CHAPTER FIVE

Crosscutting Research and Data Priorities

Basic understanding is needed to inform mitigation and adaptation policies. For example, understanding is needed of the full physical and socioeconomic consequences of different levels of global warming. Physical consequences include, for example, changes in weather and climate extremes, and socioeconomic consequences include those discussed in Chapter 2. This understanding is needed to set an appropriate top-line mitigation goal (e.g., limiting warming to 1.5 or 2°C) and also to anticipate and plan how to live in a world with that level of warming. Such understanding is foundational to the National Climate Assessment, which takes on new importance as climate change impacts become material and remains a legislative mandate. All of this requires improved understanding of not only fundamental processes, but also of local-scale physical manifestations, as well as granular assessments of consequences for ecosystems and human systems.

Closely related, and similarly fundamental to understand, are nonlinear responses to increasing greenhouse gas (GHG) emissions, including thresholds, tipping points, and physical and carbon-cycle feedbacks. These issues directly inform socioeconomic impacts of climate change, as well as more profound questions such as the carbon emissions budgets associated with different levels of global warming, and even the possibility of uncontrolled GHG emissions from biotic sources.

Improved capabilities for modeling the physical climate system remain a key focus of the research coordination efforts provided by the U.S. Global Change Research Program (USGCRP or “Program”); accomplishments from this effort were highlighted by this committee (NASEM, 2017a). However, advances in process understanding, machine learning, scientific computing hardware, and more create the opportunity for significant advances. Specific goals should include better simulation of local-scale

phenomena as well as climate and weather extremes, and advances in uncertainty quantification. This requires a suite of modeling tools, including high-resolution earth system models (ESMs), as well as models of intermediate complexity that can be better suited to exploring issues such as uncertainty quantification.

This chapter focuses on crosscutting research priorities that would facilitate an integrated systems-based approach to risk management (which would enhance management of security challenges) including greater understanding of extreme events and tipping points; improved simulation of local and regional-scale climate; the use of scenarios to project possible combinations of climate and socioeconomic development within which security challenges will arise and be managed; augmentation of data and analyses facilities; and a focus on equity and justice issues.

These integrated systems-based approaches to understanding would be facilitated by capitalizing on investments in research from international organizations and institutions, such as the European Union and the World Climate Research Program. The output of the suggested research investments would be critical input to National Climate Assessments, coordination with international assessments, and risk communication. This report assumes these activities will continue to be central to USGCRP.

Furthermore, because communication of research to a range of stakeholders and for a variety of risk-management decisions is central to the mission and practice of USGCRP, the report assumes that the communication of risks and responses will be embedded in all aspects of the Program’s next decadal research plan, building on the conclusions from multiple National Academies of Sciences, Engineering, and Medicine reports (NASEM, 2017b; NRC, 2010a). Responding to the demand for data, information, and tools that are credible, comprehensive, useful, and usable to enable decision makers at different scales to prepare for and manage climate change provides the basis for an effective national capacity for managing the risks of and responses to climate change. The national capacity needs to be structured to learn from successes and failures, to share lessons learned and best practices, and to reduce unequal burdens on any one region, sector, or population group.

EXTREME EVENTS, THRESHOLDS, AND TIPPING POINTS

Possible Earth-system responses to human GHG emissions include not only gradual trends, but also increases in certain types of extreme events and nonlinear responses, including some that are self-reinforcing. The gradual trends include continuous, incremental increases in atmospheric levels of CO₂ and other GHGs, ocean heat content, sea

level rise, and other environmental variables. Increases in some categories of extreme events, such as extreme heat, extreme precipitation, and wildfire, are well documented (see, e.g., Kossin et al., 2017). The trends for other event types, such as tropical cyclones, are more complicated. Since 1975, the proportion of Category 4 and 5 hurricanes has increased at a rate of ~25–30 percent per °C of global warming (Holland and Bruyère, 2014). This has been balanced by a similar decrease in Category 1 and 2 hurricane proportions, leading to the development of a distinctly bimodal intensity distribution. This global signal is reproduced in all ocean basins. Understanding these extremes is an urgent priority because they have disproportionate societal impacts and can help to inform climate mitigation goals.

