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Usable science? The UK Climate Projections 2009 and decision support for adaptation planning

Research output: Contribution to journalArticle

Samuel Tang, Suraje Dessai

Original languageEnglish
Article numberN/A
Pages (from-to)300-313
Number of pages14
JournalWeather, Climate and Society
Volume4
Issue number4
DOIs
Publication statusPublished - Oct 2012

King's Authors

Abstract

With future changes in climate being inevitable, adaptation planning has become a policy priority. A central element in adaptation planning is scientific expertise and knowledge of what the future climate may hold. The U.K. Climate Projections 2009 (UKCP09) provide climate information designed to help those needing to plan how to adapt to a changing climate. This paper attempts to determine how useful and usable UKCP09 is for adaptation decision making. The study used a mixed-methods approach that includes analysis of adaptation reports, a quantitative survey, and semistructured interviews with key adaptation stakeholders working in the science–policy interface, which included decision makers, knowledge producers, and knowledge translators. The knowledge system criteria were used to assess the credibility, legitimacy, and saliency of UKCP09 for each stakeholder group. It emerged that stakeholders perceived UKCP09 to be credible and legitimate because of its sophistication, funding source, and the scientific reputation of organizations involved in UKCP09’s development. However, because of the inherent complexities of decision making and a potentially greater diversity in users, UKCP09’s saliency was found to be dependent upon the scientific competence and familiarity of the user(s) in dealing with climate information. An example of this was the use of Bayesian probabilistic projections, which improved the credibility and legitimacy of UKCP09’s science but reduced the saliency for decision making. This research raises the question of whether the tailoring of climate projections is needed to enhance their salience for decision making, while recognizing that it is difficult to balance the three knowledge criteria in the production of usable science.

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