Scaling up actionable climate knowledge

Significance

Impacts of climate change, such as flooding, drought, and fires, are already affecting millions of people worldwide. To mitigate and adapt to these impacts, we need climate information that: 1) is usable and used by decision-makers, and 2) is disseminated rapidly and widely, that is, information that can be scaled up. We propose three ways to accelerate usable climate knowledge through the collaboration between scientists and potential users: 1) increasing the number and diversity of people cocreating climate information that they trust and can use, 2) disseminating climate information that can be widely available to many decision-makers (e.g., through the internet), and 3) collaborating with decision-makers that make decisions that affect the public (e.g., water managers, city planners).

Abstract

To address climate-driven crises, we need actionable climate knowledge to inform decision-making and support problem solving. Although the science of actionable knowledge is rapidly evolving, less is known about how and why actionable climate knowledge scales up and with what outcomes. We advance three outcome-driven pathways to scale up actionable climate knowledge: 1) broadening participation by increasing the diversity and number of actors involved in actionable climate knowledge coproduction; 2) diffusing actionable climate knowledge uptake among actors not originally involved in its coproduction, and 3) aggregating impact by coproducing actionable climate knowledge with influential actors, such as practitioners and policy-makers, whose decisions affect many others. These pathways can intersect, complement, interact, and tradeoff with each other. Understanding how these pathways work, evolve, and change is critical if we want to better inform the production and scaling of climate actionable knowledge to solve climate problems.

At the core of addressing sustainability challenges, such as climate change, is the belief that scientific knowledge supports better decision-making for global to local action and solutions (1). Over the past few decades, the emergence of climate change as an existential problem in the Anthropocene has led to a greater interest among scientists and decision-makers in knowledge that informs action (2). However, the processes that lead decision-makers to use scientific knowledge, especially climate knowledge, are complex and fraught, particularly regarding the extent to which scientific knowledge has consistently informed solutions (3). We define actionable climate knowledge as science-based climate knowledge coproduced through the engagement between scientists and potential users to inform and drive climate solutions (2). The work of understanding, describing, evaluating, and intervening to make scientific knowledge more actionable has created its own community of research, and has increasingly been influential in the way science is funded and carried out (4). And if there is climate knowledge that is actionable—that is, it informs decisions and solutions—it is reasonable to hypothesize that scaling it up—or intentionally increasing its use among decision-makers, from individual, to households, communities, practitioners, and policy-makers—to address related problems across sectors and geographies would lead to more effective climate action. Recently, global scientific climate assessments such as the IPCC (Intergovernmental Panel on Climate Change) Assessment Report-6 (AR6) have extolled the role of scaling up successful local experiments as an integral part of mitigating climate change (5). But key research questions remain unresolved, including whether and how to scale up actionable climate knowledge, with what outcomes, potential benefits, or harm.

This article explores drivers and constraints of actionable climate knowledge scalability and proposes a heuristic for scaling it up. We recognize that there are multiple ways to scale up climate knowledge. This contribution explores three options that specifically focus on scaling up actionable climate knowledge. A rich and rapidly growing area of scholarship focusing on the coproduction of actionable knowledge has often, theoretically and normatively, focused on the process of knowledge creation. Our goal, in contrast, is to navigate the less trodden path of understanding what happens after actionable climate knowledge has been coproduced, especially in terms of outcomes such as participation, diffusion of coproduced decision support tools (DSTs), and aggregated impact.

With this specific set of goals in mind, we review the broader literature from diverse areas of study focusing on scaling up knowledge. We specifically focus on empirical work on scaling up actionable climate knowledge and build upon this literature to advance a heuristic of pathways through which actionable climate knowledge may scale up through 1) broadening participation by increasing the number and diversity of people, especially potential users, engaged in coproducing actionable climate knowledge, 2) diffusing the uptake of actionable climate knowledge, such as coproduced DSTs, by actors who did not participate in its coproduction, and 3) aggregating the impact of actionable climate knowledge by coproducing it with actors—such as policy makers, practitioners, natural resource managers—whose decisions affect a large number of potential users (e.g., individuals, heads of households, community members). Rather than being discrete processes, these pathways can intersect, complement, interact, synergize, and tradeoff with each other depending on context and level of decision-making (e.g., from individuals, households, and communities to practitioners, regional and national policymakers). In the next sections, we describe the different literatures characterizing the pathways and discuss in more detail potential tradeoffs and synergies surrounding scaling up actionable climate knowledge.