The Climate Science Special Report of the Fourth National Climate Assessment (Kopp et al., 2017) makes climate tipping points—large-scale, nonlinear shifts in Earth systems—a major focus of its final chapter. Lenton et al. (2019) summarize the current state of understanding of climate tipping points, discuss some of the limitations of the concept, and explore the potential for a cascade of tipping points, with each one triggering others and creating a shift to a warmer world.

Tipping points exist not only in the physical climate and ecological systems, but also in social systems. For example, the introduction of technology led to overfishing of cod and other species in the North Atlantic, resulting in fishery collapse with significant impacts on livelihoods and communities (Hamilton et al., 2004). Of particular concern for the USGCRP research agenda are the interactions between physical and social systems that can lead to surprises and unexpected tipping points with large impacts, such as the drying trends that adversely affect agricultural yields interacting with internal migration, limited employment possibilities, and poor governance resulting in conflict and external migration.

The 2012 Strategic Plan called for USGCRP-supported research to improve modeling of extreme events and identified the possibility of tipping points in physical and biological systems as potential research topics of importance. By the time of the release of the Fourth National Climate Assessment (USGCRP, 2017), advances were made in modeling extreme events, and the assessment included a full chapter on tipping points. However, experience over the past decade and even the past few months highlight the need for continued and expanded research in coupled human-natural system disruptions and socioeconomic consequences of extreme events, tipping points, and social tipping points that might influence mitigation of and/or vulnerability to climate change. Tipping points can also be potentially leveraged for constructive shifts in social-environmental interactions toward low-carbon futures (Otto et al., 2020).

Extreme Events

People will experience climate change primarily through extreme events, many of which are increasing in frequency and intensity, that lead to more compound events with less recovery time in between. Whether or not an event becomes a disaster is a function of the interaction of exposure to the hazard and the degree to which individuals, populations, ecosystems, or infrastructure are sensitive and capable of responding with coping mechanisms, avoidance, adaptation, or transformation (IPCC, 2012; Kim et al., 2020). The vulnerability of interconnected and highly dependent infrastructure, such as water delivery systems that rely on electrical power or emergency shelters that depend on transportation and communication systems, can be amplified by these interdependencies.

The coincidence of multiple types of extreme, climate-related events can compound challenges for communities and regions. Examples include a heatwave experienced coincident with an extreme drought or wildfire, king tides (extreme high tides) coincident with storm surges from coastal storms, and extreme inland storms causing extensive erosion of soils made bare by massive wildfires, in turn driven by the convergence of drought and pest outbreaks. These challenges—most underlain by climate change but many compounded by poor management or inappropriate design—require new preparation paradigms and resilience-building solutions that recognize the uncertainty of where, when, and with what intensity future extreme events will occur as well as that the magnitude and pattern of impacts will be shaped by the vulnerabilities and capacities of exposed communities. One thing appears certain: the history of previous extreme events is now a poor guide to likely future occurrences.

Extreme events also tend to exacerbate existing fissures in society and deep structural inequities. Responses to extremes events can also be considered opportunities to address such structural inequities and rebuild impacted systems to not only be more resilient but more sustainable in the future. New research should further develop understanding about how individuals, organizations, communities and governments assess the likelihood of, perceive, and respond to extreme events.

Tipping Points

One of the lessons of the COVID-19 pandemic is that a potentially manageable crisis can create societal tipping points as impacts on one system (e.g., health) cascade to affect economic and other systems. The COVID-19 pandemic provides important lessons for what can happen when a sudden and unexpected change occurs for which there

was insufficient preparation and planning. Slow and inconsistent implementation of required interventions, including adequate testing, contact tracing, physical distancing requirements, and other measures, resulted in community spread, millions of cases, and hundreds of thousands of fatalities in the United States alone.

