Many communities across the world are experiencing the impacts of climate change in terms of extreme weather and compounding hazards. Decision-makers are increasingly looking to use climate data and projections to evaluate their risks and inform their planning & operations. However, using projections of future climate for such specific applications is an inherently complex endeavor. The appropriate use of climate data depends on many factors including: the decision that is being made, the type of data that is available, users’ technical capacities & limitations, users’ risk tolerance, planning timeframes, compatibility with other data or frameworks, etc. Furthermore, climate data is continuously being improved and updated, and policy and regulation are also evolving to better integrate future climate information. Overall, despite many advances in the development of climate data and understanding of extremes, practical guidance on how this science can be put into use is very limited.

In this talk, I will highlight two projects that have embarked on collaborative guidance development to assist climate data users. In the Cal-Adapt Analytics Engine project we have developed “Guidelines on appropriate use of climate projections” for California’s climate data users. I will discuss the rigorous and iterative co-production process that we used, which incorporated the perspectives of a wide-range of data users, decision-makers, scientists, as well as software tool developers. In the HyperFACETS project, we are bringing together climate scientists with water, energy and land managers to co-produce research on “Guidance for Model Linkages”. This research examines cases when different models and datasets need to be integrated to assess the impact of future climate, for e.g. integrating climate model data into hydrological or water management models to assess multi-sectoral and compounding impacts. I will discuss our mixed-methods approach for developing guidance on how to overcome issues such as data compatibility, scale mismatches, error propagation, etc. These two cases illustrate the importance of collaborative and deliberative engagements for developing generalizable guidance on the appropriate use and integration of climate data into other scientific and practical applications.