An Integrated Agenda for Solar Geoengineering Research
This chapter presents the committee’s recommendations for the research agenda to be pursued under the program discussed in Chapter 4. This builds directly upon the analyses presented in the preceding chapters, including the assessment of critical knowledge gaps discussed in Chapter 2 and takes into account the principles for a research program discussed in Chapter 3.
6.1 HIGH-LEVEL FRAMING FOR THE RESEARCH AGENDA
Unlike many typical research agendas that are organized largely around disciplinary fields of study, we propose here an integrated approach that emphasizes linkages across many traditional disciplinary divides. For clarity of presentation and organization, the key issues are categorized here as “clusters” of interdisciplinary research questions that target regions of the SG research landscape that could help reduce the most decision-relevant uncertainties; but these clusters should not be viewed as isolated silos of research. The agenda is also intended to address topics that are not already priorities for the broader climate change research enterprise; although at the same time, we acknowledge (and indeed hope) that some research can advance knowledge both for questions specific to SG and for climate change understanding more generally.
The diverse array of clusters encompassed by the proposed research agenda can be framed within a set of three broad categories, listed below. Note that the first of these categories may be seen as a departure from how a research agenda is traditionally conceptualized in that it focuses on building a stronger foundation for improving the research enterprise itself, and it thus underlies how all the other research areas will be approached.
- Context and Goals for SG Research. This category encompasses studies that help us better characterize the current and future contexts for SG research, development, and possible deployment—with the aim of better understanding the evolving “decision space” for these activities. It includes efforts to clarify the range of possible goals for an SG program and understand how these goals shape research priorities, guide development of modeling scenarios, and
- identify key considerations for decision making. This area of research will help inform decisions about which futures (among the wide range that are possible) may be most fruitful to investigate. It will advance exploration of whether and how SG can be developed to generate broadly beneficial outcomes, how to address the risks and uncertainties, and how to build the capacity needed for countries to engage meaningfully in research and research governance.
- Impacts and Technical Dimensions. This category encompasses research to better understand basic mechanisms determining the technical feasibility of different SG strategies, their effectiveness in terms of regional-to-global-scale cooling, and their potential impacts on other climatic variables (e.g., precipitation). This includes chemistry and microphysics research to understand the properties of injected reflective particles and interactions with clouds and other atmospheric processes, engineering studies of the technical requirements associated with different SG technologies, and advancing strategies to monitor and attribute the climate impacts of SG activities. Research related to human health, social systems, and ecology aims to develop systematic approaches to studying impacts, to better characterize the range of possible impacts, and to consider the uncertainties and limits to understanding impacts.
- Social Dimensions. This category encompasses a wide array of research exploring how to better understand public perceptions of SG research and its possible future deployment; how to fairly govern and effectively engage various publics and stakeholders in SG research, development, and deployment decisions; how to approach domestic and international conflict and cooperation in the SG arena; and how to integrate ethics, justice, and equity considerations. These research dimensions are essential for better understanding questions about the social acceptability of SG.
A critical concept to emphasize is that these general research categories are closely interlinked. Rather than progressing in some simple linear fashion from one stage of research to the other, these categories of research will need to advance in an integrated, interactive manner. For example, the ways in which future contexts are conceptualized (Context and Goals) will affect the scenarios used to study the possible effects of SG interventions (Impacts and Technical Feasibility) and vice versa. If research found that one type of SG intervention would have more widespread beneficial impacts than another type (Impacts and Technical Feasibility), that would likely shape the public acceptability of each of these strategies (Social Dimensions); however, social values and priorities (Social Dimensions) can also help guide the kinds of interventions that are considered and researched (Impacts and Technical Feasibility). These are just a few
illustrative examples of the many linkages to consider. Identifying and investigating these interactions is itself an important aim of the proposed research program. Thus, in the recommendations that follow, we highlight the importance of engagement across research areas and suggest steps to support interaction and integration.
To help define the more specific research that is needed, the committee has identified a set of 13 clusters (listed below) as key locus points for an initial phase of an SG research program. These are framed as “clusters” because each represents a coherent but loosely grouped collection of related research questions and needs, recognizing that there are considerable linkages and overlaps among the different clusters. Figure 6.1 illustrates how the research clusters can be loosely grouped within the broader categories discussed above.
6.2 THE RESEARCH AGENDA TOPICS
This section walks through the proposed 13 research clusters, each with a short overview followed by a collection of key steps forward related to each topic. The nature of these suggestions varies considerably among the different clusters (e.g., some presented as research questions, some as specific research activities). These variations arise because some of these fields are more developed than others in terms of the existing base of research and the theoretical foundations for defining new research activities. For the more nascent fields of research, the suggested steps forward are broader and more exploratory in nature. In addition, these 13 clusters represent widely varying types of research—for instance, ranging from laboratory and field studies, to computer modeling, to quantitative and qualitative social science investigations (e.g., empirical studies, data analysis, surveys, and case studies)—and thus the nature of the steps forward differ accordingly.
Context and Goals for SG Research
 Program Development Pathways:
Designing an SG research program to maximize the prospects for broadly beneficial outcomes.
The exploration and possible implementation of SG—like any other technology—is inherently a sociotechnical enterprise. The generation of scientific knowledge and its application takes place in a particular societal context and therefore has to be cognizant of and responsive to that context; in turn, new knowledge and its application shapes societal discourses and institutions. The context for SG research includes the fact that these technologies would have global and intergenerational consequences. Yet, the institutional capacities to manage SG on behalf of a global, intergenerational public are currently very limited.
SG involves a particularly acute form of the technology control dilemma (also known as the Collingridge dilemma), which holds that social guidance of a developing technology is easiest in its early stages (Collingridge, 1982). However, the precise shape and implications of the emerging technology are often not well understood in these stages, making it difficult to know how to guide it. By the time the technology is developed and its implications are clearer, many features of the technology may be already locked in, making it difficult to shape it in response to societal input.
Even initial technical feasibility assessments for SG require assumptions and design choices that may further shape the trajectory of research and development. For example, models of stratospheric aerosol injection (SAI) require choices regarding
where to inject aerosols (altitude, latitudes) and how much (based on the amount of warming to offset), and these choices can significantly affect the simulated impacts. Such choices can shape SG’s effects and impacts and, concomitantly, its social acceptability. Similarly, in order to assess technical and social feasibility, researchers must make choices and assumptions about SG design. Ideally, such choices would enable the exploration of multiple possible approaches, while taking account of evolving social, political, economic, and climate contexts, as well as public and stakeholder perspectives. But in practice, knowledge of how to achieve these goals is very limited.
The design of an “SG system” (i.e., the constellation of activities and actors involved in the generation and application of scientific knowledge and the shaping and governing of that process) needs further research in multiple dimensions. System design issues reach across planning, research, development, and deployment phases, and these different elements are closely interlinked. For instance, the design of the research program will shape the nature of the scientific explorations undertaken, the knowledge from the scientific explorations will inform decisions about whether and how to proceed with further development and any possible SG deployment, and possible scenarios of SG deployment will inform relevant scientific explorations. The pathways taken in each of these dimensions will depend on the stakeholders involved in the discussions, their questions of interest, and the disciplinary perspectives brought to bear.
The notion of “design” itself implies that there is a goal the system is trying to achieve. For instance, an initial question might be about how much global cooling is desired. But how will that intent evolve over time? Would the goal be to maintain constant temperature, or limit the rate of change of temperature, or simply ramp up to a constant amount of SG (e.g., trying to maintain a specific concentration of stratospheric aerosols)? Even if a hypothetical future SG system could achieve a particular amount of global cooling, who would “decide” the temperature goal, and how would that decision be reached among all the parties that could be affected by the intervention? Are there ways other than temperature goals to conceptualize the SG design? Which stakeholders are part of this decision process? These are questions about the nature of “SG system” design that need further transdisciplinary research.
The way that SG implementation decisions are made can lead to real differences in outcomes. For example, decisions could be made in a well-intentioned, strategic way based on model projections, or they could be made in a completely opportunistic way (e.g., country X has access to airfield at latitude Y and so that is what it uses). For SAI, the type of aerosol itself and location and timing of injection will also affect outcomes and even the extent of uncertainties. But even in the absence of any real “plan,”
choices such as the latitude at which to inject aerosols (or equivalent choices regarding where to deploy marine cloud brightening [MCB]) will affect outcomes, and if SG were to be used, these choices could not be avoided. Thus, an important goal for SG design research is to ensure that those who would potentially be making deployment decisions have information regarding the differential projected impacts from different choices available to them and an understanding of the uncertainties associated with these projections.
Other important factors to understand include how an ongoing SG program might be designed to evolve over time and what information is needed to allow decision makers to evaluate adjustments or decision points as implementation proceeds. Ideally, one could monitor changes to the climate and adjust strategies (including potentially phasing the deployment back out) as new information is gained. Yet without further research, it is not clear which aspects of SG could be effectively monitored and on what timescales—thus, the degree to which it is possible to adaptively manage future SG deployment itself requires additional investigation. This becomes a key issue, given that the desirable and acceptable features of SG might change over time as societal preferences evolve.
Whether and how to proceed with SG research, design, and deployment are societal choices, although hopefully well informed by the science. Research in this area can help us develop an integrated understanding of how different choices would lead to different impacts and of the diverse range of perspectives on objectives and trade-offs. Approaching this issue from a broad “sociotechnical” perspective requires research that addresses a wide array of questions about SG system design, including (but not limited to) those listed below.
Some critical questions to address in this research cluster include the following:
- How and by whom are the scientific questions that need to be answered in an SG research program identified?
- How and by whom are the primary objectives of SG determined (i.e., what risks are to be mitigated and by how much)?
- How and by whom would decisions be made that there is enough understanding of SG benefits and risks either to abandon any further pursuit or to proceed with further development and deployment?
- What level of climate risk and mitigation effort would be sufficient to consider deployment? Who would make such decisions, and how would they be made?
- How do we deal with the distribution of risks and benefits of SG deployment? How should we deal with trade-offs? How do different stakeholders view different trades-offs? (See Section 7 below.)
- How and by whom would choices about SG deployment (e.g., type of aerosol, type of delivery technology, altitude, latitude, quantity of aerosol, frequency, and time of year) be made?
- How would we know that an SG deployment was achieving its objectives? How would we detect and attribute SG efforts? How and by whom would decisions be made about how much SG deployment is enough? How and by whom would decisions be made about the conditions under which SG deployment might be phased out and the process of doing so?
- How do we identify the “appropriate” stakeholders (e.g., natural and social science experts, ethicists, policy makers at different levels, and broader publics) and ensure that they have the capacity and opportunity to effectively participate in the SG design process?
- What dimensions of climate impacts matter most to people? How do these views evolve over time?
Questions pertaining to the underpinnings of design for SG research and deployment include the following:
- What are the limits to what can be achieved by SG interventions? What decision variables matter (e.g., latitudes, seasons, etc.)? What fundamental tradeoffs must be considered (e.g., it would be important to know if you cannot maintain precipitation over both region X and region Y)? Is there an obvious “best” way to deploy (presumably connected to whose interests and concerns are represented)?
- How do we assess the sensitivity of the answers to these questions across different climate models or to uncertain physical parameters in models?
- How can one best use observational information combined with climate model projections to make reasoned decisions about how one adjusts key decision variables?
- What are some of the unforeseen factors that could affect deployment design choices (e.g., the climate response if country X only has access to an airfield at latitude Y and deploys only from there)?
 Future Conditions:
Exploring the range of future conditions (socioeconomic, geopolitical, climatic, and other environmental) under which SG-related decisions will be made.
Future decision making over whether and how SG technologies might be deployed and governed will be informed by an explicit assessment of the range of plausible
future conditions under which such decisions may be made and the implications of those conditions for the outcomes of key deployment and governance decisions. A starting point for such research is the “scenario analysis” approach taken in climate change impact assessments, wherein a broad spectrum of social, economic, political, and cultural elements of future societal pathways are rolled up into a discrete number of storylines. These storylines are meant to represent the range of plausible future conditions under which decision making regarding climate mitigation and adaptation could occur (O’Neill et al., 2017, 2019). Scenario analysis in climate modeling and risk assessment is used to represent uncertainties associated with future socioeconomic and geopolitical conditions whose parametrizations are not easily constrained using empirical methods.
The climate modeling community has long used “Representative Concentration Pathways” (RCPs), which offer a range of plausible future trajectories for greenhouse gas (GHG) atmospheric concentrations and resulting radiative forcing over the coming decades. More recently, these RCPs are being considered together with “Shared Socioeconomic Pathways” (SSPs) that characterize a broad range of possible societal trajectories over the course of this century. Five SSPs have been developed as inputs into climate models in the lead up to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Hausfather, 2018; O’Neill et al., 2017, 2019). Providing broad context for assessing barriers and opportunities for mitigation and adaptation, the SSPs describe futures of sustainability-focused growth and equality (SSP1); a “middle of the road” world where trends follow historical patterns (SSP2); a fragmented world of “resurgent nationalism” (SSP3); a world of increasing inequality (SSP4); and a world of rapid and unconstrained growth in economic output and energy use (SSP5).
To inform SG decision making, scenarios would also need to consider the interactions between future climate forcing and societal trajectories with plausible trajectories for SG deployment and its climatic and socioeconomic consequences. To date, however, modeling work to assess possible future SG deployment and its impacts has been conducted with a more limited set of scenarios that are designed primarily to enhance understanding of physical effects and mechanisms under highly idealized conditions. Scenarios developed under the Geoengineering Model Intercomparison Project include those in which SAI is applied in conjunction with a quadrupling of atmospheric CO2, with a 1 percent per year increase in atmospheric CO2, and with a moderate warming scenario (RCP4.5). Recent single model studies have produced simulations that kept temperatures to 1.5 or 2.0°C levels (Jones et al., 2018; Tilmes et al., 2016, 2020).
On an ad hoc basis, individual research initiatives have also explored outcomes of a somewhat broader range of forcing and implementation scenarios. Papers have proposed scenarios that, for example, maintain a fixed temperature (Ricke et al., 2010) or a fixed rate of change of temperature (MacMartin et al., 2014a) or cut the rate of change of net radiative forcing in half (Irvine et al., 2019) in climate and economic models. But scenarios have not yet been established and adopted by the SG research community to explore and provide policy-relevant assessments of impacts under a more broadly representative range of plausible pathways of SG deployment. There are, for example, several scenarios under which SG might be deployed that have been characterized in the research literature and in broader societal discourse, including the following:
- “Peak shaving” under idealized conditions of modest climate overshoot and capacity for sustained effective governance (MacMartin et al., 2018b; Tilmes et al., 2020).
- Deployment in “climate emergency” conditions of continued rising GHG concentration, increasingly severe risks, and uncertain capacity for sustained effective governance.
- Unilateral deployment by an actor seeking to use SG as a means to control climate or with other unknown intentions, without informing others or abiding by any international governance norms that may be established (Victor, 2019).
- Deployment under conditions of competing objectives among nations regarding temperature and impact goals (Frumhof and Stephens, 2018).