The Science of Actionable Knowledge.

A widely held tenet of the science of actionable knowledge is the belief that engagement between scientists and users of knowledge is a critical driver of knowledge actionability. Scholars have argued that for climate knowledge to be actionable, it needs to fit decision-makers’ needs and decision contexts (e.g., be salient, available, timely, and understandable), interplay well with already used knowledge, and be credible, legitimate, and equitable (6, 7). The main hypothesis guiding the intersection of these tenets is straightforward: If scientists and users engage with each other in an iterative and equitable way, the knowledge coproduced from this interaction will be more legitimate and better fit decision-making, therefore increasing its actionability (8). However, a rich empirical scholarship has shown that the practice of coproduction can be complex and fraught with problems, including lack of representation, unequal power distribution among participants, and inequitable outcomes (9).

While scholars have developed different conceptualizations of what engagement with users is and how it should be evaluated and practiced (2), these conceptualizations often involve engagement between social actors (e.g., scientists, decision-makers, government officials, clients, community members) seeking to solve a problem. Yet, although the literature on the process of engaged research, especially coproduction of climate information and action, has evolved rapidly (10), there has been relatively limited empirical focus on what happens with actionable climate knowledge after it is coproduced and how it scales up (11). Moreover, the perception among many decision-makers that climate knowledge is too uncertain (e.g., probabilistic) and that outputs of global climate models do not fit local level decisions, limits its actionability in many decision contexts (12). What climate change scholars seek to communicate to the public and decision-makers as solutions often have a negative connotation in terms of threats (e.g., doomsday predictions) and—particularly in high-income countries—lifestyle choices (e.g., consuming less, traveling less, having less while paying more). Because political and social actors can perceive these challenges negatively, they can result in defensiveness of the status quo and resistance against action (13). Finally, scholars have argued that other characteristics of climate knowledge such as credibility, legitimacy, and salience, and the way climate knowledge fits to decision contexts and interplays with other knowledge already being used, also drive or constrain its use (6, 7).

Scaling Up Actionable Climate Knowledge.

We advance a heuristic theorizing different pathways through which actionable climate knowledge may scale up. Fig. 1 illustrates the three main pathways of scaling up actionable climate knowledge: 1) broadening participation by increasing the number and diversity of people and organizations engaged in coproducing actionable climate knowledge with the goal of increasing its use; 2) diffusing the uptake of actionable climate knowledge, such as coproduced DSTs, by actors who did not participate in its coproduction, and 3) aggregating the impact of actionable climate knowledge by coproducing it with actors—such as policy makers, practitioners, natural resource managers—whose decisions affect a large number of potential users such as individuals, households, communities.

Fig. 1.

Pathways to use and scalability Pathway 1) broadens participation by increasing the number and diversity of people engaging in coproducing actionable climate knowledge, Pathway 2) diffuses the uptake of actionable climate knowledge, such as coproduced DSTs, by actors who did not participate in its coproduction, and Pathway 3) aggregates the impact of actionable climate knowledge by coproducing it with actors whose decisions affect a large number of potential users.

Pathway 1: Broadening participation. The first pathway focuses on increasing the diversity and number of participants in coproduction to foster the use of actionable climate knowledge in decision-making at different scales. Achieving rapid, sustainable, and equitable use of scientific knowledge requires broadening participation across diverse actors, including both scientists and nonscientists, as well as across different geographies (14). In turn, broader participation is expected to lead to more representation of preferences, identities, and willingness to act in solving climate-driven problems in a just and equitable way (15). For example, an analysis of the development of 15 European pilot landscapes to increase climate change adaptation found that participants’ perceptions on usability of their engagements were equivalent across different personal backgrounds, and a majority saw the value in increasing representative and interdisciplinary participation (16). By increasing the diversity and number of actors participating, engaged research provides context-driven tools that are designed with specific decision-makers’ needs already “built-in” (3).

However, the process of scaling up participation can be plagued by inequalities and undesirable outcomes. For example, social hierarchies have an impact on engagement of different communities and scaling. In the coproduction of actionable climate knowledge, scientists and governmental users often have more time, resources, and experience to initiate these processes than other participants. Such inequity at the outset gives these influential actors greater ability to define the scope for participation in ways that serve their interests, biasing engagement-driven knowledge (17). In turn, this bias can further be compounded by the strong authority that is attributed to scientific expertise compared to other knowledges (e.g., practical, local, or Indigenous Knowledges), further marginalizing the perspectives of other actors involved (18, 19). For example, drawing from interviews with Indigenous and non-Indigenous peoples working in climate boundary organizational networks in the United States (US), Dhillon (2022) describes how decolonial perspectives and Indigenous ways of knowing are sidelined in practice, aligning with other evidence that efforts to produce and expand actionable climate knowledge are falling short of normative aspirations of what engagement could be in terms of serving marginalized peoples (20).

