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Innovations in assessment and adaptation: building on the US National Climate Assessment

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Part of the Springer Climate book series (SPCL)

Abstract

Well-targeted scientific assessments can support a range of decision-making processes, and contribute meaningfully to a variety of climate response strategies. This paper focuses on opportunities for climate assessments to be used more effectively to enhance adaptive capacity, particularly drawing from experiences with the third US National Climate Assessment (NCA3). We discuss the evolution of thinking about adaptation as a process and the importance of societal values, as well as the role of assessments in this evolution. We provide a rationale for prioritizing future assessment activities, with an expectation of moving beyond the concept of climate adaptation as an explicit and separable activity from Bnormal^ planning and implementation in the future. Starting with the values and resources that need to be protected or developed by communities rather than starting with an analysis of changes in climate drivers can provide opportunities for reframing climate issues in ways that are likely to result in more positive outcomes. A critical part of successful risk management is monitoring and evaluating the systems of interest to decision-makers and the effectiveness of interventions following integration of climate considerations into ongoing strategic planning activities and implementation. Increasingly this will require consideration of path dependency and coincident events.We argue that climate adaptation is a transitional process that bridges the gap between historically time-testedways of doing business and the kinds of decision processes that may be required in the future, and that scientific assessments will be increasingly central to these transitions in decision processes over time.

Keywords

Adaptive Capacity Climate Change Adaptation Climate Adaptation Sustained Assessment Climate Assessment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.CSIRO AgricultureCanberraAustralia
  2. 2.University of ArizonaTucsonUSA

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