These scenarios place the context of decisions to deploy as driven mainly by concerns over climate risk. There is also a need to systematically explore the possible socioeconomic and geopolitical conditions that national governments and other actors may experience in the future under all phases of a possible future use of SG. These included decisions to deploy, adjustments to implementation over time, detection and attribution of impacts, and decisions to terminate.
Socioeconomic and geopolitical conditions are important variables affecting SG outcomes and work is needed to more fully explore a sufficiently broad range of cases, including those that consider the distribution of impacts. Projects seeking to integrate input from diverse disciplines to develop a broader set of policy-relevant SG scenarios are now under way. The National Socio-Environmental Synthesis Center, for example, is convening experts to “develop a set of scenarios and models that integrate social and environmental aspects of climate engineering technologies and their interactions with mitigation efforts.”1 Building on this and other nascent initiatives, an SG research
1 See http://ceassessment.org/new-scenarios-and-models-for-climate-engineering/.
program could seek and incorporate input from decision makers and representative stakeholders to ensure that SG scenarios take account of diverse policy-relevant perspectives (engagement strategies discussed in earlier chapters). Research scenarios that are co-developed with stakeholders are likely to be more credible, salient, and legitimate and therefore more useful to support decision making (Cash et al., 2003; Dilling and Lemos, 2011).
An important limitation of scenarios in SG modeling is that they are inherently static; that is, they are not well suited to incorporate dynamic feedbacks from societal responses to SG deployment and other changing geopolitical conditions. Yet, uncertainties over societal feedbacks, such as the effect of SG research and development on emissions reductions, may dominate considerations over whether, for example, global SG might be effectively governed for a sustained (half-century or longer) time period. Thus, it will be important to characterize the limits to scenarios in SG decision making and explore ways to explicitly characterize the implications of socioeconomic and geopolitical uncertainties to decision makers. In addition, it will be important to consider novel approaches to representing societal feedbacks in climate impact assessments that reflect the much shorter timescales between deployment and climate response expected with SG relative to mitigation.
Some critical steps forward to advance this research cluster include the following:
- Develop an improved set of SG scenarios for use in impacts modeling and policy assessments. These scenarios should characterize a representative range of socioeconomic, geopolitical, and climatic and other environmental conditions under which SG deployment decisions might be made. They should be developed through collaboration among experts across relevant natural and social science disciplines as well as include substantial participation of experts from developing nations. They should foster alignment with the SSP scenarios (O’Neill et al., 2019) and other scenario processes as appropriate, such as those developed for the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (Rosa et al., 2017).The process of scenario development should include the solicitation of meaningful input and review from a representative range of policy makers and stakeholders, including from non-western and developing country perspectives. The scenarios to be developed are likely to be more credible, salient, and legitimate for informing decision makers if they are co-developed in consultation with a broad range of societal actors as described above (Cash et al., 2003).
- Develop new analytical approaches to socioeconomic uncertainty assessment. Such approaches are needed to accommodate the problem of the short timescale between implementation of shortwave SG forcings and
- physical Earth system responses. This includes the development of novel socio-environmental systems modeling frameworks in which feedbacks between climate outcomes and climate decision making are represented as dynamic processes with uncertain, but empirically calibrated, parameterizations. For example, some models have previously explored the relationship among perception of climate change, support for emissions reductions policies, and policy-driven climate outcomes (e.g., Beckage et al., 2018; Ricke and Caldeira, 2014). Such models could be a valuable tool for understanding the dynamical relationship among SG, mitigation, and adaptation in a way that fixed emissions and forcing scenarios cannot. (See related discussion in Research Cluster 3,“Integrated Decision Analysis.”)
 Integrated Decision Analysis:
Understanding implications of, and strategies to address, persistent uncertainties that affect decision making related to SG.
If the aim of an SG research program is to reduce decision-relevant uncertainties, more comprehensive, innovative approaches to uncertainty analysis will be required in order to effectively integrate across many of the research questions discussed throughout this chapter.
Scenario analysis research.
Some scholars suggest that dynamic social system feedbacks are the most fundamental uncertainty associated with long-term outcomes of SG implementation. But it is unclear whether socioeconomic uncertainty in analyses including SG can be adequately characterized through use of scenarios, which are inherently static. Instead, it may be more important to identify ways to incorporate a new category of socioeconomic model uncertainty into “partitioned outcome” uncertainty assessments that include SG. In addition, it will be necessary to develop decision analytic frameworks that accommodate simultaneous consideration of SG with other climate risk mitigation tools, for example, portfolio approaches (Cao et al., 2017; Ricke and Moreno-Cruz, 2020) or “cocktail geoengineering” (Cao et al., 2017). (See related discussion under Research Cluster 1,“Future Conditions.”)
Integrated assessment research.
Another tool broadly applied for examining the implications of uncertainty for climate decision making is integrated assessment modeling, wherein idealized models of the climate system and the economy are run simultaneously. Integrated assessment models (IAMs) have been used to explore the implications of key uncertainties to setting optimal climate policy or reaching specified climate policy goals, such as emissions or temperature targets. Applying IAMs for decision-analytic purposes requires having a robust integrated model of the socio-environmental system. In the near term, this presents a problem for application of
IAMs to uncertainty assessment of SG outcomes because the science of SG impacts is fairly immature. Without robust reduced-form, empirically parameterized models of the relationship between climate variables and socioeconomic outcomes the output of IAM-based SG decision analysis will not be reliable or meaningful.
IAMs can be powerful tools for bridging natural science, social science, and economics and for investigating critical questions about SG. At present, however, the different IAMs being used for climate-related research use widely differing assumptions, which makes results difficult to reproduce. Moving forward, it will be important to organize standardized intercomparison studies that utilize comparable scenarios and simulations.
Decision making under deep uncertainty.
A number of separate but related methodologies have been developed for conducting decision analysis under conditions of “deep uncertainty,” which is defined as “conditions … where analysts do not know, or the parties to a decision cannot agree on, (i) the appropriate conceptual models that describe the relationships among the key driving forces that will shape the long-term future, (ii) the probability distributions used to represent uncertainty about key variables and parameters in the mathematical representations of these conceptual models, and/or (iii) how to value the desirability of alternative outcomes” (Lempert et al., 2003). At present, questions about outcomes under potential future implementation of SG appear to meet such “deep uncertainty” conditions. Methods used for decision analysis under such conditions have been labeled as Robust Decision Making, Real Option Analysis, and Adaptive Policy Making.
Characteristics of these tools include consideration of a broad range of scenarios and decision strategies; application of satisfactory (as opposed to optimal) decision criteria; and use of adaptive learning, wherein decision strategies and criteria are iteratively adjusted with additional information. Prioritizing research that applies to SG critical methods for decision making under deep uncertainty could help identify strategies for executing research that quantifies uncertainty in a holistic way.This will aid future decision making about setting further research priorities and weighing pros and cons of SG implementation.
Some critical steps forward to advance this research cluster include the following:
- Develop methodologies to incorporate socioeconomic model uncertainty into SG outcome uncertainty assessments, including both empirical uncertainty from climate effect and impact studies, as well as parametric and model-form uncertainties.
- Develop more robust, empirically parameterized models of the relationship between climate variables and socioeconomic outcomes to support IAM-
- based decision analyses, in particular relationships that do not primarily represent outcome-climate relationships as a function of temperature.
- Advance the application of methods for decision making under deep uncertainty to SG, including through the examination of outcomes under a diversity of sociopolitical scenarios, non-optimizing (satisficing) decision criteria, and adaptive learning strategies.
- Develop decision analytic frameworks that accommodate the examination of outcomes in the presence of heterogeneity in decision makers and a diversity of international institutional constraints (including lack of cooperation and coordination between parties engaging in SG activities).
 Capacity Building:
Developing the capacities needed for all countries to engage meaningfully with SG research and research governance activities.
The need for helping countries around the world build capacity to participate in research and decision-making processes is a topic that often arises in discussions about SG intervention strategies. Yet there is almost no systematic exploration in the SG literature about what kind of capacities are most needed for allowing effective engagement with research and research governance efforts, and how these capacities might be developed and sustained across a wide array of geographical and cultural contexts. The importance of pursuing such questions stems from our recognition that involvement of a diverse range of stakeholders is critical for robust SG research, design, and governance—and that individual and community perspectives on almost all aspects of this issue are shaped by local context. While such realities greatly enhance the complexity of capacity building efforts, recognizing and addressing these diverse needs will help ensure a more robust SG enterprise.
Some critical questions to address in this research cluster include the following:
- What kinds of capacities are needed in order to engage meaningfully with critical dimensions of SG research and research governance?
- What are the current differences and commonalities in capacities between the Global North and South? What capacity exists today, and what are the key gaps?
- What kinds of capacities are needed to enable a transdisciplinary, robust, and adaptive SG research enterprise? What types of capacities are desired by countries not currently involved in SG research?
- What kinds of physical science (e.g., experimental, modeling, or engineering) and social science, humanities, policy, and legal expertise might be needed?
- What kinds of “boundary” actors might be important to serve as bridges across disciplines, issues, and stakeholders?
- What types of organizational entities (e.g., academia, civil society, private firms, governments, or international organizations) should be focal points for capacity building?
- What kinds of capacity might be needed in broader general “publics,” in order to fully and effectively engage with the SG research enterprise?
- What kind of institutional forms and capacities might be required in order to suitably organize and coordinate among the many actors involved in an SG research program?
- What kinds of expertise and institutional capacities are needed in order to design an SG research enterprise that is truly transdisciplinary, sociotechnically robust, and adaptive?
- What kinds of expertise and institutional capacities would be needed to suitably design and govern SG deployment activities?
- How might such capacities be developed, strengthened, maintained, and assessed?
- What might be the role of various actors (e.g., national and sub-national governments, academia, philanthropies, and international organizations) in supporting the development of needed capacity in the Global North and South? What kinds of efforts and resources are being devoted currently to building such capacity?
- What might be the role of and best mechanisms for international (N-S, S-S) cooperation in developing different kinds of capacity pertaining to scientific knowledge generation, research governance, and SG governance?
- What are the greatest areas of opportunity for capacity building, and what are the most significant barriers? How can opportunities be best utilized and barriers be reduced?
- What levels and kinds of financial, institutional, and political support would be needed to build the capacity for robust engagement by climate-vulnerable regions, indigenous peoples, and nations of the Global South in SG research and research governance, and how might such support be secured?
Impacts and Technical Dimensions
 Atmospheric Processes:
Understanding chemical and physical mechanisms that determine how addition of materials to the atmosphere alters the reflection and transmission of atmospheric radiation.
There is a wide array of research questions to explore in order to better understand the technical feasibility of SG interventions, and the exact nature of these questions
varies depending on whether one is focused on SAI, MCB, or cirrus cloud thinning (CCT). The discussion in this part of the research agenda is thus longer than the other topics discussed in this chapter; it is broken out into three separate sub-sections, each focused on the different SG strategies.
Stratospheric Aerosol Injection
It is clear from the Chapter 2 discussion that adding aerosols to the stratosphere would result in global cooling at the surface. Predicting the magnitude of this cooling, the climate response more generally, and the resulting impacts requires use of a climate model (discussed in Research Cluster 6). Those predictions depend on the concentration, size distribution, and spatial distribution of the aerosols injected, their radiative properties, and chemical effects; thus, predictions depend on the ability to adequately characterize and simulate important aerosol processes that occur at small spatial scales (relative to the grid scale of a climate model). The uncertainties in processes translate into uncertainty in predicting policy-relevant impacts. Reducing uncertainty in the relevant stratospheric processes is thus a high priority.
This cluster will involve higher resolution simulations along with observational, laboratory, and (potentially) outdoor experiments. Because of the long lifetime of aerosols in the stratosphere (relative to transport timescales), and because some of the relevant observations that might constrain processes are at a larger scale, research to resolve process-level uncertainties cannot be conducted completely independently from climate modeling research (described further below and in the next section).
As described in Chapter 2, the overall magnitude and spatial distribution of the forcing produced by SAI depends strongly on the aerosol size distribution (or, equivalently, ratio of surface area to volume or mass), as well as feedbacks that depend on the aerosol-induced stratospheric heating (e.g., changes in stratospheric water vapor concentrations, in stratospheric circulation, and in upper tropospheric cirrus cover). Here we discuss the need to accurately represent these processes in climate models (capturing both longwave and shortwave effects from aerosols), and other related dimensions of this issue are discussed under Research Cluster 6. In addition, given that one of the key SAI impacts of concern is the effect on stratospheric ozone, chemistry also needs to be accurately predicted, both for sulfate aerosols and for any other proposed material.
Processes will need to be understood as a function of how much material is added for different choices of injection latitude, altitude, and season, and for different choices for the aerosol material itself (e.g., sulfate, calcite, or other solid aerosols). The method of delivering the material also matters—for example, for sulfate, whether delivered as a
precursor gas (SO2 or H2S) or as small H2SO4-containing aerosols. If lofting is via aircraft (as is likely), then ions present in aircraft exhaust may play an important role in the ultimate size distribution.
One of the research priorities for SAI is thus to address critical gaps in knowledge about the evolution of the aerosol particle size distribution—specifically, to explore plume dynamics (i.e., what happens after release from an aircraft in a coherent plume versus release uniformly mixed over a gridbox of a climate model and how long that plume stays coherent), particle nucleation (which is influenced by plume dynamics) and subsequent growth (which will depend on the existing background aerosol concentrations), and how implementation choices impact outcomes. This includes a need for improved understanding of stratospheric dynamics (mixing) and oxidation timescale (for gas addition) for an SAI. Finally, it is important to understand chemical interactions and how SAI impacts may be affected by future changes in atmospheric composition and chemistry (e.g., changes in halogen chemistry related to decreases in chlorofluorocarbons and bromine; increases in ambient NOx due to increasing N2O), and feedbacks on ozone due to stratospheric temperature changes.
Understanding how aerosol surface area and volume evolve in response to the localized addition of aerosol or aerosol gaseous precursors requires detailed simulations of nucleation processes (Lee et al., 2019) to identify the relevant rates of competition between nucleation and growth. The initial stages of particle formation and growth occur at sizes smaller than 10 nm diameter, which have thus far only been reliably quantified by simulation and laboratory experiments (Lee et al., 2019). Observations of the resulting size distributions could provide constraints that improve representation by climate models, but these observations would not be able to distinguish among the driving processes (e.g., vapor oxidation, heteromolecular and ion-induced nucleation, plume dynamics, or near-field coagulation of particles smaller than 10 nm diameter); nor could such observations distinguish interactions among chemistry, microphysics, and large-scale circulation. Establishing a quantitative and causal link between inputs and the aerosol size distribution must rely on laboratory experiments to verify model parameterizations, which must then be constrained by field observations. Designing optimal methods to inject vapors or particles requires understanding these causal links.
Understanding the impact of SAI forcing on stratospheric and upper tropospheric composition requires quantifying the impact of the particles emitted (and any exhaust from the delivery system) on ozone chemistry and stratospheric dynamics. Aerosols will affect stratospheric dynamics through heating (from absorption of infrared [IR] radiation). Predicting the changes to stratospheric circulation requires a climate model,
and those predictions depend on an accurate parameterization of the heating rates. The impact of aerosols on upper tropospheric cirrus also needs to be understood; cirrus may be influenced by changes to vertical temperature gradients and hence aerosol heating, as well as potentially by aerosols themselves. As changes to cirrus would affect the overall radiative forcing, these processes will also need to be understood and properly represented in climate models.