The cumulative impact of incremental changes in weather and other environmental variables could, at some point in time, push a part of the Earth system beyond a tipping point and into a completely new state. Two recent Intergovernmental Panel on Climate Change Special Reports (IPCC, 2018, 2019b) suggested that some tipping points could be exceeded with just another 0.5 to 1°C of warming, with an increase of 0.5°C projected to occur as early as the end of the next USGCRP decadal strategy.

It is important to note that the potential consequences of geophysical tipping points will depend on the resilience of social systems, with the potential for impacts to cascade through economic, agriculture, water, energy, and health systems. Tipping points in social systems can arise before geophysical tipping points in situations with high vulnerability. Social systems are themselves subject to tipping points that can lead to widespread and rapid social changes (Otto et al., 2020; Shwom, 2020; Smith et al., 2020). Given the widely acknowledged need for rapid change in technology and practices to meet the challenge of climate change, USGCRP should give some priority to research that deploys the substantial literature on rapid social change to provide insights into strategies that might quickly enhance uptake of mitigation and adaptation research.

Tipping points can form a cascade, with each one triggering others to create an abrupt shift in the planet’s climate system or in social systems that is irreversible. An example of a tipping point cascade involves the ocean circulation system that moves heat around the planet and plays a key role in climate patterns (Steffen et al., 2020). Greenland ice in a warmer Arctic drives a key component of ocean circulation to a 1,000-year low. Fresh water from the melting flows into the Labrador Sea, which has the potential to increase the buoyancy of surface waters and reduce formation of dense, deep water that helps drive the overturning circulation (Yang et al., 2016). Further decline in the ocean current in the Atlantic could lead to a shift in heat distribution around the planet that could trigger other tipping points. Potential tipping-point cascades should be investigated using a variety of tools; USGCRP needs to invest both in high-complexity, high-resolution earth system models (ESMs) and lower-resolution, faster ESMs of intermediate complexity that allow more thorough exploration of uncertainty. To the extent that there is a trade-off between achieving higher resolution and allowing more simulations to better understand uncertainty, those trade-offs can be assessed based on the value of the information generated and its

likely impact on decisions. Equally important is the need for expanded programs of observations to form the basis of improved representation in models of physical processes leading to potential tipping points. Such processes include permafrost thaw and associated GHG emissions and response of the terrestrial and ocean carbon sinks to climate warming.

Finally, it is important to continue to recognize that in addition to extreme events and tipping points, there is significant potential for humanity’s effect on the planet to result in unanticipated surprises. Kopp et al. (2017) noted that there is a broad scientific consensus that the further and faster the Earth system is pushed toward warming, the greater the risk of such surprises.

Selected Needs to Meet These Challenges in 2030

Assessment of the likelihood and timing of extreme events and abrupt changes, including cascading changes, has been difficult to quantify due to insufficient data and a limited ability to model the underlying physical and biological processes. As a consequence, it is difficult to account properly for extreme events and the possibility of major changes in the Earth system in risk projections (van Ginkel et al., 2020). The socioeconomic impacts of the COVID-19 pandemic may provide a useful model for considering the types and magnitudes of such adverse effects, including those on marginalized and at-risk populations, and the need for targeted research investments (Bonaccorsi et al., 2020; Nicola et al., 2020; Singu et al., 2020).

To improve projections of the likelihood and timing of extreme events and abrupt changes in the climate system and the magnitude of consequences for society, three related research efforts could be undertaken. First, existing ESMs should be modified to facilitate simulations of individual tipping point cascades. Second, capacity should be developed to model the two-way associations between climate and social tipping points, including economic shocks and societal disruptions such as forced migration and environmental justice disparities. Third, integrated assessment modeling efforts should be advanced to develop the capacity to link climate and social tipping points (van Ginkel et al., 2020).

