首页    期刊浏览 2024年07月06日 星期六
登录注册

文章基本信息

  • 标题:Estimation of global tropical cyclone wind speed probabilities using the STORM dataset
  • 本地全文:下载
  • 作者:Nadia Bloemendaal ; Hans de Moel ; Sanne Muis
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2020
  • 卷号:7
  • 期号:1
  • 页码:1-11
  • DOI:10.1038/s41597-020-00720-x
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:Tropical cyclones (TC) are one of the deadliest and costliest natural disasters. To mitigate the impact of such disasters, it is essential to know extreme exceedance probabilities, also known as return periods, of TC hazards. In this paper, we demonstrate the use of the STORM dataset, containing synthetic TCs equivalent of 10,000 years under present-day climate conditions, for the calculation of TC wind speed return periods. The temporal length of the STORM dataset allows us to empirically calculate return periods up to 10,000 years without fitting an extreme value distribution. We show that fitting a distribution typically results in higher wind speeds compared to their empirically derived counterparts, especially for return periods exceeding 100-yr. By applying a parametric wind model to the TC tracks, we derive return periods at 10鈥塳m resolution in TC-prone regions. The return periods are validated against observations and previous studies, and show a good agreement. The accompanying global-scale wind speed return period dataset is publicly available and can be used for high-resolution TC risk assessments.
国家哲学社会科学文献中心版权所有