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Decision Making Under Risk of Extreme Climate Events: Applying Lesson From Seasonal Forecasting

Progress Report 2004-2005

Investigators

Jennifer G. Phillips, Bard Center for Environmental Policy
David H. Krantz, Center for decision Sciences, Columbia University
Bradfield Lyon, IRI for Climate Prediction, Columbia University

Evidence from the field of seasonal climate forecasting applications has shown that it is difficult to relay new climate information to users in a format that is useful, partially because cognitive biases in perceptions of uncertain, probabilistic climate information may inhibit good decision making. This lesson has useful application in the area of promoting adaptation to climate change. We make the assumption here that expectations for the coming season or seasons, whether based on climatology, a seasonal forecast, or knowledge of climate change, are susceptible to cognitive biases, and decisions arising from these expectations stand to be improved if biases are addressed. Observational and model-based data support the assertion that climate is changing, making critical the societal goal of improving our ability to respond to new climate information. Observed changes are manifest as increases in extreme events, which influence mental models of climate and, in turn, shape climate-sensitive decisions. This proposed research draws on insights gained in the arena of seasonal forecasting, taking advantage of current responses to extreme climate events, to better understand and address the ways in which mental models of climate act as barriers to adaptation to climate change.

Given the tight linkages between farming systems and climate, we will utilize an agricultural setting for this work in the expectation that mental models of climate among farmers should be particularly well-developed and will lead to useful results. Our work will be conducted in the Northeast US, a region without seasonal forecast skill, which will ensure that mental models of climate are based solely on experience and expectations for climate change. Our primary collaborator is the Regional Farm and Food Project, a non-profit farmer network providing educational resources to farmers in eastern New York State. Using written surveys and in-person interviews with dairy and vegetable farmers, we will map mental models of important climate events, including expected ranges and return frequencies, identifying the relationship between mental models and resource management decisions. Perceptions will then be compared with distributions of observed climate based on historical records drawn from local stations. To address cognitive biases identified through interviews, we will develop and deliver instructional materials in workshop and focus group settings. Instructional materials will be based on a range of materials drawn from seasonal climate forecast materials developed by the PIs for use in Africa, results of psychology lab experiments, and creative visualization techniques to help decision makers envision climate and decision contingency scenarios,. Additional visits with farmers following extreme events that occur during the study period will provide opportunities for evaluating instructional materials, and furthering our understanding of risk management and decision making under climate uncertainty.