Communications about uncertainty in scientific climate-related findings: a qualitative systematic review

Abstract

We undertake a systematic review of peer-reviewed literature to arrive at recommendations for shaping communications about uncertainty in scientific climate-related findings. Climate communications often report on scientific findings that contain different sources of uncertainty. Potential users of these communications are members of the general public, as well as decision makers and climate advisors from government, business and non-governmental institutions worldwide. Many of these users may lack formal training in climate science or related disciplines. We systematically review the English-language peer-reviewed empirical literature from cognitive and behavioral sciences and related fields, which examines how users perceive communications about uncertainty in scientific climate-related findings. We aim to summarize how users’ responses to communications about uncertainty in scientific climate-related findings are associated with characteristics of the decision context, including climate change consequences and types of uncertainty as well as user characteristics, such as climate change beliefs, environmental worldviews, political ideology, numerical skills, and others. We also aimed to identify what general recommendations for communications about uncertainty in scientific climate-related findings can be delineated. We find that studies of communications about uncertainty in scientific climate-related findings substantially varied in how they operationalized uncertainty, as well as how they measured responses. Studies mostly focused on uncertainty stemming from conflicting information, such as diverging model estimates or experts, or from expressions of imprecision such as ranges. Among other things, users’ understanding was improved when climate communications about uncertainty in scientific climate-related findings were presented with explanations about why climate information was uncertain, and when ranges were presented with lower and upper numerical bounds. Users’ understanding also improved if they expressed stronger beliefs about climate change, or had better numerical skills. Based on these findings, we provide emerging recommendations on how to best present communications about uncertainty in scientific climate-related findings; and we identify research gaps.

Rapidly evolving aerosol emissions are a dangerous omission from near-term climate risk assessments

“…This can in turn lead to short-sighted or poorly informed decision-making in policy [97]. Following best practices on communicating uncertainty will be particularly important in this context [98].…”

Key insights from climate communication – and how they can inspire sustainability in higher education

“…Climate science often includes sources of uncertainty, and there may also be conflicting information e.g. from diverging model estimates (Kause et al , 2021). That is why, for example, a range of variability is given for climate scenarios or why specific extreme weather events are allocated to climate change with a certain probability.…”

“…That is why, for example, a range of variability is given for climate scenarios or why specific extreme weather events are allocated to climate change with a certain probability. It seems helpful here to lead with what is known for certain (Corner et al , 2018) and explain reasons for uncertainty (Kause et al , 2021).…”

Confidence levels and likelihood terms in IPCC reports: a survey of experts from different scientific disciplines

“…Research on risk communication also shows that there often is disagreement about how to interpret likelihood terms such as "likely" and "very likely" (Budescu et al 2014;Kause et al 2021;Harris et al 2017;Howe et al 2019). People disagree more about how to interpret positive likelihood terms ("likely") than about how to interpret negative likelihood terms such as "unlikely" (Smithson et al 2012).…”

“…It has been posited that pre-existing beliefs about a context can inform the way users interpret scientific evidence and related uncertainties (Beyth-Marom 1982). Perhaps as a result, interpretations of likelihood terms may vary across individuals, who tend to interpret likelihood terms in line with their pre-existing beliefs (Budescu et al 2014;Kause et al 2021).…”