Climate Projections and Uncertainty Communication

Abstract

Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists' estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis was tested in two experiments. Results suggest that including uncertainty estimates along with climate projections leads to an increase in participants' trust in the information. Analyses explored the roles of time, place, demographic differences (e.g., age, gender, education level, political party affiliation), and initial belief in climate change. Implications are discussed in terms of the potential benefit of adding uncertainty estimates to public climate projections.

Communicating Climate Change: Probabilistic Expressions and Concrete Events

“…Moreover, there is some preliminary evidence, with a nonrepresentative sample, showing significantly greater trust in global average temperature increase and sea level rise described as range of values having a 90% chance of encasing the actual value than when described as a point estimate (Joslyn and LeClerc 2016). This finding is in line with recent research in a less politicized domain, suggesting that numeric uncertainty estimates increase people's trust in weather forecasts as well as lead to economically better decisions (Joslyn and LeClerc 2012;Savelli and Joslyn 2013). Importantly, these effects are not dependent background or education (Grounds and Joslyn 2018;Grounds et al 2017), perhaps because most people intuitively understand that weather forecasts involve uncertainty (Joslyn and Savelli 2010).…”

“…In experiment 1, the increase reached significance in the abstract condition, and in experiment 2, it reached significance overall. It is likely that probabilistic expressions increase trust because even nonexperts understand that predictions such as these involve uncertainty (Joslyn and Savelli 2010). When predictions exclude uncertainty information, they seem less plausible because people know that such outcomes cannot be predicted with the precision implied by deterministic expressions.…”

Conditional Process Analysis in Two-Instance Repeated-Measures Designs

“…For example, assume we are interested in understanding why certain people believe in climate change and others do not. Recently, research has suggested that including estimates of uncertainty due to sampling variability (e.g., confidence intervals) along with the results of climate change research might help individuals trust the research more (Joslyn & LeClerc, 2016). Perhaps we believe that this would work for more liberal individuals, but may actually be counter productive for those who are more conservative.…”

Future Global Change and Cognition

“…In addition to Ranney and Clark (2016)'s focus on explanations, Cook and Lewandowsky (2016) as well as Hahn, Harris, and Corner (2016) explore the behavioral and normative aspects, respectively, of using the scientific consensus as a communi- cation tool. Sweetman and Whitmarsh (2016) examine the importance of social role models, and Joslyn and LeClerc (2016) examine the impact of providing uncertainty estimates on people's acceptance of climate projections. Galesic, Kause, and Gaissmaier (2016) likewise expand on the uncertainty theme by providing a classification of different sources of uncertainty and how they can be acknowledged by policy makers and stakeholders.…”

“…The article by Joslyn and LeClerc () also makes specific recommendations that address uncertainty in climate projections. Joslyn and LeClerc begin with the concern that variability between scientists' estimates might give the (mistaken) impression that there is disagreement about the fundamental fact of climate change rather than about the extent or timing.…”