Considerable challenges remain in understanding climate change, evaluating its associated effects on society, and identifying potential adaptation options. Implementing adaptation measures can increase the adaptive capacity and lessen the sensitivity of society as a whole, reducing its vulnerability to climate change effects.
To successfully adapt to climate change, society’s leaders need to make decisions that reduce potential damage and take advantage of new opportunities. However, decision and policy makers do not always have the information they need to make necessary changes. Also, they often lack appropriate decision support tools to present information on a cost-loss level, which would enable them to explicitly include adaptation actions in city and state budgets.
The Center for International Climate and Environmental Research–Oslo (CICERO) and the Norwegian Computing Center convened a workshop in Oslo, Norway, in April 2016 that brought together representatives from science and practice to discuss the practical and methodological challenges of climate change adaptation. Climate scientists, environmental economists, statisticians, and those who provide and need distilled climate data to support decisions made by the public and private sector, mainly at the city and state levels, attended. The workshop was structured around three themes: adaptation, uncertainty, and visualization.
The participants identified open access to easily available data as one of the main challenges of climate change adaptation. This holds, in particular, for economic and insurance data, in addition to the more traditional climate data. Such data sharing requires collaboration between governments, local authorities, the private sector, and public agencies. Compelling results from a pilot study presented at the meeting showed how local insurance loss data obtained from the insurance industry can enable informed decision making at the municipal level for reducing vulnerability to the effects of water-related natural hazards in cities.
Several recommendations emerged from the meeting, including that various data types must be coupled in order to assess climate change effects, the cost of these effects, and the cost of different adaptation options. In particular, attendees called for new modeling frameworks that can model the uncertainty of climate, risks to society, and costs and benefits of adaptation strategies in a joint fashion.
In addition, decision support tools must be able to deal with uncertainty. Meeting participants discussed how tools that combine real options analysis with a portfolio approach are flexible and appealing because they allow decision makers to ponder combined adaptation strategies and invest in adaptation on whatever schedule they choose, all while accounting for the uncertain effects of climate change.
Participants discussed visualization and presentation of information throughout the workshop. They agreed that there is a need for visualization tools for decision making and adaptation options that are user specific and simple without disguising the underlying uncertainty. The practitioners expressed a strong preference for uncertainty information that is presented in terms of risks and likelihoods.
In general, attendees agreed that scientists should interact with policy makers to coproduce stories. Storytelling—setting a scene—will not only help scientists convey information to policy makers but will help both communicate costs and benefits of climate change adaptation strategies to the public.
The workshop was hosted by the Norwegian Computing Center with support from the Research Council of Norway through grants 249709/E10 and 243953/E10 and by NordForsk through project 744556.
—Thordis L. Thorarinsdottir, Norwegian Computing Center, Oslo, Norway; email: firstname.lastname@example.org; and Karianne de Bruin, CICERO, Oslo, Norway; and Wageningen Environmental Research, Wageningen, Netherlands
Thorarinsdottir, T. L.,de Bruin, K. (2016), Challenges of climate change adaptation, Eos, 97, https://doi.org/10.1029/2016EO062121. Published on 07 November 2016.
Text © 2016. The authors. CC BY-NC-ND 3.0
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