Biological and Environmental Research - Earth and Environmental System Sciences
Earth and Environmental System Modeling

The Relevance of Detection and Attribution for Loss and Damage Policy

Monday, December 14, 2015 - 16:00
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The concept of loss and damage (L&D), the residual adverse impacts of climate change beyond what can be addressed by adaptation, has featured as a central component of recent discussions on international climate policy, most notably in negotiations under the United Nations Framework Convention on Climate Change. However, it remains unclear what sort of scientific evidence will be required to inform L&D activities, including with respect to issues of responsibility, liability, compensation, and financing. Possible types of scientific evidence include simple observation of the occurrence of weather-related disaster, understanding of causation and the role of anthropogenic emissions, and the comparison of understanding of causation versus observations of long-term trends through detection and attribution (D&A) analysis.

In this presentation we will discuss these questions in detail and consider the implications. If L&D policy leans towards a compensation rationale, then it will likely require the most comprehensive form of evidence of the role of anthropogenic emissions in observed L&D, in other words D&A analysis. However, this has restrictive requirements, for instance in the retrospective availability of long-term monitoring, that may be prohibitive in many situations. Unfortunately, conditions that lead to a dearth of sustained long-term monitoring often also lead to greater vulnerability and exposure, and are thus exactly the conditions that L&D activities are intended to address. On the other hand, if L&D activities are motivated as a mechanism for supporting adaptation they may not necessarily require D&A evidence, but can nevertheless benefit from the confirmation and calibration that D&A provides. Thus, even if L&D policy is not focused on compensation, building resources and capacity in long-term monitoring and its analysis remains a priority.

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