Boundary organizations, defined as organizations that sit between knowledge creation and use, can greatly increase the extent and quality of interactions between scientists and decision-makers and increase users’ involvement in knowledge creation over time (16). They also help reduce the high costs of engagement-driven knowledge production, such as time, logistics, trust- and legitimacy-building, and link different knowledge communities and uses. Similarly, Communities of Practice (COP)—often characterized by a small active core group and a larger number of peripheral participants (21)—can be instrumental in scaling up participation and knowledge use. In this process, peripheral participants often observe and implement what they learn from the core group. For example, empirical studies show that peripheral participants are more likely to use the knowledge developed in the engaged research process (16). Boundary objects—defined as objects such as models, technologies, and DSTs that facilitate communication between different actors—allow for a rapid increase in the number of people that can participate in engaged research (22). Technologies such as Public Participatory Geographical Information Systems (PPGIS)—in which users use a common spatial platform to visualize and collaborate to understand problems and solutions—allow for virtual and remote participatory, web-based modeling. Crowdsourcing—or the ability to enlist a large number of survey participants, usually through the Internet—is becoming more available worldwide, allowing more people to participate both in making their own decisions and generating data that inform other actors’ decisions (23). Controlled social experiments suggest that such approaches can facilitate engagement while maintaining many traits found in face-to-face interactions that drive knowledge uptake (e.g., credibility, legitimacy, fit) (24). Moreover, asynchronous PPGIS often provides the flexibility to enlist potentially large numbers of people to deepen and broaden the crowd of participants. In addition, crowdsourcing may add greater insights when compared to single individuals or organizations that may lack specialized or geographic knowledge (25). However, concerns about methods such as PPGIS, web-based modeling and surveying, include lack of digital and geographic knowledge (26) and sufficient internet connectivity for enabling dynamic interactivity, especially for marginalized and underserved communities worldwide (27). Finally, despite the empirically documented potential for scaling up, there has been relatively less research focusing on both the logistics and equity implications of recruiting more participants and how their participation matters. For example, there is a dearth of analysis and evaluation of how broadened participation influences outcomes (e.g., informing solutions that are just and sustainable and that benefit those who need them the most) (11). Another critical and related question is whether the documented benefits and shortcomings of coproduction (e.g., costs, legitimacy, credibility, fit, interplay) scale up as more people participate and through what mechanisms (24). While dissemination of innovation theory suggests that uptake of new knowledge can happen far and wide in many fields, the empirical evidence for scaling actionable climate knowledge among a larger number of users and to different geographies and sectors is limited (27). In this context, taking advantage of the robust empirical literatures focusing both on the values and behaviors that drive and constrain climate action and on the role of networks in fostering opportunities and overcoming constraints could further illuminate both theoretical and practical approaches to accelerate climate information use and scaling up (28, 29).

Pathway 2: Diffusing actionable climate knowledge beyond nonparticipant users. The second pathway concerns scaling up coproduced actionable climate knowledge beyond those who participate in its coproduction. Such processes often involve the diffusion of DSTs, a means of packaging actionable climate knowledge for users in relevant contexts (1). In general, DSTs may diffuse through society when they fit decision processes, resources are available, and their adoption is perceived positively by users (30). In contrast, the diffusion of DSTs may stall if tools interplay negatively with existing decision processes, are perceived as too risky or too uncertain by potential users, and benefits are not readily apparent (1, 13). Potential users may come to learn about DSTs from influential early adopters, and decisions to adopt can be due to social learning, a process affected by the dynamic characteristics of social relationships among participants (creators), users (early adopters), and potential users (31). DSTs may scale actionable knowledge up through diffusion depending on who is connected (32) and how, with network ties (e.g., familial, neighborhood, COP) shaping how potential users evaluate the advantages and disadvantages of adoption (33). Some potential users may need flexibility to allow for “reinvention” of DSTs, where users take the basic principles of the tools and methods and adjust them to fit their specific needs (34).

