Scholarlink

We employ non-homogeneous Markov chains to study the impact of anthropogenic CO \(_2\) emissions on stationary climate-related disaster frequency (SDF). Annual incidence rates are calibrated with a logit model of global disasters and CO \(_2\) growth estimated from 1960–2022. We find that the baseline SDF ranges from approximately 7 to 14%. Up to one half of the SDF is attributed to variability in CO \(_2\) emissions, which may be influenced by policymakers. Our findings highlight the significant role of CO \(_2\) emissions in driving disaster frequency, aligning with the Sendai Framework’s first priority for action: understanding disaster risk. We also conduct sensitivity analysis to compare the long-term risk reduction potential of different IPCC RCP scenarios.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Short and Long Term Climate-Related Disaster Risk: Connecting the Dots

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Demosthenes Tambakis,
  • Saite Lu

摘要

We employ non-homogeneous Markov chains to study the impact of anthropogenic CO \(_2\) emissions on stationary climate-related disaster frequency (SDF). Annual incidence rates are calibrated with a logit model of global disasters and CO \(_2\) growth estimated from 1960–2022. We find that the baseline SDF ranges from approximately 7 to 14%. Up to one half of the SDF is attributed to variability in CO \(_2\) emissions, which may be influenced by policymakers. Our findings highlight the significant role of CO \(_2\) emissions in driving disaster frequency, aligning with the Sendai Framework’s first priority for action: understanding disaster risk. We also conduct sensitivity analysis to compare the long-term risk reduction potential of different IPCC RCP scenarios.