SIMULATION OF LOCAL- AND REGIONAL-SCALE CLIMATE

Decisions to manage the risks of climate change need to be informed by projections at relevant scales. The spatial resolution of global climate models (GCMs) continues to improve but is still generally insufficient to directly inform most decisions. This needs

to be addressed through development of much finer-resolution GCMs and improved “downscaling” of GCM results. Furthermore, GCMs do not simulate or do not simulate well many climate-related hazards, including wildfires, floods, tropical cyclones, and tornadoes. Improved representations of these phenomena are needed, whether within climate models or—as is common practice—in separate models driven by climate model output.

In general, downscaled projections result from either dynamical or empirical downscaling approaches. Dynamical downscaling refers to techniques that rely on dynamical climate models, either regional climate models or variable resolution models. Empirical statistical downscaling relies on developing relationships between large-scale variables produced by reanalyses of past climate data or GCMs (e.g., 500 mb heights) and local variables (e.g., temperature and precipitation) needed for impacts and adaptation work, very often at the single point scale. Then these relationships are used to determine changes in the local variables for the future period. Each approach has strengths and weaknesses; these often determine which approach is used, but often the decision is pragmatic rather than scientific. For example, statistical downscaling approaches are less computationally expensive than dynamical methods; thus, it is easier to downscale a large number of GCMs. Dynamical methods, on the other hand, more easily provide a large suite of variables (e.g. winds, humidity, snow) and thus are useful for studies that require more exotic variables. An important development that needs to be further pursued in dynamical downscaling is the value added of developing climate projections at convective resolving scales (Prein et al., 2015).

Numerous comparisons (e.g., Tang et al., 2017) indicate that the methods project different climate changes, based on the same GCM, particularly for precipitation. However, why they differ has not been sufficiently explored and thus which method would be more credible in a particular region is not easy to determine. More rigorous comparisons are needed of dynamical and statistical approaches.

According to a 2012 National Academies report, “Although different approaches to achieving high resolution in climate models have been explored for more than two decades, there remains a need for more systematic evaluation and comparison of the various downscaling methods, including how different grid refinement approaches interact with model resolution and physics parameterizations to influence the simulation of critical regional climate phenomena” (NRC, 2012, p. 71). USGCRP should build on its strong track record in advancing ESMs and coordination of different U.S. modeling centers through its interagency working group.

Socioeconomic Downscaling

The downscaling of socioeconomic aspects of scenarios also is critical. In this context, downscaling encompasses providing both scenarios and the empirical data needed to calibrate and assess scenarios at finer scales, including communities and groups within communities that may be differentially impacted by climate change. With regard to the data needed for verification, ultimately data on individuals and households is ideal although more aggregate data on small areas or local jurisdictions can often be useful when finer grain data is lacking.

Downscaling of variables beyond aggregated measures of demographic and economic change, such as measures of equity and of patterns of urbanization, are needed by decision makers. Quantification and downscaling are needed of variables relevant for adaptation, such as measures of extreme poverty, quality of governance, water scarcity, innovation capacity, extent of social protection, and educational attainment (Schweizer and O’Neill, 2014).

Local- and regional-scale simulations are also needed to quantify some of the co-benefits to society in specific locations associated with mitigation. Examples of quantification of potential co-benefits include climate effects on local air quality, including particulate matter loads, and the potential for carbon sequestration associated with afforestation.

Scientific findings can be made more readily actionable at decision-relevant scales when projections are informed by the range of urgent challenges faced by local or regional entities. For example, urban practitioners are calling for downscaled climate information to understand the likelihood of future extreme events, and their interactions with the built environment, along with projections of possible future distributions of vulnerable populations to facilitate planning for implementing defensive strategies. Coastal states need information about sea level rise, coastal storm frequency and intensity, and socioeconomic projections such as population growth, property values, and availability of insurance to plan for coastal realignment or fortification. To wisely manage future water resources, municipalities dependent on water supplies from distant watersheds need information on future climate, hydrology, and ecology of those watersheds, plus projections of population and business growth in their municipality. These examples suggest the importance of ongoing dialogue between the research community and those who need the emerging understanding to inform their decisions. In addition, research is needed to clarify what degree of spatial and temporal resolution is useful for decision making as many decisions may not require high resolution.