There is robust empirical evidence, particularly in agriculture, that underscores how climate DSTs can diffuse given beneficial tool features, influential users (especially peers), and trusted knowledge brokers (e.g., meteorological organizations, extension agents, and local nongovernmental organization representatives) (11). However, evidence suggests that the large-scale diffusion of adaptation tools is not as prolific as that of mitigation or non-climate-related tools. A study analyzing global patent records from 1995 to 2015 found that agricultural climate adaptation tool diffusion was noticeably low (35). These findings suggest that more work is needed to understand why most climate DSTs may never reach potential users who may benefit from them. For example, while climate adaptation action is often associated with increased costs (36), many drivers of diffusion of innovations are linked to a perception of immediate gain or profit (37). Because it may be harder to diffuse climate DSTs whose benefits of use are potential avoidance of future loss or whose positive outcomes are far in the future, there may be a need to intervene in the processes that drive diffusion beyond the coproduction of a climate DST (11). Identifying potential users could help DST developers appropriately allocate climate service resources for increased impact beyond those who coproduced it such as by employing marketing campaigns or coupling climate DSTs to other services (11, 38). Similarly, there is little empirical evidence of whether and how the traits that make knowledge coproduction desirable, such as legitimacy, credibility, and fit (6), diffuse beyond the original participants creating the tools. For example, are nonparticipants more likely to adopt knowledge if they know the knowledge was coproduced by their peers? While knowledge and tools can reach more people through networked diffusion, ongoing work can document evidence as to whether relational benefits such as trust and social learning similarly scale up through diffusion.

Pathway 3: Aggregating impact of coproduced actionable climate knowledge. Scaling up by aggregating impact happens when actionable climate knowledge coproduced through the engagement between scientists and a small number of influential decision-makers—such as policymakers, practitioners, and resource managers—has the potential to affect a large number of people in society. Here, impact aggregates through highly consequential decisions these actors make using coproduced knowledge—such as in the areas of policy design and implementation, enactment of regulation, and planning to respond and adapt to present and future hazards. For example, in the United States, powerful decision-makers within organizations such as the Water Utility Climate Alliance and the Army Corps of Engineers have coproduced knowledge with climate scientists that influences water governance decisions of millions of people, and their access to and use of clean water now and in the future (39). Indeed, these coproduction processes among government officials and scientists who have overlapping goals and similar ways of knowing are often perceived by participants as highly desirable as they bring together high-quality scientific knowledge and powerful decision-makers with the capacity to influence outcomes (24, 39).

However, aggregating impact through this kind of coproduction process also has drawbacks. On the one hand, technocratic insulation—defined as the capacity of technical personnel within agencies to insulate their decision-making process behind the cloak of technical expertise to pursue their own goals (40)—may allow agencies, practitioners, and managers to avoid both the politics and conflicts surrounding complex decision-making such as those concerning climate change mitigation and adaptation. Indeed, by arguing that such decisions require high levels of technical expertise, scientists and technocrats may feel justified in making those decisions beyond the reach of the public (40). Hence, technocratic insulation challenges accountability and the broadening of participation by insulating decision processes from those affected by them, both in terms of legitimacy and of desired outcomes (e.g., just and sustainable solutions) (24). These trade-offs between participation, democracy, and impact are relatively unexamined, with only a few studies focusing on how insulated actionable climate knowledge coproduction can result in negative outcomes (24).

On the other hand, coproduction of knowledge and action can also be construed as benefiting both sides and increasing their ability to get things done. For example, extensive literature on public administration uses the terms coproduction and cocreation to define partnerships between public servants and actors in society as a means of increasing legitimacy and fit between policy and needs, innovating, and effectively increasing government capacity to implement policy (41). They have also persuasively argued that the embeddedness of citizens as policy partners is part and parcel of democracy (41). Moreover, the normative scholarship focusing on actionable climate knowledge coproduction argues that opening the discussion of climate challenges to nonexperts can help clarify and mediate debate, enhance the legitimacy of decision-making (42), and invite more inventive deliberation as scientific preconceptions are questioned and explored (43). However, there is relatively little empirical evidence of how this works in practice, especially in the climate arena. Similarly, there are very few studies exploring how technocratic insulation influences the legitimacy and usability of coproduced actionable climate knowledge; those studies often produce ambivalent findings. For example, a study assessing a water simulation model produced by scientists and water managers in Arizona found that policymakers were skeptical of the salience, credibility, and legitimacy of information produced (44). A long-term study of the trade-offs between democratic decision-making and use of climate information in water management showed that in drought-ravaged northeast Brazil, technocratic insulation both positively influenced the adaptive capacity of water managers to conserve water and created a precarious environment for users to participate in water governance. While water managers were able to curb water use by relying on climate information scenarios (coproduced with climate scientists), 20 y of participatory negotiation empowered users to increasingly challenge water managers publicly. Indeed, by asserting their democratic right to participate in the water allocation decisions, users were able to advocate for higher levels of water use, which in turn could lead to water depletion and loss of environmental services (24).

