Coproduction of knowledge is believed to be an effective way to produce usable climate science knowledge through a process of collaboration between scientists and decision makers. While the general principles of coproduction—establishing long-term relationships between scientists and stakeholders, ensuring two-way communication between both groups, and keeping the focus on the production of usable science—are well understood, the mechanisms for achieving those goals have been discussed less. It is proposed here that a more deliberate approach to building the relationships and communication channels between scientists and stakeholders will yield better outcomes. The authors present five approaches to collaborative research that can be used to structure a coproduction process that each suit different types of research or management questions, decision-making contexts, and resources and skills available to contribute to the process of engagement. By using established collaborative research approaches scientists can be more effective in learning from stakeholders, can be more confident when engaging with stakeholders because there are guideposts to follow, and can assess both the process and outcomes of collaborative projects, which will help the whole community of stakeholder-engaged climate-scientists learn about coproduction of knowledge.

Ecologists who specialize in translational ecology (TE) seek to link ecological knowledge to decision making by integrating ecological science with the full complement of social dimensions that underlie today's complex environmental issues. TE is motivated by a search for outcomes that directly serve the needs of natural resource managers and decision makers. This objective distinguishes it from both basic and applied ecological research and, as a practice, it deliberately extends research beyond theory or opportunistic applications. TE is uniquely positioned to address complex issues through interdisciplinary team approaches and integrated scientist-practitioner partnerships. The creativity and context-specific knowledge of resource managers, practitioners, and decision makers inform and enrich the scientific process and help shape use-driven, actionable science. Moreover, addressing research questions that arise from on-the-ground management issues -as opposed to the top-down or expert-oriented perspectives of traditional science -can foster the high levels of trust and commitment that are critical for long-term, sustained engagement between partners.

Resource managers and decision-makers are increasingly tasked with integrating climate change science into their decisions about resource management and policy development. This often requires climate scientists, resource managers, and decision-makers to work collaboratively throughout the research processes, an approach to knowledge development that is often called ''coproduction of knowledge.'' The goal of this paper is to synthesize the social science theory of coproduction of knowledge, the metrics currently used to evaluate usable or actionable science in several federal agencies, and insights from experienced climate researchers and program managers to develop a set of 45 indicators supporting an evaluation framework for coproduced usable climate science. Here the proposed indicators and results from two case studies that were used to test the indicators are presented, as well as lessons about the process of evaluating the coproduction of knowledge and collaboratively producing climate knowledge.

A growing body of research in translational science provides a foundation for translational ecologists to consider the practices that show the most promise, as well as the potential pitfalls of those practices. These research approaches (eg user-inspired climate science) require deliberate engagement with end users, and an understanding of the social and cultural contexts in which a research project functions. We examine the climate science translation literature (looking at how research can inform decision making) to identify key issues related to how the social sciences have helped guide researchers engaged in user-inspired research. We focus on understanding the more intangible inputs to research projects, including the social and cultural contexts; stakeholder engagement; the role of social capital; and evaluating the outputs, outcomes, and impacts of translational science projects and initiatives. Research on return-on-investment metrics for translational science is increasingly pointing to the conclusion that intentional, structured processes, such as those found in translational sciences, boost the likelihood of science being successfully incorporated into environmental decision making and policy.

Relationships between drought indices and fire danger outputs are examined to (1) incorporate fire risk information into the National Integrated Drought Information System California–Nevada Drought Early Warning System and (2) provide a baseline analysis for application of drought indices into a fire risk management framework. We analyzed four drought indices that incorporate precipitation and evaporative demand (E0) and three fire indices that reflect fuel moisture and potential fire intensity. Seasonally averaged fire danger outputs were most strongly correlated to multi-scalar drought indices that use E0 (the Evaporative Demand Drought Index (EDDI) and the Standardized Precipitation Evapotranspiration Index (SPEI)) at approximately annual time scales that reflect buildup of antecedent drought conditions. Results indicate that EDDI and SPEI can inform seasonal fire potential outlooks at the beginning of summer. An E0 decomposition case study of conditions prior to the Tubbs Fire in Northern California indicate high E0 (97th percentile) driven predominantly by low humidity signaled increased fire potential several days before the start of the fire. Initial use of EDDI by fire management groups during summer and fall 2018 highlights several value-added applications, including seasonal fire potential outlooks, funding fire severity level requests, and assessing set-up conditions prior to large, explosive fire cases.