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      Advances in risk assessment for climate change adaptation policy

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          Abstract

          <p class="first" id="d13942421e183">Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. </p><p id="d13942421e185">This article is part of the theme issue ‘Advances in risk assessment for climate change adaptation policy’. </p>

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          Most cited references32

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          Uncertainty and Quality in Science for Policy

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            The Social Amplification of Risk

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              Rethinking adaptation for a 4°C world.

              With weakening prospects of prompt mitigation, it is increasingly likely that the world will experience 4°C and more of global warming. In such a world, adaptation decisions that have long lead times or that have implications playing out over many decades become more uncertain and complex. Adapting to global warming of 4°C cannot be seen as a mere extrapolation of adaptation to 2°C; it will be a more substantial, continuous and transformative process. However, a variety of psychological, social and institutional barriers to adaptation are exacerbated by uncertainty and long timeframes, with the danger of immobilizing decision-makers. In this paper, we show how complexity and uncertainty can be reduced by a systematic approach to categorizing the interactions between decision lifetime, the type of uncertainty in the relevant drivers of change and the nature of adaptation response options. We synthesize a number of issues previously raised in the literature to link the categories of interactions to a variety of risk-management strategies and tactics. Such application could help to break down some barriers to adaptation and both simplify and better target adaptation decision-making. The approach needs to be tested and adopted rapidly.
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                Author and article information

                Journal
                Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
                Phil. Trans. R. Soc. A
                The Royal Society
                1364-503X
                1471-2962
                April 30 2018
                June 13 2018
                April 30 2018
                June 13 2018
                : 376
                : 2121
                : 20180106
                Affiliations
                [1 ]Geography, College of Life and Environmental Sciences, University of Exeter, Rennes Drive, Exeter EX4 4RJ, UK
                [2 ]School of Social Sciences, University of Dundee, Dundee DD1 4HN, UK
                [3 ]Grantham Research Institute on Climate Change and the Environment, London School of Economics, London WC2A 2AE, UK
                Article
                10.1098/rsta.2018.0106
                5938640
                29712800
                2c54f0ca-7213-45d4-91dd-30344cb047f8
                © 2018

                https://royalsociety.org/-/media/journals/author/Licence-to-Publish-20062019-final.pdf

                https://royalsociety.org/journals/ethics-policies/data-sharing-mining/

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