It’s Not Just About More Data: Translation of Science and Decision Support Evaluation for Climate Impact Indicators

The U.S. Global Change Research Program is currently considering establishing a National Climate Indicators System, which would be a set of physical, ecological, and societal indicators that would communicate key aspects of climate changes, impacts, vulnerabilities, and preparedness to inform mitigation and adaptation decisions. Thus, over the past several years 150+ scientists and practitioners representing a range of expertise from the climate system to natural systems to human sectors have developed a set of indicator recommendations that could be used as a first step to establishing such an indicator system. These recommendations have been implemented into a pilot system, with the goal of working with stakeholder communities to evaluate the understandability of individual indicators and learn how users are combining indicators for their own understanding or decision needs through this multiple Federal agency decision support platform.

This prototype system provides the perfect test bed for evaluating the translation of scientific data – observations, remote sensing, and citizen science data -- and data products, such as indicators, for decision-making audiences. Often translation of scientific information into decision support products is developed and improved given intuition and feedback. Though this can be useful in many cases, more rigorous testing using social science methodologies would provide greater assurance that the data products are useful for the intended audiences. I will present some initial research using surveys to assess the understandability of indicators and whether that understanding is influenced by one’s attitude toward climate change. Such information is critical to assess whether products developed for scientists by scientists have been appropriately translated for non-scientists, thus assuring that the data will have some value for the intended audience. Such survey information will provide a data driven approach to further develop and improve the National Climate Indicators System and could be applied to improve other decision support systems.