Evaluating Extreme Ice Accretion Hazards due to Freezing Rain Based on Reanalysis Data
Abstract Ice accretion during extreme freezing rain events damages infrastructure systems, such as power transmission lines, in China, as evidenced by the 2008 ice storm. However, no tabulated values or maps of the return period for annual maximum ice accretion thickness were provided in the Chinese design codes. In the present study, extreme ice accretion thickness for the Chinese mainland was evaluated. For the ice accretion thickness evaluation, environmental data from 1979 to 2024, extracted from the ERA5 reanalysis data set for grid points over the Chinese mainland, were used. The calculated ice accretion thickness for each freezing rain event was used to develop samples of the annual maximum ice accretion thickness at each grid point. The samples were then subjected to the extreme value analysis. The analysis results showed the spatial statistical characteristics and identified spatial patterns of extreme ice accretion thickness. The probabilistic analysis of the annual maximum ice accretion thickness indicated that among the Gumbel, generalized extreme value, and lognormal distributions, the lognormal distribution was the preferred distribution at the vast majority of considered grid points. The peak-over-threshold approach with the generalized Pareto distribution was also considered for the extreme-value analysis of ice accretion thickness. The ice accretion hazard maps, in terms of the return period of the annual maximum ice accretion thickness, were developed by considering different combinations of extreme analysis approaches, fitting methods, and return periods. Based on the sensitivity analysis, a set of selected options or criteria was suggested for mapping the ice accretion hazard that could be considered for the structural design code revision. It seems that the developed ice accretion hazard map for the Chinese mainland is the first of its kind.
Authors
- HAN PING HONG (ORCID: https://orcid.org/0000-0002-6959-2409)
- Y. X. Liu
- J. N. Liang
Institutions
- Western University (CA)
- Harbin Institute of Technology (CN)
- Guangdong Institute of Intelligent Manufacturing (CN)
- Intelligent Health (United Kingdom) (GB)
Publication Details
- Journal
- Journal of Cold Regions Engineering
- Published
- 2026-10-06
- DOI
- https://doi.org/10.1061/jcrgei.creng-1244
- Primary Topic
- Icing and De-icing Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00