Synergies, Trade-Offs, and the Coproduction Fit Paradox.

In our introduction, we talked about the need to rapidly scale up and accelerate the use of actionable climate knowledge. To better understand the drivers and constraints of scaling up actionable climate knowledge, we propose a simple heuristic that describes three potential pathways based on desirable outcomes: broadening participation in actionable climate knowledge coproduction, diffusing climate DSTs beyond coproduction, and aggregating and enhancing the impact of actionable climate knowledge. Like many heuristics, our three pathways intentionally streamline complex relationships behind actionable climate knowledge scaling up; however, they are useful for understanding the main mechanisms and potential pitfalls of the different ways climate knowledge can spread actively (through interventions) or passively (by spreading or diffusing over time). There is limited empirical evidence of what these processes are or how to measure them; in this section, we review this limited literature with the goal of describing, theoretically and practically, how these pathways can interconnect, overlap, and intersect with each other. Next, we offer three examples of the trade-offs and synergies documented in the literature.

Example 1. Synergy between DST diffusion and broadening participation. Because actionable climate knowledge is often perceived by potential users as avoiding loss instead of profiting or benefiting from it (37), empirical evidence of rapid diffusion and adoption of climate knowledge and DSTs is limited. However, by seeking to actively and purposefully broaden participation in support of climate knowledge actionability, DSTs can both garner public support and increase legitimacy. One way to accomplish that is engaging in marketing or crowdsourcing campaigns to diffuse coproduced DSTs and climate solutions (38). For example, in the US Midwest, the Useful to Usable Project (U2U) spearheaded a broad marketing campaign to diffuse its coproduced agricultural climate adaptation tools that included mailing information to thousands of farmers and participating in farming events to publicize the tools (38). As a result, many more farmers became aware of the U2U DSTs and slowly started both to use and recommend them to their peers (11). The catalysts for actionable climate knowledge diffusion may also overlap (45). In Kenya, a study of climate-smart agricultural practices diffusion in Gilgil Sub-County found that agricultural extension offices were the predominant network of knowledge diffusion for potato farmers because officers were best able to communicate climate knowledge in a way that fit farmers’ decision-making needs, as well as being readily accessible and reliable. Meanwhile, family and friends were the second-most predominant network, possibly because they acted as pilot farms for some of the knowledge and technologies in question (46).

Example 2. Tradeoff between DST diffusion and fit. Conversely, efforts to coproduce DSTs with practitioners in one region and disseminate them to nonparticipant peers in another region can backfire as the latter can perceive those tools as lacking fit. For example, a large study involving over 200 city practitioners across 46 cities in the US Gulf region found that sustaining a complex process of scaling up a DST called FloodWise Communities—originally coproduced by city practitioners in the Great Lakes regions—was complex and challenging. First, the experiment showed that context matters as local politics, regional exposure to extreme events (a particularly severe hurricane season) and the COVID pandemic were critical constraints to the dissemination of the tool (47). Second, the study found that the perception of fit of coproduced knowledge in one region may not always follow climate knowledge when applied to another region. While participants were positive about many aspects of the tool, they often perceived that it did not always fit their own context despite the high level of customization provided by the tool (48). For example, many participants were quick to discount climate information that did not match their lived experience of weather and climate-driven events. Others remarked that they would have preferred that the tool was coproduced in the region to better “fit” their needs (48). This outcome suggests that touting high levels of fit as an outcome of the coproduction process, scientists and boundary spanning practitioners may create unrealistic expectations among participants. It may also suggest a “coproduction fit paradox”, in which participants’ high expectations that the coproduced information will perfectly fit their decision needs may actually constrain rather than drive its use. Since the parameters of what a “perfect” fit means may be impossible to assess, this paradox has the potential to negatively affect if and how actionable climate knowledge scales up.