Some open research questions associated with the aerosol microphysics of SAI include the following:
- For gaseous additions, what is the rate of formation and growth of particles from their precursors, and how does this depend on the time and location (latitude and altitude) of injection? How does this depend on the aerosol concentrations already in the stratosphere? What aspects of these processes are not well represented by available models? How well can these processes be constrained by existing observations (e.g., after volcanic eruptions)?
- For direct addition of aerosol, what are the effective concentrations of particles that determine the coagulation rates in the near field following injection, and how are these affected by aircraft and local dynamics? To what extent do these processes affect the resulting particle size distribution?
- How is plume dispersal influenced by the wake of the aircraft, and how does that depend on the location and height of injection? Do ions generated in the engine enhance the rates of nucleation significantly (i.e., by a factor of 10 or more)?
- Given the results of the items above, are existing models of nucleation, aerosol dynamics, and plume dispersion sufficient to adequately predict the timing and properties of the particle size distribution for a given input of aerosol or precursor over a range of altitudes and latitudes?
Addressing these questions requires a mix of (i) laboratory measurements of the rates of oxidation of aerosol precursors, (ii) accurate simulation of microphysical processes, and (iii) a sufficiently realistic representation of both the small-scale turbulence and the larger-scale circulation. Modeling of turbulence in the lower stratosphere is improving, but it needs to be constrained by comparison to observations (including capabilities to measure both background conditions and aircraft-perturbed turbulence). Near-field dynamics will necessarily be parameterized in large-scale models used to evaluate SAI; thus, accurate parameterizations need to be constructed to adequately describe the subgrid-scale processes and their dependence on injection parameters.
To better understand the impact of SAI forcing on stratospheric and upper tropospheric composition, open research questions include the following:
- What are the rates of heterogeneous chemistry occurring on the surfaces of SAI particles? This requires knowledge of what the surfaces are and their interaction with, for example, existing sulfate, N2O5, HCl, and ClONO2 (factors that could be examined in laboratory experiments).
- How would SAI interventions (addition of gases, liquids, or solids) alter ice and nitric acid trihydrate nucleation rates in the stratosphere, and how would this influence polar denitrification/dehydration?
- What are the heating rates associated with the SAI? This requires knowledge of the optical properties of the injected particles and their volume and mass, which need to be predicted from the injection material and conditions.
- How does stratospheric circulation adjust to the changes in shortwave and longwave forcing? How does stratospheric water vapor change as a result of the circulation changes and tropopause heating?
- How does stratospheric ozone change due to changes in heterogeneous chemistry and stratospheric circulation? Models based on laboratory measurements provide a starting point for these questions, but verification with in situ measurements may be needed.
- How much of an increase in aerosol concentration in the upper troposphere (UT) will occur? What is the impact of the additional or larger aerosol particles on cirrus (or at higher latitudes, on polar stratospheric clouds)? How does this compare to changes in vertical velocity from stratospheric heating?
Addressing all of these questions will require a combination of modeling, laboratory studies, new observations, and, potentially (if these other approaches prove inadequate), controlled-release experiments. Addressing the microphysical questions in particular likely requires a combination of plume-scale microphysical modeling and laboratory measurements of chemical reaction rates and yields, followed by comparison of the model results with relevant observations.
Collecting observations after volcanic eruptions, such as those suggested in the NASA Major Volcanic Eruption Response Plan (NASA, 2018), may be able to help reduce some of the uncertainties (specific to sulfate), by putting some constraints on aerosol coagulation, chemistry, and heating rates (as well as water vapor, or circulation changes), along with potentially reducing uncertainty in stratospheric circulation and transport.
Laboratory studies may be appropriate to reduce uncertainties in processes that occur on short timescales and small spatial scales (e.g., within an aircraft plume), but it is difficult to maintain stratospheric conditions in a laboratory setting over substantial timescales. Thus, there is a potential role for deliberate controlled-release experiments to better constrain processes occurring within an aircraft plume in particular, espe-
cially for direct injection of sulfate aerosol (as accumulation-mode H2SO4) or alternate aerosols for which there is no natural analogue.
Some critical steps forward to advance this research cluster (for SAI) include the following:
- Advance rigorous analysis of existing uncertainties—including how well they are or are not constrained by existing data (e.g., how much parameters can be varied while still matching observations) and how much that range of uncertainty influences projected climate outcomes from SAI (i.e., how to prioritize which sources of uncertainty to reduce)—and assessment of which uncertainties can be reduced and by how much (using existing and new observational data, laboratory measurements, and/or in situ deliberate releases of material).
- Identify quantitative linkages with uncertainty estimations (using realistic rather than idealized scenarios) among the different steps from release of injected materials to the resulting changes in aerosol surface area and volume, and changes in stratospheric composition. Critical sources of uncertainty should be identified, bounded if possible, and their impact on predictions assessed.
- Develop a program to characterize the gas and aerosol dynamics and chemistry following volcanic eruptions that inject substantial H2S and SO2 in the stratosphere (observed over several months) to provide key observations for reducing uncertainty associated with SAI. One such plan has been developed, but not yet deployed, by NASA (see above).
- Advance laboratory measurements and high-resolution microphysics plume model simulations to quantify some of the uncertainties in near-field aerosol particle size distributions. If such uncertainties cannot be reduced by laboratory measurements, then direct releases of materials into the stratosphere to study the aerosol dynamics and chemistry could be performed; however, heterogeneous chemistry of proposed alternatives to sulfate should be investigated in laboratory experiments before considering atmospheric release.
- Study the impact of enhanced aerosol input to the UT by improving understanding of the ice nucleation properties of the different proposed particles and of the size distribution and lifetime of such aerosols in the UT. Laboratory experiments and detailed simulations provide a starting point for these questions.
- Climate models are the critical tool to assess large-scale climate responses associated with SAI. Currently, these rely on adequate parameterizations of subgrid cell processes; thus, the output of all of the above steps needs to be incorporated in improved parameterizations.
Observational Needs. Expand monitoring of baseline conditions of the stratosphere, for model evaluation, for improving the representation of the aerosols in the stratosphere without SAI, for understanding how stratospheric aerosols influence dynamics and chemistry, and thereby for understanding the impacts of SAI on stratospheric ozone and the resulting tropospheric ultraviolet (UV) dose. The following observational recommendations from the World Meteorological Organization Ozone Managers Meeting (2017)2 are suggested as a necessary precondition for SG research involving stratospheric aerosol manipulation:
- Understanding the important connections among changes in ozone, climate, and atmospheric transport—and in particular expected changes in the global meridional Brewer-Dobson Circulation and unexpected events like the recent break of the Quasi-Biennial Oscillation—require appropriate monitoring of temperature, winds, and trace-gas profiles (especially of dynamical tracers like N2O and SF6) as well as ozone and water vapor.
- Continuation of ground-based stations—especially those with long-term records of ozone, trace gases, UV, temperature, and aerosols—is necessary to provide a reliable baseline for trend estimation and for assessments of polar ozone loss. The steady decrease in the number of stations, especially for profile measurement capabilities, is endangering the unambiguous determination of trends and the capturing of unexpected events, as well as our ability to validate satellite data records.
- Continuation of limb emission and IR solar occultation observations from space is necessary for global vertical profiles of many ozone and climate-related trace gases and parameters. Without such observations, the accuracy of the predictions of data assimilation systems and related services to policy makers will degrade.
Marine Cloud Brightening
For understanding MCB, the highest priority research questions are how aerosols interact with clouds locally (and immediately) and regionally (and over days). These same questions are also issues of great importance for advancing fundamental understanding of climate change, and thus any advances in this understanding would be beneficial on multiple fronts.
2 See http://conf.montreal-protocol.org/meeting/mop/cop11mop29/presentations/English/10ORM_COP_MOP_Jucks_V2.pdf.
Resolving these questions requires observations, including controlled release experiments, to improve model representation of stratocumulus radiative response to aerosols. Specific links between aerosol size and composition and forcing changes should be mapped out, along with the types and properties of clouds that can be brightened. These results will be needed to inform the design of a distribution system, because the production and delivery system required depends on the size and tolerance of the cloud interaction processes as well as the ocean region and season. For example, we need to understand the conditions in which excess droplet numbers could cause cloud dissipation, since such “overshoots” in number concentrations could sufficiently reduce cloud fraction, thickness, and optical depth so that the increase in reflectance is more than offset. Particle size could impact such feedback processes but we do not yet have the observations and models needed to determine the design criteria for a particle production and delivery system.
Uncertain cloud processes.
As discussed in Chapter 2, given the complex interaction between microphysics and turbulence in the marine boundary layer, at scales too small to be captured in global-scale models, idealized climate model simulations of MCB interventions do not provide reliable projections of climate impacts. There are two types of processes that need to be considered, and they differ in scale and impact. First is the intended effect—brightening of clouds by increasing the number of droplets. This effect occurs locally and within minutes of when particles reach the cloud layer (an effect that underlies the canonical observations of ship tracks [Twomey, 1974]). The second type of effect is a consequence of changes in the drop distribution (and possibly the buoyancy and turbulence), which alters the precipitation and the extent of the cloud. This effect relies on larger-scale interactions with heat and water transport and determines the evolution of the cloud over hours to days. While the first type of process affects how much a cloud will brighten, the second type can alter the so-called lifetime of the cloud, and so it affects how long the brightening will persist in the atmosphere.
For the first type of process, observations and high-resolution modeling studies need to address the following questions (for the relevant conditions, i.e., regions, seasons, and frequency):
- How does the distribution of updraft velocities in a cloud result in which particles are activated to droplets?
- How does turbulence in the boundary layer drive entrainment of free tropospheric or unsaturated air into a cloud and affect droplet growth and evaporation?
- For what size and density range of particles is boundary layer turbulence sufficient to distribute particles emitted at the surface into the cloud layer?
- Since drop formation is a strongly threshold-dependent process in most warm clouds, are there nonlinearities associated with spatially localized particle sources that may enhance or dampen MCB in ways not predicted by current observations of such isolated perturbations as ship tracks?
- Do multilayered clouds reduce the effectiveness of MCB because of vertical structure and scattering processes not represented by models?
- Is particle absorptivity sufficient to dampen buoyancy in clouds and reduce liquid water path? (This question relates to whether combustion emissions that form ship tracks are qualitatively different from the salt, which would likely be used as CCN for MCB.)
- How is the vertical distribution of droplet sizes within a cloud affected by turbulence variability and strength?
The second type of process is dependent on the first, since the drop distribution and air motion (turbulence) changes are the starting points for drizzle formation. However, the longer time needed for these processes to interact and evolve means that their impacts are more widely distributed to downwind regions, and this requires additional observations and constrained modeling to address the following questions:
- How much do giant CCN and turbulence contribute to droplet spectral broadening (Feingold et al., 2002; Witte et al., 2019)? Do these large particles need to be avoided when attempting MCB?
- Will additional droplet numbers result in enhanced cloud evaporation, causing cloud thinning rather than brightening?
- How does aerosol mediate the diurnal cycle of precipitation? Does this vary depending on either aerosol amount or CCN spectrum (activation curve as a function of supersaturation) associated with different airmass regimes?
- What is the role of aerosol in controlling drizzle fluxes from the cloud layer, and how does the drizzle redistribute moisture and heat in the sub-cloud layer?
- Do models initialized with the measured aerosol properties reproduce the observed ACI evolution along Lagrangian tracks from the coast into the stratocumulus regions offshore (Christensen et al., 2020)?
Because these processes are complex and interacting, existing observational data sets are not sufficient to establish causal relationships. Observations and models need to address these questions jointly in order to assess whether model microphysics and turbulence are realistic (with chemically and optically realistic particles). Large eddy simulation (LES) modeling is an important tool for providing realistic turbulence, but it needs to be constrained by comparison to relevant observation and often lacks particles with realistic size distributions and chemical composition. Therefore, field
measurements are needed to provide the range of conditions and constraints that parameterizations must represent for the regions in which the model is applied.
Controlled emission experiments.
Because the variability of turbulence in the Marine Boundary Layer (MBL) has few observations to constrain a very complex problem, observations need to target a series of measurements in three specific target regions (northeastern Pacific, southeastern Pacific, and southeastern Atlantic) to obtain the statistics needed to constrain LES and identify statistically robust answers to the research questions posed above. For example, satellite evidence indicates that the northeastern Pacific stratocumulus cloud decks in the subtropical region are most susceptible to changes in their outgoing shortwave radiation due to changes in cloud microphysics (Painemal, 2018). This means that existing efforts have been insufficient to make progress on this problem due to both limited resources and limited ranges of CCN in otherwise similar (or effectively “controlled”) conditions. Current shipping routes do not provide the frequency or spatial coverage needed to assess MCB in clean regions with the necessary amount of sampling because when ships are transiting, they tend to follow shipping lanes that provide the highest fuel efficiency, rather than provide coverage of clean regions needed to sufficiently assess MCB.
Measurements of the effects of land-based urban and industrial pollution sources do not provide the independent information needed to assess causal relationships because it is not possible to disentangle the co-variability of meteorology and aerosol perturbation. For example, in many regions, such as the northeastern Pacific coast, polluted air masses also tend to be dry and warm, whereas clean air masses tend to be wetter and colder (Atwood et al., 2019). This means that the driving forces of the clouds (temperature and water) cannot be investigated independently from the size and concentration of pollution particles.
For these reasons, an effective MCB research plan would include controlled emission experiments in the atmosphere. The rationale for this is the overwhelming need for in situ process studies in MCB-relevant conditions. To a large extent, observational research on the Earth system has relied on existing phenomena and the way that their changes over time and space yield correlations. This means that causal and quantitative relationships rely on laboratory analogues and numerical simulations. However, neither laboratories nor models can represent the full complexity of the actual atmosphere, ocean, and land system. By introducing a controlled perturbation into the Earth system, in which the particles and meteorology are not related, it is possible to gain new and more accurate characterizations of that system. The resulting information is qualitatively different from that from existing modes of research and can serve to accelerate our understanding of both potential interventions and future climate change. Moreover, the type and scope of the controlled emission experiments that
would be required are very small compared to the nature and emissions of many current human activities for recreation, entertainment, conservation, and commerce purposes, and they are far less than those of ongoing military exercises. Examples of past experiments that used controlled sources include the U.S. Department of Energy (DOE) Free-Air CO2 Enrichment (FACE), Eastern Pacific Emitted Aerosol Cloud Experiment for paraffin particles (Russell et al., 2013), and Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) for biomass burning emissions.3
One example of an open question that requires a process study with controlled emissions is aerosol-related cloud feedbacks. Specifically, the second type of lifetime processes can include self-limiting feedbacks of aerosol effects on cloud precipitation (self-limiting because precipitation removes water and then the process stops) that could be uniquely targeted with controlled experiments (Ackerman et al., 2004; Gryspeerdt et al., 2016, 2019b). For example, there is recent evidence that drizzling of stratocumulus clouds can lead to cloud dissipation in some areas, which are evident in observations as pockets of open clouds (POCs; Feingold et al., 2015; Sorooshian et al., 2009; Wang and Feingold, 2009; Xue et al., 2008; Yamaguchi and Feingold, 2015). While POCs are important because they are widespread and they appear to be associated with aerosol removal by precipitation scavenging, disentangling effects from aerosol sources and sinks is nearly impossible without the ability to do repeated controlled experiments in the relevant region and season.
