WORKSHOP: The Nexus of Climate Data, Insurance, and Adaptive Capacity: November 2018 - Asheville, NC

社会依靠保险来帮助从自然灾害中恢复，并帮助指导有复原力的基础设施和市场的发展。然而，保险业的决策者面临着不断上升的气候风险，必须对其进行适当的衡量和管理。飓风、洪水、强降水、干旱、风暴和其他罕见但有影响力的自然事件的频率或严重程度的变化会对保险总损失产生巨大影响。此外，气候可以通过改变暴露于高温或干旱，改变空气质量以及转向更有利的疾病条件来改变人类健康。该研讨会讨论了保险业如何更好地衡量和管理气候风险。具体而言，本次研讨会将促进三个不同但相关的研究群体之间关于建模和管理气候风险的全国性跨学科科学研究讨论：气候建模和数据群体，统计学家，以及保险和再保险行业的研究人员。本次研讨会的目标是每个群体中活跃的科学研究人员，其目标是：分享观点，方法和数据库;确定现有研究的差距;形成只有新的、协作的和跨学科的团队才能解决的可行研究路径。讨论的主题包括：决策和现有数据产品的时间尺度;气候数据产品中的不确定性来源;从所有研究界的角度对“理想”气候数据集和模型预测的说明;极端事件既是一个统计挑战，也是保险和再保险损失的主要驱动因素;飓风等次网格单元现象;该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Societies depend on insurance to help recover from natural disasters, and also to help guide the development of resilient infrastructure and markets. However, decision makers in the insurance industry are faced with rising climate risks, which must be properly measured and managed. Changes in the frequency or severity of hurricanes, floods, intense precipitation, droughts, wind storms, and other rare but influential natural events can massively impact total insured losses. Also, climate can lead to changes in human health through shifting exposures to heat or drought, changing air quality, and shifts towards more favorable conditions for disease. This workshop addresses how climate risks can be better measured and managed by the insurance industry. Specifically, this workshop facilitates a national, interdisciplinary scientific research discussion on modeling and managing climate risks among three different but related research communities: the climate modeling and data community, statisticians, and researchers within the insurance and reinsurance industries.This workshop aims at active scientific researchers in each community, with the goals of: sharing perspectives, methods, and databases; defining gaps of existing research; and forming actionable research paths which can only be addressed by teams which are new, collaborative and interdisciplinary. Topics discussed include: time scales for decision making and available data products; sources of uncertainty in climate data products; statements of "ideal" climate datasets and model projections from the perspectives of all research communities; extreme events as both a statistical challenge and a primary driver of losses in insurance and reinsurance; sub-grid cell phenomena such as hurricanes; and data-fusion of historical weather data products, climate model output, and insurance loss databases.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.