Climate change is increasingly recognized as a risk management challenge, but one in which the risks are often deeply uncertain. Deep uncertainty exists when parties to a decision do not know or do not agree on any single probability distribution over future states of the world, the system models relating action to consequences, or the weightings over objectives. Methods and tools to address such deep uncertainty have become increasingly available to help researchers and decision makers. While different in many particulars, these approaches all include the concepts of stress testing proposed plans over a wide range of plausible scenarios and then seeking to identify robust and adaptive pathways that can achieve goals over a wide range of such scenarios. At their best, such approaches can help generate common understanding and consensus among diverse groups, increase transparency, facilitate the use of analytics in deliberative processes, and help result in more resilient (and less over-confident) plans. This talk will describe recent advances in decision making under deep uncertainty (DMDU); survey how these approaches have been applied to both climate change mitigation and adaptation; discuss successes, barriers, and challenges; and offer suggestions for future research.
[Virtual] Andlinger Center Highlight Seminar
Thu, Sep 24, 2020, 4:30 pm to 5:30 pm