Testing for both brightening and lifetime effects is central to MCB because it means that aerosol effects would not scale with the amount (and spatial coverage) of aerosol, since it could mean that a large number of clouds either are insensitive to particle addition or have counteracting feedbacks such as increased dissipation. This behavior is also at the center of inter-model disagreements about aerosol indirect effects on the radiative balance. The complex interplay of a variety of chemical and physical processes—scavenging rates, precipitation frequency and distribution, entrainment of high or low humidity air and particles, cloud dissipation, cloud air motion spectra and buoyancy changes, and cloud heating from water condensation and particle absorption—means that observed correlations will not imply causation and that model results may suffer from counteracting errors that need to be isolated (Mulmenstadt and Feingold, 2018). In short, it is not known whether radiative forcing is more buffered to the effects of added aerosols than is included in current climate models.
Climate model development.
The best tools for integrating our knowledge of atmospheric processes, and for evaluating whether our understanding of those processes
3 See DOE/FACE, https://facedata.ornl.gov/; FIREX-AQ, https://blogs.nasa.gov/earthexpeditions/tag/firex-aq/.
is consistent with observations, are global climate models. Climate models are also needed to study the effectiveness of MCB and the possible unintended consequences of MCB for precipitation and other impacts. Thus, a priority is to develop climate models with the skill to simulate MCB implementation and to represent accurately three basic components: (i) cloud occurrence and properties, (ii) aerosol emissions and processes, and (iii) interactions between aerosols and clouds.
Clouds. Marine stratocumulus clouds are a persistent feature of the northeastern Pacific, southeastern Pacific, and southeastern Atlantic, with a variety of classic studies characterizing some of the key features of the cloud climatologies in those regions (Lenschow et al., 1988; Painemal and Zuidema, 2011; Painemal et al., 2014, 2015; Stevens et al., 2003; Wood et al., 2011). However, most global models do not represent accurately the horizontal and vertical extents and frequency of these cloud regions (Klein et al., 2013; Su et al., 2013; Xiao et al., 2014), although some decadal trends do appear to be correctly represented (Norris et al., 2016). Likely the shortcomings of climate models in representing clouds reflect the limitations on gridbox size and available variables, which are limited by computing power (Schneider et al., 2017b). Innovations are needed for improved parameterizations that specifically target persistent low stratocumulus in upwelling regions. Several approaches have shown promise, including 2-D simplifications (Jones et al., 2019), statistical representations (Chinita et al., 2018; Kawai and Teixeira, 2012; Wu et al., 2020), and adjustable gridding with embedded LES (Schneider et al., 2017a). Other approaches using observational test beds and combined measurement studies are needed. Testing whether the process-based knowledge that we have obtained from these earlier studies is sufficient when incorporated in global models requires a sufficiently long and accurate measurement record to provide statistical overlap. The detailed characterization of the full annual cycle of clouds and their properties is the first and most basic objective that will fulfill this need for global climate models, some of which can be verified with existing satellite records, but providing accurate measurements of cloud vertical extent and more detailed radiative properties, in addition to characterizing the range and frequency of regional precipitation that occurs, would require in situ measurements. Clouds simulated by models should be evaluated in relevant regions and seasons to assess the following relationships:
- What model development is needed for the simulated variability in cloud fraction, rain and drizzle frequency, and intensity in the marine stratocumulus clouds to represent what satellite and in situ observations show?
- What are the key simulated large-scale meteorological and radiative factors that cause marine stratocumulus clouds to form and persist, and how may the availability of these clouds for MCB change in a world with higher concentrations of GHGs?
- How does the parameterized contribution of turbulence change stratocumulus structure and susceptibility to brightening and precipitation?
Aerosols. In order to predict the response of adding aerosol particles to clouds, models must first correctly represent the size, concentration, and properties of particles that are already present in the atmosphere. Ongoing efforts for air quality and climate change provide initial validation of many of the major features of aerosol concentrations over continents and particularly in urban areas, which have ongoing monitoring in most developed regions. However, there is a lack of in situ monitoring in ocean and remote regions, as these areas are not of concern for human exposure to particulate pollutants. Consequently, it is not surprising that there are substantial uncertainties and sensitivities to natural marine CCN sources (Burrows et al., 2018; McCoy et al., 2015; Wang et al., 2018), meaning that to reduce uncertainties in indirect effects in ocean regions, we must be able to better quantify the marine CCN budget at background and urban-influenced conditions (Lohmann and Feichter, 2005; Twomey, 1977). While models are needed to identify which processes contribute to aerosol uncertainties, quantifying the relevant processes requires substantial observations in order to characterize the variety of aerosol sources (Reddington et al., 2017). Recent work has provided improved seasonal quantification of CCN budgets in the North Atlantic (Croft et al., 2020; Sanchez et al., 2016, 2017b, 2018; Zheng et al., 2018), but this region does not have as much continuous stratocumulus coverage and evidence of persistent ship tracks for MCB since the stratocumulus are more short-lived and synoptically driven. Similar evaluations of measured and modeled aerosol budgets and concentrations that target the northeastern Pacific, southeastern Pacific, and southeastern Atlantic are needed to address the following types of questions:
- What processes and emissions need to be improved to represent the observed seasonal frequency and relative contribution of background and manmade aerosol particles in these regions?
- Are the simplified model representations of photochemical oxidation, cloud processing, and other physical-chemical interactions sufficiently well represented to predict CCN?
- How well do climate models predict aerosol properties relevant to CCN activation (aerosol amount, size distribution, composition, and hygroscopicity) and their associations with different air masses in these regions?
Interactions. If the cloud and aerosol simulations of models are realistic when considered separately, then it makes sense to assess the processes by which they interact. Here the evaluation includes the interaction of two complicated aspects that cannot be explicitly calculated in climate models: the microphysics and the turbulence. We expect that to some extent both of these aspects are included in simulated clouds to begin with and hence can be verified to a large extent by comparison with observations. However, these aspects influence both the radiative changes in clouds that affect temperatures and the feedback processes of the clouds that affect lifetime, and this causes a number of additional issues for introducing MCB-like new perturbations that may include conditions not represented by past observations:
- Which aspects of model errors matter most to the cloud properties that are most important for MCB?
- What is the role of in-cloud microphysics and entrainment and detrainment in changing the drop distribution? Do these processes affect the cloud lifetime?
- Can we separate the roles of aerosol, meteorology, and radiation in determining changes in cloud properties (including cloud droplet number, liquid water path, precipitation rate, boundary layer depth, decoupling, and diurnal cycle) (Gryspeerdt et al., 2016, 2017, 2019b)?
- To what extent does adding aerosol change the formation and cycling of precipitation, and is that effect accurately represented in models? Does the aerosol affect drizzle fluxes from the cloud layer, and are these processes included accurately in models? Can models represent the redistribution of drizzle and the resulting impacts on heat fluxes in the sub-cloud layer?
- Do models initialized with the measured aerosol properties reproduce the observed aerosol cloud interactions along Lagrangian tracks (Christensen et al., 2020)?
- How much do giant CCN and turbulence contribute to droplet spectral broadening, and is this effect suppressed by MCB (Feingold et al., 2002; Witte et al., 2019)?
All three of these areas of model development require both satellite and in situ measurements to ensure first the accuracy and completeness of particle and drop distributions and air motion spectra provided by in situ observations and then the extension of those properties by tying to improve satellite capabilities. Multiseason and multiyear surface observations in ocean regions are required to provide the range of background conditions in regions where MCB may be implemented.
Then controlled-release experiments can be used to test model behavior and assess verisimilitude.
If climate models can be developed that represent MCB accurately, then they provide important tools to assess the impacts of MCB on regional climate and ecosystems. Climate models could then also be used to design experiments to test whether those impacts are well represented. Addressing questions related to MCB impacts requires a series of studies that can be organized under the following research questions:
- How does the (resuspension and) deposition of salt particles impact downwind ecosystems and communities? Will deposition affect soils, rainwater, and vegetation?
- Will the geographic localization of radiative cooling have unexpected, unintended consequences for rainfall, temperature, or other climate variables that could harm vulnerable communities?
- Will downwind communities have costs associated with additional salt deposition and removal?
- Will local or regional cooling, or teleconnections, affect crops or other livelihoods?
The open questions that require better ongoing and targeted observational studies are those of cloud distributions and types, associated precipitation and other deposition, and the susceptibility of specific ecosystems. For this, networks of observations could provide the long time series of observations required to constrain models and evaluate their performance.
Some critical steps forward to advance this research cluster (for MCB) include the following:
- Prioritize coordinated observations and modeling that quantify and constrain the effectiveness of brightening. These efforts will likely be most efficient and productive if they include intentional atmospheric perturbation studies (controlled emission experiments). But these can be done on small scales that do not detectably alter climate variables (e.g., temperature, precipitation, and global mean forcing) (see Section 6.3 on considerations for outdoor experimentation).
- Target geographic regions that are most likely to be effective for MCB (e.g., persistent stratocumulus cloud decks covering large fractions of the northeastern Pacific, southeastern Pacific, and southeastern Atlantic rather than regions that lack persistent stratocumulus coverage, such as the tropical western
- Pacific and North Atlantic). Research should include efforts to track and predict expected changes in cloud coverage, extent, and susceptibility.
- Pursue, for the near term, modeling studies at the scale of LES, parcel and column models, and nested regional models—all of which can help inform the improvement of climate model parameterizations. Pursuit of global-scale MCB modeling will be more useful after climate models are further developed on several key fronts: to better represent Earth’s current cloud cover, to better quantify the uncertainties and feedbacks associated with perturbing cloud processes, and to provide a more accurate estimate of how changes in aerosol will alter climate. Tie modeling at all scales to observations, with the evaluation of new parameterizations for climate models based on satellite and in situ measurements.
Observational Needs. These research needs require improved capabilities and availability and support of observational facilities including aircraft, satellite, ship, and ground-based. Such improvements would be of value for both SG and broader climate change research, as progress in both suffers from a need to better understand marine boundary layer cloud processes and feedbacks. Existing ground-based observational networks (which focus largely on monitoring gas-phase atmospheric composition) with substantial enhancements in instrumentation and geographic coverage could serve to verify the climate-relevant aerosol and cloud properties produced by models. Lidar technologies (based on ground, satellite, and aircraft platforms) could likely be used to allow tracking of aerosol plumes and cloud structure, but the absence of quantitative calibrations will mean that they are only useful when validated by in situ observations. To be more useful for SG research, existing observational resources should be expanded to better monitor in situ and remote properties of cloud and aerosol number distributions, their spatial and temporal evolution, and multiscale properties, including the following steps:
- Research aircraft should be equipped with instrumentation for comprehensive boundary layer measurements of aerosol and droplet size distributions and composition, turbulence, and radiative fluxes.
- Satellites should be designed to measure cloud and turbulent properties at minimum 100 m resolution in the lowest 1 km of the atmosphere to allow in situ results to be extended to broader regions.
- Research vessels should be modified to accommodate and supported to collect continuous in situ and remote aerosol and cloud properties so as to facilitate multi-month open-ocean studies of aerosol and cloud properties.
- Ground networks should be enhanced and expanded to provide coastal measurements of stratocumulus properties and extent in the northeastern
- Pacific, southeastern Pacific, and southeastern Atlantic, incorporating lidar and balloon measurements of the vertical extent of cloud altitude, water, and frequency as well as aerosol, for comparison to climate models.
Cirrus Cloud Thinning
CCT is currently the most uncertain of the three methods considered here. Model predictions of how this form of intervention could affect climate outcomes vary widely, with some indicating minimal effects and some showing the ability to produce negative radiative forcing (see Chapter 2). Most studies agree that the uncertainties are driven by a lack of knowledge of the nucleating conditions that are present for the existing global distribution of cirrus clouds. The different and yet all very plausible assumptions made about these conditions produce the wide range of climate outcomes.
Until some of this fundamental uncertainty is resolved by improving our observations of cirrus clouds (addressing the types of questions listed below), we see relatively little value in research investments aimed at global simulations of how the climate system would respond to this form of intervention. It would similarly be premature to explore technical feasibility and costs of this approach (which are likely to be less of a challenge than for SAI owing to the lower altitudes and smaller payloads required). Nonetheless, because CCT would act on outgoing longwave radiation rather than incoming shortwave radiation, it could have significant advantages relative to either SAI or MCB in terms of avoiding potential adverse effects on the hydrological cycle, depending in part on the deployment scenario. Thus, despite its relatively higher uncertainty (perhaps attributable to the lack of much research to date), CCT should still be considered an important element of a complete research agenda.
Some critical steps forward to advance this research cluster (for CCT) include the following:
- Expand observations to better constrain how often cirrus forms and the current distribution of homogeneous versus heterogeneous cirrus formation. How much of the natural cirrus forms on ice nucleating particles? This will require a combination of in situ aircraft observations (e.g., ice crystal size and number concentration) and satellite observations (overall coverage).
- Compare and constrain climate model parameterizations to ensure that models can reproduce the current range of observations of homogeneous and heterogeneous nucleation.
- Provide additional constraints for model parameterizations of ice nucleation
- schemes, perhaps through a combination of cloud-chamber experiments to test different ice nucleating particles and validation with in situ observations.
- After improvements have been made in the areas above, conduct research to assess the feasibility of realistic implementation strategies. (Is it possible to identify regions or seasons where cirrus is consistently formed through homogeneous freezing? Is it possible to develop seeding strategies that avoid introducing new cirrus in places where there is supersaturation but no existing cirrus?)
 Climate Response:
Assessing how different SG approaches would affect key climate outcomes.
One of the central goals of SG research is to predict how the climate would respond to a hypothetical deployment. The current state of scientific understanding about possible climate responses to different SG approaches was assessed in Chapter 2. In general, studies to date indicate that SG interventions would decrease globally averaged temperature and precipitation, but regional effects are less clear, and such interventions may alter the ocean and atmospheric circulation in unique ways.
Climate models are the critical tool to assess large-scale climate responses associated with SG intervention strategies. Many early SG climate simulations simply “turned down the sun” as a proxy for SG (Kravitz et al., 2011), but the climate response to any specific approach (SAI, MCB, CCT) will differ from such idealized simulations and will depend on the method, spatial distribution, and magnitude of the intervention strategy employed. There will also always be uncertainty in the predicted climate response; thus, research needs to not only estimate the “best guess” response but also explicitly attempt to characterize the degree of uncertainty. Uncertainties in the climate response to SG result both from uncertainties in representing SG-specific atmospheric processes (described in the previous section) and from some of the same shortcomings that limit our understanding of the response to other climate forcings, such as the regional hydrological response to increasing concentrations of GHGs. There is also uncertainty in projecting the climate response due to climate change alone without SG, and for some processes the overall uncertainty in future climate projections might be smaller with SG than without it.