Example 3. Synergies and tradeoffs between aggregating impact and broadening participation. In aggregating impact, a lack of accountability from actors who make aggregate decisions can discredit actionable climate knowledge when it is perceived as crowding out other kinds of knowledge (e.g., practical and Indigenous Knowledge) (49), or when aggregate decisions insulate decision-making from users affected by the problem (50). They also share many of the drivers and constraints identified in the literature that shape the impact of actionable climate knowledge. Often, coproduction involving a small number of influential actors limits participation and inclusion of diverse actors and their preferences, rendering the process less democratic and legitimate through technocratic insulation (24, 51). However, insulation can be mitigated both when technocrats seek to garner support for their decisions by actively involving the public in their implementation or by increasing the chain of participant boundary organizations and actors across different scales of decision-making processes (52, 53). Scaling up by aggregating impact can be supplemented through crowdsourcing or PPGIS to simultaneously scale up by broadening participation in different phases of the coproduction process. In these instances, although the general action agenda is designed by the “people at the top,” community members can have a say in the specific priorities and action items that the action strategy addresses. For example, using a pairwise wiki survey—which allows respondents to choose between two options, for New York City residents with community meetings, the Mayor’s Office of Long-Term Planning and Sustainability integrated residents’ suggestions on creating a greener city into the New York City sustainability plan (54). In this case, pairwise wiki surveys allowed respondents to participate in two ways: i) making pairwise comparisons between existing ideas; and ii) suggesting new ideas that will be presented to future participants. By increasing participation, eight of the final 10 ideas came from residents who participated in the survey. Insulation can also be mitigated through an effort to include COP that can further disseminate actionable climate knowledge through their networks. In the Great Lakes region, the US National Oceanic and Atmospheric Administration (NOAA) engaged with different boundary organizations and actors to coproduce an actionable ice forecast in support of navigation in the region (55). The chain of actors involved included climate scientists from different organizations developing ice forecasting models, ice forecasters from NOAA that apply those models, engagement actors from boundary organizations such as the Great Lakes Climate Adaptation Partnership and the Cooperative Institute of Great Lakes Research that mediate the coproduction process, and boat captains from COP representing both public (e.g., US Coast Guard) and private users (e.g., commercial boats) of these forecasts. Through their participation in the coproduction process, each of those actors could aggregate impact at different scales that affect thousands of people through the decisions they make (55).

Understanding these trade-offs and synergies requires rigorous evaluation of outcomes; yet there is limited empirical evidence of how both tradeoffs and synergies affect decision-making and desirable and undesirable outcomes (3). For example, despite significant investment on government-driven climate assessments through the years and across different jurisdictions and geographies, empirically documented evidence of policy action—, for example, through policy tracing—driven by such assessments has been limited (56). While assessments such as the IPCC—among the longest and perhaps the most comprehensive coproduced environmental assessment between governments and scientists—are widely believed to be actionable, there has been limited peer-reviewed evaluation of its impact on policy-making worldwide. This is not to say assessments are not actionable and used; rather it highlights the urgent need to fund and foster rigorous evaluation that can not only increase our understanding of the cost-effectiveness and impact of assessment in terms of policy and decision-making but also support design principles for future assessment efforts. In conclusion, what these empirical examples show is that the different processes shaping scaling up can be complementary and contradictory, sometimes involving undesirable trade-offs and unintended outcomes but also producing synergies that can critically support the design of solutions and the practice of climate-driven decision-making. For example, on the one hand, a lack of accountability from actors who make aggregate decisions can discredit actionable climate knowledge when it is perceived as crowding out other kinds of knowledge (47) or when aggregate decisions do not include the diversity of potential users affected by the problem (50). Additionally, participants’ high expectations about the outcomes of coproduction may actually constrain use, rendering a coproduction fit paradox. On the other hand, broadening participation can support the diffusion of DSTs and increase diversity and inclusion across scales that aggregate the impact of actionable climate knowledge and DSTs among different users.

Hence, there is a critical need for increased empirical research to explore these synergies and trade-offs to better inform what and how to scale up actionable climate knowledge and DSTs to support adaptation and mitigation of climate impacts. Recently a group of scholars dedicated to the science of knowledge actionability has identified critical gaps and advanced an ambitious research agenda for this area of study (1). In this Perspective, we join their effort by focusing more specifically on research addressing the drivers and constraints of actionable climate knowledge scaling up and suggesting that an important goal of this research agenda should be shifting the focus from those who do not use climate information to those who do so that we can better understand how best to scale up actionable climate knowledge.

Data, Materials, and Software Availability

All study data are included in the main text.