing evidence is based on theoretical experiments or isolated modeling studies that use crop models missing key processes associated with SAI that affect plant growth, development, and ultimately yield. Here, we utilize three global gridded process‐based crop models to better understand the potential impacts of one SAI scenario on global maize productivity. Two of the crop models that simulate diffuse radiation fertilization show similar, yet small increases in global maize productivity from increased diffuse radiation. Three crop models show diverse responses to the same climate perturbation from SAI relative to the reference future climate change scenario. We find that future SAI implementation relative to a climate change scenario benefits global maize productivity ranging between 0% and 11% depending on the crop model. These production increases are attributed to reduced surface temperatures and higher fractions of diffuse radiation. The range across model outcomes highlights the need for more systematic multi‐model ensemble assessments using multiple climate model forcings under different SAI scenarios. 

Abstract. The Middle East and North Africa (MENA) region is the dustiestregion in the world, and understanding the projected changes in the dustconcentrations in the region is crucial. Stratospheric aerosolinjection (SAI) geoengineering aims to reduce global warming by increasingthe reflection of a small amount of the incoming solar radiation to space,hence reducing the global surface temperatures. Using the output fromthe Geoengineering Large Ensemble Project (GLENS), we show areduction in the dust concentration in the MENA region under both the globalwarming (RCP8.5) and GLENS-SAI scenarios compared to the present-dayclimate. This reduction in dust over the whole MENA region is stronger underthe SAI scenario, except over dust hotspots and for the dry season. In otherwords, in the summer, with the strongest dust events, more reduction has beenprojected for the global warming scenario compared to the SAI scenario.The maximum reduction in the dust concentrations in the MENA region (underboth global warming and SAI) is due to the weakening of the dusthotspot emissions from the sources of the Middle East. Further analysis ofthe differences in the surface temperature, soil water, precipitation, leafarea index and near-surface wind speed provides some insights into theunderlying physical mechanisms that determine the changes in the future dustconcentrations in the MENA region. Detailed correlation analysis over dusthotspots indicates that lower future dust concentrations are controlled bylower wind speed and higher precipitation in these regions under boththe RCP8.5 and SAI scenarios. 

Abstract. Farmers around the world time the planting of their crops to optimize growing season conditions and choose varieties that grow slowly enough to take advantage of the entire growing season while minimizing the risk of late-season kill. As climate changes, these strategies will be an important component of agricultural adaptation. Thus, it is critical that the global models used to project crop productivity under future conditions are able to realistically simulate growing season timing. This is especially important for climate- and hydrosphere-coupled crop models, where the intra-annual timing of crop growth and management affects regional weather and water availability. We have improved the crop module of the Community Land Model (CLM) to allow the use of externally specified crop planting dates and maturity requirements. In this way, CLM can use alternative algorithms for future crop calendars that are potentially more accurate and/or flexible than the built-in methods. Using observation-derived planting and maturity inputs reduces bias in the mean simulated global yield of sugarcane and cotton but increases bias for corn, spring wheat, and especially rice. These inputs also reduce simulated global irrigation demand by 15 %, much of which is associated with particular regions of corn and rice cultivation. Finally, we discuss how our results suggest areas for improvement in CLM and, potentially, similar crop models. 

Abstract. We quantify future changes in wildfire burned area and carbon emissions inthe 21st century under four Shared Socioeconomic Pathways (SSPs) scenariosand two SSP5-8.5-based solar geoengineering scenarios with a target surfacetemperature defined by SSP2-4.5 – solar irradiance reduction (G6solar) andstratospheric sulfate aerosol injections (G6sulfur) – and explore themechanisms that drive solar geoengineering impacts on fires. This study isbased on fully coupled climate–chemistry simulations with simulatedoccurrence of fires (burned area and carbon emissions) using the WholeAtmosphere Community Climate Model version 6 (WACCM6) as the atmosphericcomponent of the Community Earth System Model version 2 (CESM2). Globally,total wildfire burned area is projected to increase over the 21st centuryunder scenarios without geoengineering and decrease under the twogeoengineering scenarios. By the end of the century, the two geoengineeringscenarios have lower burned area and fire carbon emissions than not onlytheir base-climate scenario SSP5-8.5 but also the targeted-climate scenarioSSP2-4.5. Geoengineering reduces wildfire occurrence by decreasing surfacetemperature and wind speed and increasing relative humidity and soil water,with the exception of boreal regions where geoengineering increases theoccurrence of wildfires due to a decrease in relative humidity and soilwater compared with the present day. This leads to a global reduction in burnedarea and fire carbon emissions by the end of the century relative to theirbase-climate scenario SSP5-8.5. However, geoengineering also yieldsreductions in precipitation compared with a warming climate, which offsetssome of the fire reduction. Overall, the impacts of the different drivingfactors are larger on burned area than fire carbon emissions. In general,the stratospheric sulfate aerosol approach has a stronger fire-reducingeffect than the solar irradiance reduction approach. 

Abstract. The Geoengineering Model Intercomparison Project (GeoMIP) is a coordinating framework, started in 2010, that includes a series of standardized climate model experiments aimed at understanding the physical processes and projected impacts of solar geoengineering. Numerous experiments have been conducted, and numerous more have been proposed as “test-bed” experiments, spanning a variety of geoengineering techniques aimed at modifying the planetary radiation budget: stratospheric aerosol injection, marine cloud brightening, surface albedo modification, cirrus cloud thinning, and sunshade mirrors. To date, more than 100 studies have been published that used results from GeoMIP simulations. Here we provide a critical assessment of GeoMIP and its experiments. We discuss its successes and missed opportunities, for instance in terms of which experiments elicited more interest from the scientific community and which did not, and the potential reasons why that happened. We also discuss the knowledge that GeoMIP has contributed to the field of geoengineering research and climate science as a whole: what have we learned in terms of intermodel differences, robustness of the projected outcomes for specific geoengineering methods, and future areas of model development that would be necessary in the future? We also offer multiple examples of cases where GeoMIP experiments were fundamental for international assessments of climate change. Finally, we provide a series of recommendations, regarding both future experiments and more general activities, with the goal of continuously deepening our understanding of the effects of potential geoengineering approaches and reducing uncertainties in climate outcomes, important for assessing wider impacts on societies and ecosystems. In doing so, we refine the purpose of GeoMIP and outline a series of criteria whereby GeoMIP can best serve its participants, stakeholders, and the broader science community. 

Abstract Atmospheric soot loadings from nuclear weapon detonation would cause disruptions to the Earth’s climate, limiting terrestrial and aquatic food production. Here, we use climate, crop and fishery models to estimate the impacts arising from six scenarios of stratospheric soot injection, predicting the total food calories available in each nation post-war after stored food is consumed. In quantifying impacts away from target areas, we demonstrate that soot injections larger than 5 Tg would lead to mass food shortages, and livestock and aquatic food production would be unable to compensate for reduced crop output, in almost all countries. Adaptation measures such as food waste reduction would have limited impact on increasing available calories. We estimate more than 2 billion people could die from nuclear war between India and Pakistan, and more than 5 billion could die from a war between the United States and Russia—underlining the importance of global cooperation in preventing nuclear war.