Work is required to further improve the ability of climate models to assess the climate response to SG, especially in terms of robustly representing key climate processes. As discussed in the previous section, it is well understood that adding aerosols to the lower stratosphere will produce surface cooling, but uncertainties in the climate response to SAI arises from how well different models capture the resulting changes in
stratospheric water vapor concentrations, changes in the stratospheric circulation with subsequent links to the tropospheric circulation, or details of the radiative properties and chemical effects of the aerosols, among other factors. The ability of models to predict the climate response to MCB is even more limited fundamentally because how aerosols interact with clouds locally as well as regionally is a major uncertainty. Presently, for instance, it is unclear whether global climate models simulate low clouds that are too susceptible to aerosols and thus overestimate their potential cooling effect, or whether the models are correctly estimating the aerosol cooling efficacy of low clouds but for the wrong reasons. Thus, assessments to date of the effectiveness of MCB in climate models are unable to determine the efficacy or impacts of this type of SG.
Global climate models include parametric representations, called “parameterizations,” that are designed to include the transports of energy, momentum, and other quantities by the unresolved or “subgrid scale” motions of the air and water, as well as by radiation and precipitation. Many of the uncertainties described in the previous section that are important to address in order to accurately predict the climate response to SG relate to subgrid-scale climate processes. Despite decades of research on this front, current parameterizations are still problematic.
Today, however, continuing increases in computer power are making it possible to replace some problematic parameterizations with explicit, smaller-scale processes. For instance,“cloud-permitting” or “storm-resolving” global models have much more realistic simulations of clouds and precipitation systems (Stevens et al., 2020), but their grid spacing is still not fine enough to allow detailed simulations of individual large clouds or of the thin boundary layer clouds targeted by MCB. In particular, the balance among radiative heating, turbulent mixing, and cloud microphysics represents a challenge even for the application of very fine-scale simulations, and there are still known deficiencies in their representation. Nonetheless, numerous studies have shown that global storm-resolving models are able to realistically simulate important atmospheric processes that lower-resolution models miss (e.g., Stevens and Bony, 2013). Such high-resolution global models, however, present an enormous computational challenge and have not yet been used to study SG.
For SAI, validation of climate responses with observations after volcanic eruptions provides some basis for confidence in using global climate models to assess the response to deliberate injection but with uncertainties, as described earlier. Evaluating effects of subgrid-scale mixing (e.g., at the scale of the “plume” released behind an aircraft) is an important next step for SAI research, and this could also be aided by the development and application of higher resolution models. Modeling of stratospheric chemistry and transport to date has been dominated by coarse-grid climate models. Yet observations
of rocket emissions indicate that plumes can remain as coherent structures for weeks or longer in the stratosphere. Other studies have shown that chemistry in aircraft plumes is misrepresented at the grid scale, which can result in significant errors in the estimated impacts of aviation on atmospheric composition. Considering these findings together, work is needed to ensure that plume-scale effects are correctly represented in SAI studies as described elsewhere in this chapter.
Overall, climate models are an extremely useful tool to examine the climate response to SG; however, they are imperfect. Two relatively new approaches to target research questions specific to clouds and aerosols and their representation in models are: (i) constraining to specific sets of observations that provide a more explicit way to ensure factors such as aerosol distributions are realistically represented in models (e.g., Tunved et al., 2006, 2013); and (ii) separating the processes to which specific effects can be attributed and allowing model improvements to focus on those processes that are most deficient (Ghan, 2013).
Some critical steps forward to advance this research cluster include the following:
- Use climate models to establish better estimates of the uncertainties in regional climate responses to SG interventions and assess how much those uncertainties can be reduced through research.
- Model-based research should incorporate observational constraints to provide a path toward more realistic simulations.
- Model processes should be investigated individually and tracked so that specific deficiencies and inter-model differences can be identified and improved.
- Develop more realistic climate model scenarios that explore the range of possible SG strategies and explore how SG forcing differs from other anthropogenic climate forcings (as well as exploring their individual and combined climate responses). Modeling approaches should consider the following:
- The utility of large ensembles in order to quantitatively document the irreducible uncertainty in climate response arising from unforced natural (or internal) variability.
- Framing projected responses in the context of the full probability distribution of possible outcomes (as opposed to only the best-estimate response) and in the context of different SG implementation scenarios and strategies.
- Enable the representation of MCB in global climate models, in particular through the following:
- Simulations with observationally constrained or process-tracked models at
- global and smaller scales to provide process-specific information needed to interpret observations and predict future scenarios.
- Improved parameterizations to better represent low cloud distributions globally, seasonally, latitudinally, and vertically, with cloud properties that reflect observations.
- Incorporation of realistic causal links between cloud drop number concentrations and aerosol particle size distributions, which show the sensitivity and limitations of number enhancement.
- Improve representation of SAI in global climate models.
- Explore whether global aerosol optical depth (AOD) distribution is significantly affected by plume-scale effects for a single given scenario; by subgrid-scale changes in the injection strategy (e.g., flight paths).
- Examine how the accuracy of climate model simulations of SAI is limited by grid resolution. (e.g., Do we need to parameterize our plume models, rather than just inject uniformly in a gridbox? Are nested grids needed to represent plume processes? What spatial resolution is needed to faithfully represent the radiative forcing and impact outcomes?)
- Evaluate the trade-offs in computational resources and simulation accuracy between grid resolution and aerosol representation. Enable possible future representation of CCT in global climate models through model development efforts.
- Models need to correctly capture the distribution of homogeneous versus heterogeneous freezing conditions.
- Parameterizations of cirrus-aerosol interactions and of UT vertical velocity may need improvement.
- Address observational needs for improving and evaluating climate models.
- Long-term observational networks generally provide the most significant constraints on climate model performance because long time series of data are often required to constrain models and evaluate their performance. While ground-based observational networks cannot address all of the needs referred to in the “Atmospheric Processes” section, they can provide validation of aerosol loadings and distribution of clouds through measurements that include (i) a long-term stratospheric aerosol and trace gas measurement program that maintains or enhances current space- and ground-based measurements of temperature, ozone, aerosol, and trace gas stratospheric profiles; and (ii) a long-term coastal aerosol-cloud measurement program to provide ground-based measurements of cloud, aerosol, precipitation, and radiation properties that target stratocumulus clouds in MCB-susceptible regions..
- The timely transfer of information from process and observation studies into climate and Earth system models is critical. The “Climate Process Team” (CPT) concept4 could help address the modeling needs specific to SG strategies, as key processes (e.g., stratospheric transport, cloud microphysics, aerosol indirect effects, subgrid scale mixing) could be targeted with this approach.
 Other Impacts:
Assessing the potential environmental and societal impacts of SG intervention strategies.
SG interventions are designed to alter global or regional climate, which can affect numerous environmental factors such as atmospheric and sea water temperature, precipitation patterns and intensity, extreme events (e.g., heat waves, droughts, and hurricanes), sunlight intensity and quality, ocean acidification, and nutrient mixing. Changes in any of these factors can in turn affect the magnitude and distribution of risks posed to biodiversity, ecosystem services, and human well-being. For example, changing temperatures and precipitation patterns will affect the distribution and productivity of terrestrial vegetation, ocean primary production, and crop production, as well as the abundance and distribution of organisms and the health of critical biological habitats such as coral reefs and tropical forests; changing quality and quantity of solar radiation can affect the efficiency of plant growth and solar energy production; and exposure to increased UV radiation from loss of stratospheric ozone can increase human health and ecosystem risks. And as discussed in Section 2.2c, the underlying challenge is to understand whether SG interventions would alleviate, or would make worse, the impacts on all of these systems stemming from climate change alone.
The uncertainties in climatic responses to SG intervention (discussed in the previous research cluster) limit our understanding of the cascading impacts on associated ecosystems and their goods and services. Existing global climate and Earth system models can estimate the coarse-scale distribution and magnitude of some direct climate effects, and these estimates have been applied to examine the potential effects of SG interventions on terrestrial vegetation, but there are substantial gaps that limit
4 See https://usclivar.org/climate-process-teams. A CPT can be defined as a funded multi-institutional project that assembles observation-oriented experimentalists, process modelers, process diagnosticians, theoreticians, and climate model developers from two or more modeling centers into a single project that focuses on a specific process (or set of processes) to assess model sensitivities to process uncertainties; establish observation and model metrics; and develop, test, and implement parameterization improvements. CPTs provide effective mechanisms to facilitate close collaboration and enduring links between process experts and model developers, thereby accelerating scientific understanding of key physical processes and leading to improvements in their representation in climate models.
our ability to use such models to estimate impacts in many other areas—including, for instance, the cryosphere and ocean biogeochemistry. The coarse resolution of projected climatic responses to SG interventions renders it difficult to assess impacts on natural and human systems at the finer spatial scales that are most relevant to decision making.
Moreover, SG analyses to date have largely focused on a limited range of climatic variables—temperature and precipitation. While some impacts depend in a fairly straightforward manner on these variables (e.g., human mortality can be directly affected by extreme heat conditions), many impacts of concern depend on concurrent changes across numerous climate variables (e.g., agricultural productivity can be affected by temperature, precipitation, humidity, and solar radiation levels, as well as atmospheric CO2 concentration, which in turn will depend upon how the emissions scenario is being applied in a given study). Adding to these challenges is the fact that many SG impacts will depend upon the particular type of intervention, on the manner of its deployment, and on how much cooling is exerted, and the fact that impacts can be affected by individual and societal responses to the changing environmental conditions and by the widely varying scenarios in which SG development and deployment could unfold (see Research Cluster 1).
Due to these current limitations, there has thus far been very limited research on the impacts of SG interventions on environmental and human health. Much of the existing work is based on extrapolation from known responses of ecosystems or health risks to climate-related drivers, using simplified scenarios of SG deployment. The research proposed under this cluster aims in large part to simply advance approaches for how to effectively investigate these sorts of impacts. The needed research approaches range from detailed mechanistic studies of impacts on specific ecosystems or sectors to broader integrated studies of how different types of impacts and risks may be distributed across populations and geographic regions.
Some critical steps forward for this research cluster include the following:
- Explore the effects of SG interventions on a broader range of climatic and biogeochemical variables that are relevant to social-ecological systems, including studies carried out at high enough resolution to inform understanding at regional and local scales and including a fuller range of SG deployment scenarios. Advance integrated system modeling and assessment approaches that improve our understanding of the possible distribution of benefits and risks from SG impacts.
- Include a broader range of social-ecological systems in SG-related studies, for instance, encompassing coastal, ocean, and cryosphere ecosystems and
- human-managed ecosystems such as agricultural and fisheries. Include better linking among radiation, land and ocean components of models, and tracking changes in direct and diffuse radiation in order to assess effects on photosynthesis in crops, vegetation, and phytoplankton. Such research may include studies of historical analogues and mesocosm experiments5 along with modeling studies.
- Explore the economic impacts of SG on production processes and key inputs to those processes (e.g., agricultural irrigation, labor participation, capital flows, and land quality), trade and commerce (e.g., international trade and global supply chains), and demand for goods and services, as well as impacts on aggregate economic indicators (e.g., gross domestic product and income distribution).
- Advance downscaling of climate and ocean projections under SG scenarios and model representation of cloud and precipitation processes (which drives regional representation of temperature and precipitation changes that affect wildlife and human habitats). Extend regional observations of climate change-related temperature and precipitation changes (including related factors such as extreme weather and changes in direct and diffuse radiation) to provide the long-term trend data needed for quantifying population responses to these changes (and other epidemiology-like research approaches).
- Advance networks of co-located observations of multiple relevant environmental variables (e.g., sites that collect observations of temperature, precipitation, humidity, and chemical- and radiative-atmospheric variables) to facilitate population-specific impact studies—given that populations may be affected by combinations of any of these variables.
- Study impacts of specific proposed SG aerosol chemical components on ecosystems and human health, including laboratory studies of population-specific dose-response effects and studies at the levels that might actually be required for deployment. Conduct small trials that examine how different types of candidate SG particle composition affects tissue samples and plant analogues (or other related epidemiological- and ecosystem-impact studies). Any outdoor deliberate release experiments should at a minimum include monitoring of potential exposure to provide evidence of in situ effects.
5 This refers to bounded, partially enclosed outdoor experiments that are used in environmental science to bridge the gap between laboratory studies and the real world.
 Monitoring and Attribution:
Designing an observational system (and understanding its limitations) for detecting, monitoring, and attribution of SG deployment and impacts.
Research is needed to understand the requirements of a monitoring system for analysis of SG technologies deployed at climate-modifying scales. The goals for such a system would be (i) to diagnose unexpected deployment (in the absence of international consultation and cooperation); (ii) to provide observations needed to tailor, adjust, or cancel SG interventions following deployment; and (iii) to understand the broader global effects of deployment.
One key question to be considered in the design of an observational system is: If deployment were pursued unilaterally, how do we know this deployment is happening? Any deployment at scales intended to alter the climate would likely be detectable within a short timescale (weeks to months), given the size of the effort needed to affect such a change. For example, for SAI, the large increases in AOD would be obvious from numerous existing sensors. A robust monitoring system would also improve understanding of the aim and approaches of the actor(s) involved.
Some components of an SG monitoring system would share attributes of the observational approaches needed for SG research activities. This includes, for instance, the suite of in situ and remote sensing capabilities proposed herein for study of SAI (e.g., rapid response to volcanic emissions) and MCB (e.g., in situ sampling of cloud aerosol interactions and their radiative forcing impacts).
The 2017 Earth Science Decadal Survey (NASEM, 2018a) recommended a number of space-based observation capabilities in support of the report’s proposed program. Of the proposed observing system priorities, the “Designated” Aerosols and Clouds, Convection, and Precipitation missions would be highly useful for MCB research, and of the “Earth System Explorer” class, the Ozone and Trace Gases mission would be most useful for SAI research. These missions would not advance in time to actually contribute to the initial years of the research program recommended herein, but when these new observations do become available (likely in the 2025–2035 period) they will eventually provide helpful data in support of SG research.
A broader SG monitoring system centered on space-based remote sensing observations and associated modeling needs to be developed prior to considering deployment. There are typically long timescales involved in the development of needed observational instrumentation; thus, research is needed now to define the requirements for such a system and to estimate the efficacy, cost, and development schedule.
To enable such developments, there is a need for research to evaluate the potential for (and limitations of ) our ability to attribute changes in the environment to SG deployment. For instance, the ability to diagnose radiative forcing changes from an SAI or MCB intervention using existing spaceborne radiometer instrumentation could be relatively straightforward for large-scale interventions but much more challenging at smaller scales, where induced perturbations may be difficult to detect amidst natural variability. For any type of intervention, diagnosing and attributing climate impacts is likely to be very challenging, because many of these impacts will evolve over long timescales and will be difficult to separate from natural variability.
Some critical steps forward to advance this research cluster include the following:
- Determine what variables would provide the earliest and highest signal-to-noise signals that could assist in attribution.
- Explore approaches to improve the signal-to-noise in such observables to reduce the time needed for attribution (such attribution studies should explicitly consider the importance of natural climate and geophysical variability).