SCENARIOS-BASED APPROACHES

The term scenario is used in multiple contexts, with different meanings. Scenarios do not predict the future but facilitate exploration of a range of possible futures, their associated risks, and the extent to which mitigation and adaptation could reduce projected risks. Scenarios are used to explore what could happen under different sets of assumptions. Approaches to scenarios for global change research include (1) models based on internally consistent descriptions of how future drivers of GHG emissions could evolve over the course of this century; and (2) participatory-based descriptions of factors that can inform specific policy development.

To be effective in identifying research needs, scenarios should be targeted to the full range of scales—global, national, regional, municipal, and community-based—so that USGCRP research can be integrated into the mitigation and adaptation policy portfolios of decision makers and legislative bodies, enabling them to explore potential conflicts, trade-offs, and synergies. Use-inspired research¹ to inform such decisions is also needed on coupling downscaled climate models with multiscaled ecological, socioeconomic, and human behavior models to project possible futures at appropriate scales.

Scenarios to Project Climate Change, Associated Risks, and Effectiveness of Mitigation Policies

Over the past decade, the climate change research community developed a scenario framework that instead of providing one set of internally consistent and plausible visions of the future, provided a tool kit that includes GHG emission pathways (RCPs, or Representative Concentration Pathways; published in 2011), socioeconomic development pathways (SSPs, or Shared Socioeconomic Pathways; published in 2017), and possible policies. The RCPs are input into climate models for projections that do not correspond to a specific societal pathway. The SSPs are alternative societal futures, including inequities, that are as independent as possible from climate change. This framework design provides a flexible approach to addressing a range of questions. Examples include the following: Given a particular emission pathway, to what extent could development choices affect the range of possible risks? Given a particular development pathway, to what extent could different emission pathways and associated climate-related changes affect the range of possible risks? Figure 5.2 illustrates

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¹ Use-inspired research entails engagement with a wide spectrum of users, so as to produce research that informs decision making and leverage the value of discovery-driven research (Clark et al., 2016; Stokes, 1997).

the scenario framework and process for integrating studies combining future climate outcomes, societal conditions, and policy options.

The RCP-SSP framework has been widely adopted across research communities, with about 1,600 publications related to climate change drivers, risks, and response options (O’Neill et al., 2020). To date, the SSP narratives have been designed to support qualitative and quantitative extensions by region (e.g., Europe, New Zealand), by selected cities (e.g., Tokyo), and by sector (e.g., health, energy, agriculture, forestry, fisheries).

Developing narrative physical climate storylines of low-probability, high-consequence climate extremes could further understanding of complex interactions among the physical, ecological, economic, and societal aspects of extreme or compound events and could be used to explore uncertainties (Shepherd et al., 2018). These storylines should encompass a range of conditions including gradual changes in climate as well as possible extremes and tipping points.

Credible, reproducible, and consistent methods for the use of the SSPs across scales are needed to explore new questions (O’Neill et al., 2020). A more diverse set of global SSPs could facilitate exploration of a broader set of boundary conditions for multiscale analyses. This could include development of SSP variants or the mapping of other

scenarios or scenario families to the SSP framework. Developing sanctioned regional scenarios would facilitate consistency across different research endeavors and organizations, such as produced for the Fourth National Climate Assessment.

Adaptation scenarios are needed that describe the transitions by which adaptation outcomes could be achieved. Projecting future resilience would be improved by incorporating variables describing strength of governance and political institutions, health care access, social protection, and other factors.

The RCP-SSP framework does not currently incorporate or address the potential for solar geoengineering research and deployment and its climatic, ecological, socioeconomic, or geopolitical implications. A challenge for including solar geoengineering research is that scenarios are static, but the feedbacks from solar geoengineering would be dynamic on relatively short timescales.

