09 7月 2024 gabriels



  • Frances Moore,美国加利福尼亚大学
  • Chia-Ying Lee,美国哥伦比亚大学
  • Kelly Hereid,美国利宝相互保险公司
  • James Done,美国大学大气研究联合会



Extreme weather events can cause loss of life, disruptions of communities and livelihoods, and extensive property damage. Changes in several extreme weather phenomena – from wildfires, to severe storms, to tropical cyclones, to extreme heat and drought – have been attributed to anthropogenic climate change and it is likely that the frequency and severity of these events will continue to change in the future. The recognition that past experience of weather extremes may be insufficient to characterize present risk, nor serve as a baseline for future risk, is increasingly well-recognized. Many organizations across the public and private sectors are urgently seeking to integrate information on current and future weather risk, including anthropogenic climate change effects, into their decision-making.

Managing the risks of extreme weather events under a changing climate requires particular modeling capabilities that include:

  • Process-informed and statistically robust representation of weather hazards and their relationships with climatological variables.
  • Realistic, comprehensive characterization of extremes, not just central tendencies
  • Assessment of social, structural, and economic vulnerabilities, and event impacts (e.g. lives lost, people displaced, properties destroyed or financial losses)
  • Provision of usable probabilistic information
  • Model skill at the spatial resolution and time-scales relevant for decision-making

These capabilities are distinct from those required to support global climate negotiations and guide emissions targets – historically the primary policy application of global climate models. Instead many of these capabilities are being developed in the field of catastrophe modeling, largely within the private sector. While there is an increasing body of studies on assessing non-stationary hazards, methodologies to best integrate information on anthropogenic climate change with the functionality of catastrophe models are not well-developed. This limits our capability to support the broad array of climate risk management decisions that society must undertake.

This focus issue invites manuscripts broadly relevant to these questions. Topics could include (but are not limited to) evaluation of models for risk-management applications, integrating non-stationarity into hazard, vulnerability, and impact modeling, intersections with risk management decision-making, and institutional questions on the provision of public-facing climate-risk information.




作者可登入期刊主页进行在线投稿,在“文章类型”中选择“特刊文章”,并在“选择特刊”的下拉框中选择“Climate-Change Informed Catastrophe Modeling to Support Climate Risk Management”。



Environmental Research: Climate

  • Environmental Research: Climate(ERCL)是一本多学科、开放获取的期刊,致力于解决有关物理科学的重要挑战以及气候系统和全球变化的评估,并在影响/未来风险、复原力、环境减缓、环境适应、环境安全和最广泛意义上的解决方案方面进行努力。我们鼓励所有的研究方法,包括定性、定量、实验、理论和应用方法。