- Advance critical observational systems and infrastructure for long-term monitoring of stratospheric and lower atmospheric composition (as described in the previous sections “Atmospheric Processes” and “Climate Response”) and incorporate the following:
- Aircraft, balloon, and ship facilities for calibration/validation of satellites and to provide a broader suite of observations needed to diagnose impacts.
- Capability to monitor the diffuse and direct solar radiation at Earth’s sur- face to aid the study of biological impacts.
 Technology Development and Assessment:
Addressing the science and engineering issues regarding SG implementation related to hardware, materials, and infrastructure underlying SG research.
As discussed in Chapter 4, the proposed research program does not include the goal of supporting technology development that is specifically oriented toward building the capacity for SG deployment. Yet the development of some specific technology capabilities is needed to advance fundamental understanding of particular scientific questions proposed in this research agenda (in particular the “Atmospheric Processes” cluster) or to better understand the technical feasibility challenges of particular approaches. This line between technology capability for research and technology capacity for deployment, for both SAI and MCB,6 is discussed below.
6 CCT research remains sufficiently immature as a concept that the capabilities needed have not yet been documented, but they are unlikely to be as challenging as either MCB or SAI deployment.
For SAI, relevant questions include whether and how one could deliver a useful payload to a sufficient altitude, and what is a reasonable estimate of the economic and other costs for doing so. As described in Chapter 2, studies indicate that aircraft are likely the cheapest delivery option, and there is strong evidence that delivery at ~20 km can be achieved with purpose-designed aircraft (Bingaman et al., 2020). An altitude of 20 km would be sufficient to achieve cooling, but deployment at higher altitudes offers the benefit of significant reductions in the amount of material required and thus reductions in some associated impacts. While altitudes as high as 25 km have been assumed in some recent climate model simulations (Kravitz et al., 2019b; Tilmes et al., 2018a), there has been essentially no exploration of how material might be lofted this high. Understanding how engine and airfoil design choices alter chemistry and physics in the nearfield plume would also be important.
There can also be engineering effort required for aerosol delivery itself. It is not expected that there are any significant challenges to injecting a gas such as SO2 directly into the stratosphere; however, direct injection of sulfate or alternative aerosol particles will likely require additional capabilities (e.g., to disperse solid aerosols). These injection techniques have not been well researched in part because understanding the detailed technology needs will depend on the outcome of microphysical research (discussed in the earlier “Atmospheric Processes” section).
There are no obvious additional engineering challenges associated with the remainder of the SAI delivery system. This approach would require basic infrastructure, such as runways, but no novel challenges that motivate near-term research; although once likely aerosol precursors emerge, additional study may be warranted on issues such as large-scale extraction and processing efficiencies for these materials. From a “life-cycle impacts” perspective, it is worth noting that construction of new aircraft fleets will require energy and other resources and that flying fossil fuel-based aircraft will emit CO2 and NOx.
For MCB, the primary question is the capability to produce salt particles of an appropriate size distribution that can be lofted into, and serve as nuclei for, boundary layer clouds. MCB deployment would also require the development of appropriate ships (or other delivery approaches) with capacity to produce and distribute aerosol. The aerosol composition most likely to be employed is salt (NaCl), available either from seawater or dissolved from a bulk supply. If the dispersal method used requires extracting salt from seawater, then the ship must have facilities for filtering and processing large volumes of water for this extraction process. Relevant technology is already in use at desalination facilities, but the scale-up and at-sea implementation will require some development. To date, there has been some engineering development of the nozzles that would be required to produce salt spray with appropri-
ate size distribution—this has been tested in a laboratory setting and, recently, outdoors.7
At this stage, we do not recommend for two reasons any large-scale research on detailed designs or prototypes of the engineering hardware that would be required for deploying either SAI or MCB. First, developing detailed designs for deployment now would justifiably raise public concern that the research program was going beyond its stated purpose to solely inform future decisions about deployment. Second, detailed designs are premature, given that many technical requirements will depend on the outcomes of research.
Nonetheless, there are several reasons why a research program should include small investments in understanding the engineering of deployment capability:
- Such efforts could provide insights needed to assess whether or not particular intervention strategies are technologically and/or economically feasible. If it is found that deployment of particular strategies is infeasible, then there is no reason to conduct any further research. (In other words, sufficient effort is needed to know whether proposed capabilities are possible but not to go further toward developing deployment capacity.) Initial studies will also better identify the “lead time” for technology development (i.e., how long it would take to develop the necessary hardware).
- It is also essential to understand the engineering challenges sufficiently well to influence the range of options considered in more basic scientific research. For instance, for SAI, if the projected costs make delivery to the stratosphere at 25 km extremely unlikely, then climate research should prioritize understanding the implications of injection at lower altitude. Similarly, if dispersing solid aerosols were found to be far more challenging than expected, that might suggest deprioritizing further research on this front.
- Some development of specific capabilities may be necessary simply to enable scientific experiments. For instance, for MCB studies, there will be a need for spray nozzles that can produce a particular range of aerosol size distributions. For SAI, even small-scale tests of solid aerosols will require some dispersal capability. We do not foresee any near-term need for larger-scale SAI experiments that would require delivering a payload large enough to warrant developing new capacity (i.e., it is likely experiments could be conducted using existing platforms for lofting material to the stratosphere). To avoid concerns over research representing a “slippery slope” toward deployment, simulta-
7 See https://www.scu.edu.au/engage/news/latest-news/2020/scientists-trial-world-first-cloudbrightening-technique-to-protect-corals.php.
- neously developing the capacity to deploy as part of conducting scientific experiments is not recommended.
- In principle, a cursory understanding of deployment technology might inform both scenario development and governance through better understanding of what actors would be capable of deploying and in what time frame. For example, in addition to adequate financial resources, is there a barrier to SAI deployment through access to specialized aerospace capability, or is the capacity sufficiently generic to be accessible to anyone with adequate resources? An example of research in this area is the question of what radiative forcing could be achieved through widely distributed individual balloon launches.
Some critical steps forward to advance this research cluster include the following:
- Conduct design and costs estimates for aircraft to deliver payload at altitudes up to 25 km (SAI).
- Research dispersal requirements for solid aerosols to better assess the viability of these options (SAI).
- Continue to advance nozzle design by improving understanding of the optimal properties of the particle size distribution needed for efficient nucleation. In the near term, focus on small-scale prototype design, testing, and control for the range of size and composition of particles that would be needed for laboratory- and outdoor-based research (MCB).
- Improve understanding of the boundary layer dynamics and the conditions under which particle emissions may require added heat to overcome limitations in lofting of particles and mixing to cloud level (MCB).
Efforts to advance these technical capabilities to conduct SAI experiments, and similarly the efforts to advance MCB dispersion nozzle design, would be focused on facilitating the “atmospheric processes” research discussed earlier in this chapter not providing pathways toward deployment. By focusing the technology-related work on these critical research questions, one is likely to reduce the potential for mission creep toward developing deployment capability.
 Public Perceptions and Engagement:
Understanding public perceptions of SG and advancing effective societal engagement strategies and incorporation of resulting insights into a broader SG research program.
The importance of understanding public perceptions of and responses to SG activities, and developing effective means of public engagement to inform decision making over SG research and research governance, has been discussed earlier in this report and highlighted in numerous previous publications:
- The U.K. Royal Society Report (Shepherd, 2009) noted,“The acceptability of geoengineering will be determined as much by social, legal, and political issues as by scientific and technical factors” and recommended that “geoengineering research… should not proceed in the absence of a wider dialogue between scientists, policy makers, the public and civil society groups.”
- Corner et al. (2012) note,“Questions about the morality of intentional manipulation of the climate, the sociopolitical implications of nation-states embarking on programs of geoengineering, and the requirement for responsible innovation and governance are not issues that scientists can easily address.” Such decisions involve both scientific knowledge and social values and can benefit from “collaborative, broadly based, integrated, and iterative analytic-deliberative processes” (NRC, 2008).
- Flegal et al. (2019) note,“Public engagement is widely regarded as important for geoengineering governance, largely for normative and instrumental reasons. The substantive rationale—that public engagement can improve the content of geoengineering research itself—is underappreciated.” (According to the normative rationale, broad publics should have opportunities for input on SG research, since these technologies have global reach and may affect people around the world; the instrumental rationale holds that public engagement with SG research may reduce conflict and controversy.)
- The NRC (2015) assessment called for “open conversations about the governance of such research” and recommended to “encourage civil society in the process of deciding the appropriateness of any research efforts undertaken.”
Furthermore, research by Burns and Flegal (2015) finds that to avoid “hollow” participatory exercises lacking legitimacy or meaningful impact, there needs to be a direct connection between the outcomes of deliberative processes and relevant decision-making bodies (see also Bickerstaff et al., 2010). They also highlight the insufficiency of public consultations focusing only on nongovernmental organizations and parties with a political or vested interest in particular outcomes, as this approach is not representative of society as a whole and typically fails to represent interests of the Global South. Instead, they suggest the need for nonpartisan, large-scale public deliberative processes that are not run by parties with vested interests in particular outcomes and that are sustained and iterated over time.
There is a small but growing base of research on public perception of SG activities (much of it addressing the types of questions listed below), but much more needs to be learned. Some key observations from the earlier review of existing research on this subject (Chapter 2) include the fact that general awareness of SG in the lay public is low, and the framing of the subject can greatly affect public acceptance and perception. Studies find conditional support for SG research (depending on factors such as the participants’ views on climate change as a problem and the ways that the research is conducted) but much lower support (or outright opposition) to the notion of deployment. This research is “incomplete” in that little work has been done to assess perception of SG among Global South publics, decision makers, or those most vulnerable globally.
Some critical questions to address in this research cluster include the following:
- What constitutes effective practices for “meaningful public engagement” in SG research and research governance?
- What does public engagement lead to in practice for SG research? Does evidence support outcomes in the normative, instrumental, and substantive arenas when public engagement is undertaken in an SG program?
- What levels of public engagement are best suited for different components of the SG research enterprise?
- Who are the relevant publics, and how should engagement take place?
- How do we close the gaps between the critiques and prescriptions raised by public perception researchers and use that knowledge to create improved public engagement processes that support better outcomes for research and society?
- How is perception and framing of SG issues affected by geopolitical and economic contexts and the perception of other climate policies?
- How do populations in the Global South, extremely vulnerable populations, and other less-studied groups perceive SG research and deployment?
- How do cultural worldviews and differing attitudes toward risk affect perceptions of SG issues?
- How do science policy makers, political leaders, and other decision makers view the trade-offs and decision contexts involved in SG research or deployment (recognizing that much of the public perception research thus far has been done with lay publics)?
- How might SG research and implementation interact with other aspects of climate research and policy (e.g., is it possible to monitor for moral hazard effects or to structure SG activities in a way that reduces such effects)?
- How can public engagement be effectively incorporated into the development and planning of SG activities to increase legitimacy, build trust, reduce conflict, and provide accountability?
- How can public engagement facilitate constructive deliberation about justice, ethics, and equity concerns related to SG research and governance, and how can the results of this deliberation be incorporated into ongoing SG research and research governance?
- How can SG research be responsive to various publics, stakeholders, and policy makers’ values, interests, and concerns?
Research is also needed to better understand factors such as the perceptions of those who are most vulnerable to climate change, and the information needs and perceptions of decision makers involved in SG research and deployment (e.g., government funding agencies and other institutions might fund research; those who could play a role in eventual deployment decisions).
 Political and Economic Dynamics:
Exploring the implications of SG for national and international relations and related incentive structures.
Research on the political and economic dynamics surrounding SG research, development, and implementation has evolved (in tandem with natural sciences SG research) through important contributions of political scientists, policy analysts, scholars of global governance, and economists. Yet there remain numerous gaps in our understanding of how SG affects and is affected by political and economic processes and outcomes. This research needs to advance on numerous fronts. For example, IAMs, an important tool for SG research discussed earlier in this chapter (see “Integrated Decision Analysis” cluster), will need substantial input from political science and economics—both at the macro level (e.g., regarding scenario design) and the micro level (e.g., regarding strategic dynamics to be represented in these models).
Research to date has focused largely on idealized strategies for SG governance, but it is also important to examine how dynamics are likely to play out in real-world settings and how to both design practically implementable rules and regulations and incentivize or “nudge” desired practices, standards, and behaviors. This may include studies of “mini-lateral” or “pluri-lateral” clubs of countries engaged in mutual work on SG (see Recommendation 5.1s) short of a full global multilateral agreement, in which countries can agree to common research and research governance exercises, which can then be socialized more broadly. It may include issue-linking, in which mitigation and SG are leveraged to generate an incentive-compatible governance structure.
To date, some research has focused on international relations and interactions, but very little research has considered how local politics and election cycles may affect the creation of SG research programs, deployment trajectories, and their sustainability over the long term. At the international level, there are political studies focused on high-level game theoretical frameworks, but more consideration needs to be given to the real politics and inter-party dynamics of climate change negotiation processes. Any international agreements or other international approaches to governance will require approval and support at the national level; thus, a domestic consensus on decisions concerning research, development, and potential deployment is also required, pointing to the need for research on the critical constraints of domestic policies and politics.
As discussed in Chapter 5, a common dynamic in the creation of international agreements is that first a cluster of leading countries develop national regulations, and then they initiate a process to form an international agreement that approximately mirrors and hopefully improves and extends these national regulations (Morrow and Light, 2019). More work is needed, however, to understand how these dynamics may apply to SG and to understand the incentives required for moving from the current environment of unregulated, largely privately funded research projects to the sort of coordinated national program that is described in the preceding chapter.
The creation of such a program will likely motivate further assessment of what existing domestic regulations and laws could be applied to governance of SG or what new governance mechanisms could be created specifically for this area of research. A critical mass of countries engaging in such exercises would, in turn, increase the likelihood of a concerted attempt at creating global research platforms and global systems of (soft or hard) governance mechanisms.
In addition, as discussed in other parts of this report, concerns have been raised that the interaction between SG and climate change mitigation measures could raise problems of “moral hazard” or “slippery slope” toward deployment. Together with the ethics research related to such concerns (described later in this chapter), economics and political science research can help with finding empirical evidence of the development of these dynamics, tracking the steps that lead to these phenomena, and assessing their actual success or failure at “mitigation deterrence” or technological or economic lock-in. Finally, there is a debate in the political science literature on the very governability of SG, or its very compatibility with democracy at all, that should continue to be discussed (see Horton et al., 2018 and Szerszynski and Galarraga, 2013).
Some critical questions to address this research cluster include the following:
- What dynamics have led to the creation of SG research communities in some countries as opposed to others?
- How has the emergence of these communities affected the development of national research programs or governance systems (including hurdles that have arisen to inhibit creation of research or governance programs and the success or failure of attempts to overcome such hurdles)?
- How do different national models of technology development interact with a country’s broader environment related to perception of climate risks, responsibilities, and success or failure of policy responses?
- What factors have influenced the relative failure of global governance institutions to seriously take up SG to date? What would be required to elevate national-level SG programs and governance initiatives to mini-lateral, pluri-lateral, or international fora?