Participatory Scenario Exercises

Participatory scenario development engages decision makers and the public and incorporates normative elements that are part of human decision making (including values, beliefs, norms, and existing priorities) into a process that acknowledges future uncertainty. Using scenario planning events, stakeholders can investigate interactions, synergies, and trade-offs among goals and strategies, rather than focusing on a single outcome (Carpenter et al., 2015; Iwaniec et al., 2020; Jordan et al., 2018; Sterling et al., 2019). These scenario development processes can help identify resilience measures and motivate change at varying levels of government and with the public. The inclusion of the national security community in these participatory exercises would also benefit decision makers who could gain insight into defense and intelligence agencies’ critical expertise. Once decision makers understand possible impacts, they can identify factors needed for policy change, including innovative approaches to reduce environmental hazards, increase resilience, and address inequities in the impacts of climate change and climate policy. Further research may be used to explore the implications of these interactions (Thompson et al., 2020). For example, scenarios focused on banking water versus those promoting urban greening for central Arizona in 2060 showed clear differences in the burden of extreme heat (Iwaniec et al., 2020).

Incorporating tabletop and functional planning exercises (e.g., stress testing and war games) may be effective in ground-truthing applied research findings into planning, policy, and program options considered by decision makers and the public at local, regional, state, and tribal levels. For example, back-casting approaches (i.e., starting with

a desirable future and working backward rather than starting with projections and assessing how to make future outcomes more desirable) identify desirable aspects of the future; determine obstacles, including climate change, for achieving the desired goals; and identify strategies to achieve the desirable outcomes (e.g., Nikolakis, 2020). Providing web-based and/or other opportunities for broader public participation in scenario exercises should be considered to help enhance general understanding of possible outcomes and to support difficult policy decisions.

Scenarios can make climate-impact science more usable and help speed adaptation action by decision makers. Complex environmental-threat information and computational model outputs become accessible and usable for decision makers who rely on scientific and technical advisers for leading-edge guidance. When model outputs are used in the context of participatory scenarios, they are one of several inputs to the process of developing visions for a specified time and place. Rather than being seen as a future prediction that is locked in, participants can explore changes in policy, infrastructure, or distributions of natural ecosystem and built elements that might lessen or increase the impact of an environmental threat projected by the model.

The use of socioeconomic and climate storylines as elements of scenario-based problem-solving has been effective in many environmental remediation and climate action programs (Baker et al., 2004; Carpenter et al., 2015; Iwaniec et al., 2020; Shepherd et al., 2018; Thompson et al., 2020). Such programs are effective in communicating risk via narrative, hands-on, and visual depictions of actual and potential impacts to regional stakeholders. One example of a successful program model is the Adapting to Rising Tides² initiative in the Northern California San Francisco Bay Area, which uses both community narrative and sophisticated risk graphics to inform environmental policy and community safety improvements with state-of-the-practice scenario planning. Another example is the Dutch Dialogues, held in Charleston, South Carolina (Dutch Dialogues Charleston Team, 2019). Charleston is facing an existential crisis with tidal and storm flooding, much of it related to climate-induced sea level rise. The city is holding public discussions and engaging in planning with international and domestic flood-water management experts and local community members and leaders to develop and implement strategies to ensure that the city remains livable as climate change progresses and flooding frequency and severity increase.

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² The San Francisco Bay Conservation and Development Commission Adapting to Rising Tides program is focused on helping shoreline communities in the San Francisco Bay area, spanning 10 California counties, to plan for sea level rise and other climate impacts. See http://www.adaptingtorisingtides.org.