- What policy frameworks or conditions might accelerate or decelerate activity toward SG at the national or local level (e.g., carbon prices, border adjustments, or other instruments)?
- Are there predictable tipping points with respect to climate impacts that could accelerate or decelerate interest in SG at national or global scales?
- Are different systems of government relatively more or less compatible with broadly considered principles for SG governance (e.g., transparency, accountability, public engagement, etc.)?
Developing effective, adaptive processes and institutions to govern SG activities.
The most pressing knowledge gaps on governance of SG activities are at the international level, where governance institutions are comparatively weak, and cooperation, coordination, and engagement can be difficult to establish.
As noted in Chapter 2, substantial research already addresses how existing law might apply to SG. However, such research has tended to focus on the potential application of existing law to SAI, as opposed to MCB, even though the latter raises distinct issues and might be governed by different treaty regimes (Brent et al., 2019). Moreover, additional research can provide more fine-grained analysis of international legal principles and governance options relevant to specific scenarios that international policy makers might face. Such analysis might inform, for example, a response of the United Nations (UN) General Assembly or UN Security Council to SG field tests with transboundary effects or to unilateral SAI deployment at a global scale.
As discussed in Chapter 2, a number of treaty regimes and institutional settings could serve as loci for formal international governance of SG research. Institutions vary widely in their decision-making mechanisms, adaptability, degree of state and nonstate participation, scientific input, and other features, and further research is needed to analyze the relative strengths and weaknesses of these and other possible institutional settings in the specific context of making international decisions on SG research governance. At the same time, moving too quickly into a consensus-based international agreement may unintentionally create a weak or ineffective governance regime. Alternative governance structures, including options that would defer establishing a foothold in one of the existing international agreements, may be better suited for some types of SG and some phases of SG research and/or deployment, and overlapping governance structures may be appropriate in some instances.
Research on liability and compensation for transboundary harms that could result from SG field tests or deployment has recognized not only the challenges in attributing climate-related harms but also the difficulties in developing a political consensus behind any particular international approach to liability and compensation (Horton et al., 2015). A further exploration of liability and compensation mechanisms, with particular attention to their ethical, political, social, and economic implications, is needed, as is research on the possible application of game theory and other hypothetical scenarios to look at how claims of liability would impact research in the absence of an existing legal regime or agreement.
Past research has noted the importance of expanding developing country participation in SG research and governance (Sugiyama et al., 2017; Winickoff et al., 2015). Considerations of justice argue in favor of a central role for developing countries in SG research and decision making (Rahman et al., 2018). Moreover, joint knowledge production can foster trust, political cooperation, and public acceptance of the resulting scientific knowledge (Winickoff et al., 2015). Relatively little research has examined the adequacy of existing resources for building capacity for SG research in developing countries or mechanisms for expanding that capacity. In addition, research aimed at identifying and addressing governance needs once SG is deployed—assuming that it is deployed—is a subject that warrants additional attention.
A permit requirement specific to SG can help provide oversight of risks, generate information, and serve as a form of social license. Relatively little attention has been devoted to the design of domestic permitting systems specific to research or deployment. Not all SG activities would necessarily require a permit, and some activities may be subject to permitting requirements under laws designed for other purposes. Issues for further consideration in this area include the following: the types of SG activities
that might be subject to permitting, the choice of general versus specific permits, the information to be required of permit applicants, public participation in the permitting process, and the conditions to be imposed on permittees.
Some critical steps forward to advance this research cluster include the following:
- Survey principles of international law that could be relevant to an international debate in the UN Security Council or elsewhere in the face of SG field tests or deployment with transboundary effects.
- Continue to explore existing international conventions, treaties, or agreements and associated governance regimes that could have jurisdiction in the case of SG field tests or deployment with transboundary effects, as well as opportunities for some level of international cooperative governance outside of these existing instruments.
- Study strengths and weaknesses of possible institutional settings for making international decisions on SG research and research governance.
- Study the possibility and ethical permissibility of various approaches to address harm and compensation issues, including harms that may arise with SG field tests with transboundary effects or as a result of deployment.
- Assess the adequacy of existing resources for capacity building for SG research in developing countries and advisability of opening some existing pools of climate finance to SG research or establishing new sources of funding.
- Study the intergenerational implications of SG research, development, and potential deployment, examining, for example, how research, development, governance, and any future use of SG can take into account principles of intergenerational equity, considering intergenerational benefits and burdens, as well as the institutional challenges that would be involved in a multigenerational SG deployment.
- Evaluate the desirability of a permitting requirement for SG activities and possible elements of permit system design.
Incorporating ethics and justice considerations for current and future generations into SG research and research governance.
As discussed in Chapter 2, there is a substantial and growing body of literature on ethics, justice, and equity in relation to SG, and there are important connections between this literature and broader discussions of climate ethics and climate justice. Existing research addresses a range of issues, including whether and under what conditions geoengineering (from research to deployment) would be morally permissible;
whether and how SG could be fair and equitable, considering multiple dimensions of justice (e.g., distributive, procedural, recognitional, and intergenerational); what principles might guide ethical governance of SG; and how to evaluate SG in relation to other climate response options and address interactions between SG and other climate responses.
Early literature tended to consider geoengineering at a general level, frequently addressing carbon dioxide removal and SG together. More recently, ethics research has attended more closely to the specific techniques under consideration and to distinct aspects and stages of research, development, and future decisions to proceed with or abandon SG. Although fundamental questions regarding the moral permissibility of geoengineering remain important, the increased attention to specific geoengineering approaches is welcome because “geoengineering” is not a single, fixed technology; rather, it is an evolving array of ideas that includes not only possible SG technologies themselves, but also various approaches to researching, developing, governing, and making decisions about these technologies and how they might fit (or not fit) into a broader climate response (Stilgoe, 2015).
Research on ethics, equity, and justice can provide a more nuanced understanding of the ethical issues associated with various stages of SG research, from modeling to laboratory and field experimentation, and can help to guide research governance. Ideally, ethics research would be integrated with natural and social science research, so that ethical analyses can both inform and be informed by research on the social and technical dimensions of SG (Tuana et al., 2012). As Tuana et al. (2012) explain,“Ethical analysis is not simply to be put into operation once the scientific and social scientific analysis is completed. On the contrary, ethically significant decisions are often embedded in the scientific analysis itself, as well as in how scientific models represent impacts and vulnerabilities.”
Cross-disciplinary and integrated work that engages ethical issues is already a component of SG research (e.g., Carr and Preston, 2017; Lenferna et al., 2017; Morrow et al., 2009; Tuana et al., 2012), but further research of this kind is needed, because virtually all stages and aspects of SG research and research governance involve normative questions. As Tuana et al. (2012) put it, although much important research on the ethics of geoengineering has taken place already,“what has been lacking is a clear delineation of the ethical issues that must be addressed in the course of scientific decision making about research and testing and the types of scientific knowledge and levels of confidence about models that would be ethically required to warrant responsible SRM [solar radiation management] deployment.” A related point applies to SG governance: research has played an important role in identifying ethical issues associated with
governance and developing ethically grounded governance principles; however, more work is needed to identify and prioritize principles most important at various stages of SG research and development, to propose ways of institutionalizing these principles, and to identify opportunities and barriers for ethical and equitable governance.
The integration of research on ethics, justice, and equity into a broader SG research program could enhance both processes and outcomes, strengthening the legitimacy of research and its governance. Ethical issues and questions associated with different aspects and stages of research, governance, and possible deployment are identified below, along with priority areas associated with each. The critical research questions outlined here emerge from an assessment of existing research and current understanding of key ethical issues. Additional social science research to identify the values, perspectives, and concerns of diverse publics and stakeholders globally should inform ongoing priorities for ethics research.
Some critical questions to address in this research cluster include the following:
Justice and equity issues
- How can SG research take account of the full range of ethical perspectives on this issue? On what issues is there significant ethical convergence (e.g., regarding transparency in research), and where is there significant divergence (e.g., regarding governance of field experiments)? How might disagreements regarding research and research governance be fairly addressed?
- What would constitute fair and ethically justifiable forms of public and stakeholder engagement? What constitute best practices for inclusive engagement in research and research governance at various stages of development?
- What are the ethical implications of the current concentration of SG research, policy, and governance efforts in wealthy countries, and how can existing inequities in research and research governance be addressed? What mechanisms could help to develop capacity for those who are underrepresented (e.g., poorer nations, climate vulnerable communities, and indigenous peoples) to participate more fully in research and research governance? More generally, what steps are need to strengthen and institutionalize equity and inclusiveness in research, development, and governance?
- What are the ethical considerations associated with the potentially uneven distribution of benefits, risks, and harms associated with SG? In developing research models, exploring possible deployment scenarios, and developing SG-related policy and governance, how should distributional considerations be taken into account?
- How can intergenerational ethical considerations be better incorporated into SG research and research governance? How can the social and technical feasibility of SG be evaluated from an intergenerational point of view, and how should risks to both present and future generations be evaluated? What institutions are needed to ensure that research, development, and decisions take account of intergenerational equity?
Ethical issues embedded in SG research
What ethically significant assumptions are embedded in SG models and scenarios, and how might models and scenarios be developed with explicit consideration of ethical issues?
- What ethical values and principles should guide the development and governance of field experiments? How can ethical considerations inform the development and justification of permissibility thresholds for outdoor experimentation? How might ethics guidelines and permitting requirements for outdoor experiments take into account concerns that go beyond just physical effects? What role, if any, should the concept of informed consent play in governing SG field experiments?
- What ethical considerations should guide the development and comparative assessment of various SG approaches and techniques? For example, are there important ethical differences between regional and global approaches? Between MCB and SAI? Between different kinds of possible particles being considered for SAI? Different delivery systems?
- How should risk, uncertainty, and ignorance8 be treated in relation to SG? What are the ethical implications of judging the importance of SG risks based on their estimated magnitude and probability? How might low-probability high-impact risks best be addressed? What role should risk trade-off assessment, the precautionary principle, or other approaches play in research and decision making?
- What core ethical principles should inform development of a code of conduct for SG research, and who should be involved in the development of such a code?
8 See https://heep.hks.harvard.edu/files/heep/files/zeckhauser_presentation_0.pdf.
Ethical issues associated with governance
- Are there central ethical principles that should guide SG governance? If so, what are they, and how can they be institutionalized for research, decision making, and any future deployment?
- From an ethical perspective, to what extent are existing legal and governance institutions adequate to guide and regulate SG research, development, and any possible future use? Where are the gaps, and how might they be filled?
- How can SG research and research governance be structured to build trust and cooperation among nations and to minimize damage to already-fragile relations surrounding international cooperation on global climate change?
- How should issues of potential loss, damage, and liability be addressed in relation to SG? What approaches are ethically justifiable (and why), what institutional mechanisms are feasible, and who should be involved in the development of these approaches?
- What are the central ethical concerns associated with possible moral hazard, technological lock-in, and slippery slope in relation to SG, and how might these concerns be addressed? For example, how could and should these concerns be monitored and assessed in relation to research and development? What institutional mechanisms could be developed to limit the possibility and extent of mitigation deterrence?
Ethics issues associated with SG deployment, management, monitoring, and termination9
- Under what conditions would an international body, individual nation, or other entity be ethically justified in making decisions to utilize SG? What institutions, laws, or processes are needed to enable ethically defensible decisions? What role should consensus, voting, or other processes play in these decisions? What agent(s) or institution(s) would have the legitimacy to make decisions about deployment?
- Could SG deployment be managed ethically and equitably over multiple decades or centuries (in the face of major disruptions such as wars or pandemics), and, if so, what would be required to achieve this? How and to what extent could an SG system be prepared to respond to conflicts, disagreements, and unintended consequences?
- What ethical considerations should inform research and research governance
9 Note that the recommended research on these questions reflects the need to better understand and anticipate ethical issues associated with deployment in order to inform SG decision making. This does not presuppose that SG should or will be deployed.
- planning for the phase-out and termination of SG? What level of agreement and certainty in long-term planning (for monitoring, adaptive management, compensation for harm, and termination) would be required for responsible use of SG?
Research on these questions about ethics, justice, and equity strongly interfaces with other research areas recommended in this chapter—for instance, it can inform and be informed by investigations of SG technical feasibility, social feasibility, and impacts, as well as the development of governance. Much of this research would benefit from interdisciplinary approaches and multidisciplinary research teams.
6.3 OUTDOOR SOLAR GEOENGINEERING EXPERIMENTATION
Outdoor experimentation is currently the most controversial dimension of SG research, posing the largest potential for public attention, concerns, and objections. This stems in part from arguments that outdoor experimentation at a scale large enough to affect regional to global climate is tantamount to actual deployment, and outdoor experiments short of that are legitimizing a road to deployment. For some, these objections are absolute, based, for instance, on fundamental objections to the idea that a small group of people has the right to “tamper with nature” in the absence of broad public input and consent and concerns about unintended consequences, intentionality of researchers toward outdoor experiments of increasing scale and impact, and lack of controllability and reversibility of outcomes.10
At the same time, some scientists involved in SG research argue that some form of outdoor experimentation is essential for advancing understanding of certain core physical processes, and that gaining such understanding will be essential if we are to credibly inform societal decisions about operational pursuit of SG. The 2015 National Academies report noted that small-scale field experiments may be informative and provided a number of conditions that such experiments should meet (NRC, 2015).
Recognizing both the philosophical/ethical and the technical/scientific dimensions of this issue, it is the committee’s judgment that, subject to appropriate governance and oversight, outdoor experimentation could feasibly be pursued in a balanced manner that is sufficient in scale to acquire critical observations not available by other means (see discussion in the “Atmospheric Processes” section of this chapter)
10 For example, see the Climate Action Network’s “Position on Solar Radiation Modification (SRM)” at https://climatenetwork.org/resource/can-position-solar-radiation-modification-srm-september-2019/.
but that is small enough in scale to limit impacts. This judgment is based in part on the recognition that such experimentation can be done at small enough scales that the real-world impacts would be much smaller than impacts of many other deliberate human activities that are freely undertaken by society and the belief that good governance can limit concerns over a slippery slope to deployment. This judgment is also based on concerns that moving too quickly and ambitiously toward outdoor experimentation could induce public objections and subsequent delays or restrictions. Thus, the committee believes that a tempered approach to the initial phase of outdoor experimentation provides the best pathway to a successful research endeavor.
Given the contentious nature of outdoor experiments that involve the release of substances into the atmosphere, all proposed experiments should be subject to the governance described in Chapter 5 (see in particular the permitting system and impact assessment recommended in Recommendations 5.1i and 5.1h, respectively). These governance mechanisms can be important means to limit unacceptable and to enable useful outdoor experimentation. Furthermore, these mechanisms, if designed effectively, will provide a way to ensure that the aggregate of experiments undertaken by different entities do not result in any undesirable impacts.
In addition, the committee considered how to set thresholds for the scale of outdoor experimentation. Such thresholds have been debated in the broader community as a way to provide more clarity about what scale of experiments should or should not be carried out. We agree that such clarity would be helpful in defining material releases that are too large to qualify as research, given current understanding of SG and the societal demand for SG responses to climate change. Based on extensive discussions of the topic, the committee offers proposals for initial thresholds (see below), with the expectation that thresholds may need to be revisited on a regular basis as SG research and research governance advance.