Importance of Scale

Accelerating the exchange of technical knowledge between USGCRP agencies and decision makers in regions and communities most at risk should be a priority. Scientific findings can be made more readily actionable at decision-relevant scales when this information exchange is informed by the urgent challenges faced by local or regional entities. For example, urban practitioners are calling for downscaled climate information to understand the likelihood of future extreme events, so they can integrate their understanding of the distribution of vulnerable populations and plan for implementing defensive strategies. This is particularly important because there is increased flood exposure due to precipitation extremes and population growth in the United States (Swain et al., 2020). Coastal states need information about sea level rise and storm frequency and intensity. They also need socioeconomic projections such as population growth, property values, and availability of insurance in order to plan for coastal realignment or fortification. Municipalities dependent on water supplies from distant watersheds need information on future climate, hydrology, and ecology of those watersheds, plus projections of population and business growth in their municipality, to wisely manage future water resources. And in all these analyses, vulnerable populations and equity dimensions require special attention.

DIVERSITY, EQUITY, AND INCLUSION IN GLOBAL CHANGE RESEARCH

A significant body of research demonstrates that the risks associated with climate change are not distributed equitably across sectors, regions, or populations. In particular, racial and ethnic minorities, low-income households, and remote communities are likely to be disproportionately adversely affected by a changing climate (Dietz et al., 2020; USGCRP, 2018). Nevertheless, the U.S. public often underestimates the degree to which environmental risks are a concern, which is often very high (Pearson et al., 2018). Accordingly, local, state, and national efforts regarding climate risk management are increasingly focused on how the risks and benefits of policy interventions such as mitigation and adaptation are distributed, so that policies can be designed in a manner that is effective and fair.

Developing the evidence base to support such decision making is best facilitated by broadening participation within USGCRP science agencies and grantees, so that those populations most at-risk from climate change are represented among those conducting global change research. For example, in 2017 “Earth scientists, geologists, and oceanographers” was one of the least diverse occupation categories in the sciences, with Blacks and Hispanics comprising just 1.5 percent and 3 percent of the total de-

spite representing 12 percent and 15 percent, respectively, of the U.S. population (NSB, 2019). This lack of inclusion undermines the capacity of the U.S. scientific enterprise to generate insights that are credible, relevant, and legitimate to diverse audiences (Cash et al., 2003). In addition, enhancing opportunities for stakeholder participation and community engagement in the sciences through transdisciplinary and community participatory research can enhance the impact and broaden the application of the science supported by USGCRP member agencies.

The committee suggests that USGCRP give a high priority to concrete efforts to increase diversity in climate science across the broad range of scientific fields and institutions involved. A first step would be to better understand the current state of, and trends in, diversity among individuals involved in research across USGCRP member agencies and, in particular, the extent to which those individuals are representative of the communities considered at greatest risk from climate change and climate policies (Avallone et al., 2013; Behl et al., 2017; Mattheis et al., 2019; Murillo et al., 2008; Popp et al., 2019). In addition, a systematic examination of the obstacles to greater diversity and an evaluation of programs and policies that have and have not been effective in increasing diversity could provide the basis for near-term action (Gay-Antaki and Liverman, 2018; Tucker et al., 2009).

In the longer term, ongoing engagement via deliberation and consultation with underrepresented communities can help build trust and engagement. The role of state, regional, and local partners can be amplified in order for research and academic experts to best frame improved decision-support findings and recommendations. Environmental and social justice organizations may also offer innovative approaches for the scientific community to apply in forming effective and productive ways to integrate heretofore underrepresented communities of influence. The committee suggests that USGCRP plans routinely and directly address actions toward the ends of building greater understanding of equity and climate justice and increasing diversity in the global change research community.

MAINTENANCE AND IMPROVEMENT OF DATA AND ANALYSIS FACILITIES

Progress in research on the risks and topics discussed in earlier chapters, as well as the previous sections on extremes, tipping points, and scenarios, calls for the design and implementation of augmented analysis frameworks that can more adequately represent these intersecting realms. Global change research to inform policies for the coming decades calls for an expanded USGCRP program on the development and management of needed data sets.

Special attention should be paid to developing and making available the social science data needed to support the security challenges of the coming decade. The culture of and mechanisms for data sharing are strong in the social sciences. The social sciences have had considerable experience designing and implementing long-term data collection efforts—some of the longest such projects are now in their seventh decade of coordinated efforts. What has been lacking is a serious and consistent federal investment in the data needed for social science analysis in support of global change research. There is an urgent need and opportunity to foster socioeconomic observing systems (Sandifer et al., 2020; Stern et al., 2013) that would link the most significant socioeconomic data streams to identify additional needed information and how it should be collected and aggregated so as to be useful for modeling future climate-related risks. Consistent with the integrated systems and risk-based approach, there is a need for greater attention to methods and analytical tools that accurately capture and integrate immaterial and non-monetized sociocultural values as part of efforts to assess co-benefits/dis-benefits of adaptation and mitigation strategies within the context of different possible development pathways.

Special attention will be needed on methods of uncertainty analysis; their incorporation into analysis of extremes, thresholds, and tipping points; and integration of results into forms that meet the particular needs of decision makers (see Box 5.1). The effort will build on current capacities such as integrated assessment models (Weyant, 2017), their coupling with agent-based models (Moss et al., 2001), the applications of life cycle analysis (Hertwich et al., 2015; Nielsen et al., 2020), and linking social science insights into modeling (Dietz et al., 2020; Nielsen et al., 2020). Maximum use needs to be made of evolving data acquisition technologies including remote sensing, exascale computing, and artificial intelligence (Reed and Dongarra, 2015).

In addition to social science data management and analysis, analytical tools and approaches supportive of the complex coupled system dynamics also need to be considered (Hallegatte et al., 2012; Ranger and Niehörster, 2012; Roelich and Giesekam, 2019). Econometric methods that analyze large data sets can also be extremely useful in providing insight into the socioeconomic impacts of climate change (Hsiang, 2016), and other big data methods such as machine and statistical learning can improve predictions (e.g., Hastie et al., 2017; Huntingford et al., 2019; Reichstein et al., 2019).

Important aspects of the analyses of natural science data have been supported primarily by nongovernment consortia. For example, The Global Carbon Project falls under the umbrella of nongovernmental organizations devoted to environmental

research. It operates thanks to hundreds of scientists who volunteer their time and efforts to contribute to the organization and analysis of data underpinning the annual global carbon budget—the balance between its sources and sinks at a global scale. The effort of developing the global carbon budget provides a check on the estimates of its components. USGCRP should consider how to strategically leverage these and other nongovernmental efforts, as well as participate and support however possible, to facilitate long-term records for the annual global carbon budget and other key global change information data sets.

CROSSCUTTING PRIORITIES TO ADVANCE INTEGRATED SYSTEMS-BASED RISK MANAGEMENT

A number of priorities crosscut the necessary work to support the domains of risk management described previously in Chapter 4. In particular, the committee highlighted five such priorities:

1. Understanding of extreme events and tipping points, including cascading tipping points, and related feedbacks to the climate system
2. Improved simulation of local and regional-scale climate including uncertainty characterization, which can inform mitigation and adaptation responses.
3. Pursuit of a scenarios-based approach to project climate change, associated risks, and effectiveness of mitigation policies, and to increase the effectiveness of risk management through highly inclusive, stakeholder-driven processes.
4. Increased attention to uneven distribution of costs, risks and benefits of climate change and responses to it, and increased diversity in the scientific community and in the communities with whom the USGCRP engages.
5. Augmentation of existing analysis frameworks and supporting data sets to more adequately represent the many system interactions and yield results in forms that meet the needs of decision makers and the people they represent. Continued investments in research and technology, such as exascale computing, will lead to advancements that may alter the priorities of the USGCRP research agenda over the next decade.

These crosscutting topics provide opportunities for USGCRP to advance integrating efforts and cross-disciplinary research in creative ways, including, for example, through scenario-based activities (see Box 5.2).

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