General Considerations for Setting Thresholds for Outdoor SG Experimentation
The committee believes that thresholds for outdoor experimentation should address both the impacts of the potential perturbation on the climate and the impacts of the test materials on the environment. These dual concerns about outdoor experimentation motivate the dual threshold requirements—based on the expected global mean surface temperature change and the mass of materials injected into the atmosphere—that are described below.
The proposed limits are based on the approach of (i) erring on the conservative side and (ii) being sufficient for a variety of experiments that address priority research questions (based on past studies, including analogues). In the committee’s judgment, experimentation at the proposed scale has the potential to provide valuable knowledge (i.e., helping to resolve many critical process-level uncertainties), presenting justification for the small amount of impact risk within and across national boundaries.
A practical challenge in setting and enforcing these sorts of thresholds for outdoor experimentation is that research activities are undertaken and sponsored by multiple countries and other nongovernmental entities. It is conceivable that individual countries could independently conduct experiments in which each experiment individually satisfies the threshold requirements, while leading to an aggregated perturbation that exceeds the thresholds. Governance mechanisms intended to ensure international coordination and transparency, several of which are discussed in Chapter 5, are essential to help avoid such situations.
The potential for multiple independent experiments to have a larger aggregate effect on global temperature also makes it challenging to set firm thresholds for outdoor experimentation by individual countries. Thus, the committee suggests a threshold for individual experiments as well as for the aggregated effects of all outdoor experiments conducted globally in a given year. The contribution from outdoor experiments conducted by individual countries, including the United States, should be well below these global aggregate thresholds.
Furthermore, the committee has taken a precautionary approach in choosing relatively conservative thresholds to allow for the possibility that, lacking the necessary governance and coordination, outdoor experiments could be undertaken without full disclosure to governments, the global scientific community, and the public. This consideration motivates the recommendation that the temperature thresholds for individual experiments be two orders of magnitude below detection limits, assuming that there are unlikely to be more than 10 experiments conducted each year by the international research community. This temperature threshold would therefore limit the global annual temperature change to be less than the detection limit by approximately one order of magnitude (i.e., if 10 experiments were conducted right at the threshold, the temperature change would be approximately 10 times less than what can be observed globally).
These thresholds will need to be revisited and revised periodically to account for evolving SG research and research governance. Scientists and stakeholders are likely to make compelling arguments for both lower and higher thresholds. Furthermore,
the temperature threshold suggested here focuses just on concerns about physical climate effects (and, implicitly, the related environmental and human system impacts). Social or political impacts that could be associated with outdoor substance release experiments should be independently assessed prior to each experiment.
Experiments that fall below the thresholds would be eligible to be considered on a case-by-case basis, in light of relevance to open questions, expected benefits of the study outcomes, and timing relative to other steps; they would be subject to approval based on the governance guidelines adopted by the larger SG program as outlined in Chapter 5. This case-by-case consideration would also include evaluation of potential local effects specific to the experimental design and location (e.g., could an MCB experiment expose sensitive ecosystems to excess salinity?). Interventions larger than these limits should be allowed only after new thresholds have been established, in a review process to be held within 5 years of establishing the research program.
Considerations for Setting a Temperature Change Threshold for Outdoor SG Experimentation
In setting a temperature change threshold for field experiments, it is important to consider the timescales and spatial scales to which it will apply. The committee recommends a reference timescale of 100 years, which allows one to use the same scale for experiments involving aerosols with widely varying lifetimes (days for MCB, on the order of 1 year or more for SAI). A 100-year timescale also allows for a reasonable comparison to the warming associated with CO2. In addition, it is important to compare equivalent spatial areas; thus, the committee recommends that temperature changes should be scaled to global-scale differences. In practice, this means that for small particle emission tracks, the area of cooling is divided by the surface area of Earth. Using a global-scale threshold allows for experiments in which the cooling would be detectable in a small area (typically over the ocean) but would not be measurable in global surface mean temperature.
The committee recommends limiting the perturbation allowed per experiment to less than two orders of magnitude smaller than currently detectable changes in global mean surface temperature. Given current observational capabilities, this limit would constrain the temperature perturbation to 100 nK (100 x 10-9 C) per experiment and to 1 µK (1 x 10-6 C) for the sum/aggregate of all experiments conducted globally (both limits for a 100-year time horizon). Experiments below this threshold can allow for useful scientific inquiry. For example, an MCB experiment designed to comply with this threshold (i.e., to generate a global surface temperature change of no more than 100 nK normalized to 100 years) is equivalent to a typical ship track that induces more than 15 percent albedo change over 2,500 km2 for 6 hours. Microphysical changes produced by such emissions are more than large enough to allow useful measurements to be collected in process studies (Russell et al., 2012).
Considerations for Setting a Mass Threshold for Outdoor SG Experimentation
The mass threshold is also designed to be conservative, both in limiting the overall amount of material emitted per experiment to 1,000 kg and globally to 10,000 kg annually and in ensuring that the material is considered sufficiently safe from an environmental and human health standpoint. This amount of emissions is significantly less than other commonly accepted anthropogenic emissions to the atmosphere. For example, fuel dumped by aircraft with mechanical difficulties is reported to be up to 53,000 kg per incident;11 U.S. firework usage for 2017 was estimated at more than 100,000,000 kg.12
The proposed mass thresholds assume that the substance released is known to be relatively inert and of low toxicity. This assumption is consistent with materials currently being considered for outdoor SG experiments. For example, MCB studies have proposed using NaCl (salt from seawater), which is naturally present in marine environments; SAI studies have proposed either sulfate (which occurs naturally in the stratosphere in much higher quantities after volcanic eruptions) or calcite. That said, even materials that might be considered safe in a general sense may be harmful in specific conditions, such as at high concentrations or if sensitive organisms are exposed. Before proceeding, proposed outdoor experiments would need to do a complete accounting of the environmental effects of an outdoor experiment that would consider how long and at what levels sensitive ecosystems might be exposed to a substance and the toxicity of the specific substance to organisms that would be exposed. These issues will need to be addressed by the required environmental impact assessments described in Recommendation 5.1h and the permitting processes discussed in Recommendation 5.1i.
11 See https://en.wikipedia.org/wiki/Fuel_dumping#cite_note-3.
12 See https://www.americanpyro.com/assets/docs/FactsandFigures/Fireworks%20Consump.%20Figures%202000-17.pdf.
6.4 FUNDING CONSIDERATIONS FOR SOLAR GEOENGINEERING RESEARCH
Implementing the recommended research and research governance will require dedicated resources. It is beyond the scope of the committee’s task and resources to develop detailed budget estimates for the proposed research program;13 indeed, many aspects of the SG research program are not yet mature enough to allow for the development of detailed budget estimates. Nonetheless, to help shape the planning for these detailed budgets, the committee offers a set of general guidelines and an indicative picture of a national investment in a research program.
In the committee’s view, the following guidelines provide a reasonable foundation for shaping the budget of a national SG research program:
- Funding for SG research should not shift the focus from other important global climate change research, and it should recognize the risk of exacerbating concerns about a slippery slope toward deployment. This guideline implies that the near-term budget for SG research should be small relative to the overall investment in global change research.
- The research program should support equitably all of the research clusters discussed in this chapter from the outset. The committee considers all of the recommended elements of the program as essential and believes that the program’s success will be diminished if any elements are omitted or delayed.
- The budget should be able to accommodate major field campaigns, should proposals for such campaigns meet other requirements outlined in Recommendation 6.2. Such campaigns might involve aircraft, ocean vessels, large deployments of autonomous sensors, or potentially a combination thereof, as well as modeling, analysis, and research, including on human dimensions and other impacts.
- A substantial fraction of the research program should be dynamically allocated in order to allow the research program to flexibly adapt as learning proceeds.
- Research funding should be accompanied by support for implementing research governance and public engagement. Achieving the integrated strategy of research, research governance, and engagement requires dedicated funding for advancing these other (non-research) activities.
13 It is likewise beyond the scope of this specific study to evaluate or make recommendations regarding the “opportunity costs” of supporting SG research compared with supporting other research priorities. Such choices often encompass more than just scientific considerations and will need to be weighed by decision makers.
Taken together, these guidelines can help align the program with the principles for SG research in Chapter 3 with the integrated research program design presented in Chapter 4 (see for example, Figure 4.1) and with the governance framework recommended in Chapter 5.
The committee suggests that a reasonable initial investment in SG research is in the range of $100–200 million over 5 years. A research program of this size would represent a small fraction of the national budget for climate change research. For comparison, in 2019, the U.S. Global Change Research Program (USGCRP) “cross-cut” budget for global change research overall was $2.546 billion, of which $1.047 billion was to support non-satellite research activities (Our Changing Planet, 2020). Likewise, leading foundations spent roughly $1.6–1.8 billion on advancing climate change mitigation, including for research, in 2019 (ClimateWorks Foundation, 2020). While small relative to the overall investment in global change research, a 5-year investment of $100–200 million would be a several-fold increase in funding for SG research over recent levels (see Table 4.2).
At the same time, a 5-year research investment of $100–200 million should be sufficient to advance, to varying degrees of completion, all the research topics identified in Recommendation 6.1. As a starting point for planning, the committee suggests that the budget be allocated along the lines shown in Figure 6.2. This budget would set aside approximately a quarter of the funding for dynamic allocation as learning proceeds. For the remainder, the committee proposes that, initially, roughly half of the funding be directed to research on impacts and technical dimensions (with an appropriate balance across MCB, SAI, and CCT), a quarter to research on social dimensions, and a quarter to research on context and goals. These rough budget allocations reflect differences in the cost of different kinds of research, without implying that some topics warrant more or less focus than others. Some kinds of research are more expensive than others; for example, efforts requiring advanced laboratory equipment or field campaigns involving aircraft- or ship-based observing are more expensive than computer-modeling work and most social science activities. As illustrated in Figure 4.1, these allocations should evolve as knowledge improves and the research needs adjust accordingly, thus the importance of ensuring flexibility for a large fraction of the funding.
Field campaigns to obtain in situ measurements are likely to be the most expensive element of the SG research agenda. Costs of past field campaigns have ranged from a few million up to a few tens of million for major multiyear aircraft campaigns (see Box 6.1). It is reasonable to expect that MCB and SAI field campaigns might have comparable budgetary requirements, though detailed estimated costs for specific pro-
posed missions have not been published. Experiments involving controlled releases of substances would entail some additional costs to develop injection technologies; these costs could vary widely depending on the experimental design. While these controlled-release experiments would be useful in advancing our understanding (see “Atmospheric Processes” section earlier in this chapter), undertaking them will require significant progress in developing appropriate governance, environmental review, and public engagement, as described in Chapter 5. The large range in the proposed 5-year investment in SG research, along with dynamic allocation of a significant fraction of the overall investment, can accommodate two or more field campaigns, should these various requirements be met.
Spinning up any major new research program takes time, and structuring support as a funding ramp allows for a thoughtful process of building capacity, adapting plans based on new information, and developing a research community over time. The budget is proposed to start smaller in the first year, because the workforce capacity would not yet be in place to execute a large new program. Among the reasons why it is important for all of the research elements to launch early in the process is to enable capacity building across the elements and inform decisions about future research directions. Targeted efforts to build capacity and new funding mechanisms for the “Social Dimensions” and “Context and Goals” categories will likely be required because
these areas of research are typically not well represented within the USGCRP research portfolio (NASEM, 2021).
Ramping up the funding over time also provides opportunities to allocate funding in later years, based on the findings from the research up to that point. In other words, some fraction of the research funding would not initially be assigned to particular research topics but instead would be allocated based on opportunity and need (guided by the program steering group recommended above). Likewise, exit ramps need to be built into funding plans in order to accommodate the possibility that, based on findings from the research, some (or even all) lines of inquiry may at some point be defunded.
In addition to funding research itself, support is needed for implementing robust research governance at national and international scales, including public participation and engagement. As discussed in Chapter 5, the committee envisions robust research governance that incorporates public participation and engagement and builds on the learnings from studies of research governance. Achieving the integrated strategy of research, research governance, and engagement (illustrated in Figure 4.1) requires support for carrying out these other (non-research) activities. The committee suggests as a general rule that these governance and engagement efforts be supported at approximately 20 percent of the level of the total research program support—an investment that would scale with the overall size of the research program. The 20 percent target is based on the committee’s assessment of the level of activities that are essential for this research program overall. These efforts could either be supported by the same agencies that support research or perhaps through different funding streams (e.g., U.S. Department of State, regulatory agencies, the White House Council on Environmental Quality, or public–private partnerships with philanthropy).
This budget is intended to indicate incremental funding that adds to any current or anticipated near-term funding of SG research and research governance. While the committee expects that the proposed research would be federally supported, it is also possible that support from philanthropic sources could help enable some of the proposed activities that are particularly challenging for government agencies to advance. Any philanthropic support for an SG research program would need to be pursued in a way that embodies the principles for the conduct and governance of research discussed in Chapter 5 and that ensures that the federally and privately funded activities are well coordinated.
6.5 CONCLUDING THOUGHTS
As the discussions throughout this report illustrate, the scientific community is at an early stage of understanding the complex array of issues surrounding SG. Research today offers indications that SG strategies do have potential value as one of the tools that could be used to help meet goals for limiting global warming. But research also points to many uncertainties and possibilities for unintended harmful consequences that have significant societal implications. Understanding the “social feasibility” of these technologies (e.g., societal perceptions and reactions, political and economic ramifications, and ethical concerns) is just as important as understanding the technical question of “will it work.”
The SG research program proposed herein is, by design, quite different from most traditional environmental research and development programs—with an array of interlinked research “clusters”; stepwise, iterative planning; and a strong governance framework that helps ensure transparency, accountability, human and environmental safety, and robust public engagement. Rather than being a burden on the research community, we suggest this governance framework will enable this research to proceed effectively. What has been proposed herein is just the first phase of a research program. Based on the insights gained from this initial phase of work, many aspects of this program (e.g., research goals, governance measures, and funding support) will need to be recalibrated and revised. The research program may continue to expand—or it may in fact shrink if early research suggests strong reasons to discontinue research.
Many of the difficult questions that society may eventually face about actual deployment of these SG interventions are beyond the scope of this study. We have confidence, however, that if the research program is pursued as envisioned, it will yield a much stronger foundation for addressing those critical questions. Ultimately, the growing insights about SG must be considered within a much broader lens that includes the other (primary) strategies for addressing climate change—reducing GHG emissions, capturing and sequestering carbon, and preparing for and adapting to climate change impacts. Advancing understanding of individual strategies themselves is necessary but not sufficient as “real-world” decisions will require finding an appropriate balance and interplay among all of these strategies. While not the focus of this study, we strongly encourage pursuit of a broad integrative approach.
Given that climate change is one of the most complex challenges that humanity has ever faced—and that SG is one of the most controversial aspects of the response to climate change—the scientific community must rise to this challenge with humility and creativity and stretch itself in new ways, across disciplines and national boundaries and beyond business-as-usual approaches to research.
This page intentionally left blank.