Research on the statistical characteristics of typhoon frequency

Guilin Liu, Xiao Li, Jinghua Wang, Yi Kou, Xipeng Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

25 Citations (Scopus)

Abstract

Extreme meteorological events are becoming more frequent as a consequence of global warming. Typhoon as one of the natural disasters has caused significant damages globally. Therefore, developing theoretical models to effectively predict typhoon probability is urgent. Based on the stochastic process theory, this paper studies the local statistics of typhoon frequency and suggests a stochastic process model that can describe the number of typhoons occurring locally in time domain. Mathematical evidence has been provided to prove that the number of typhoons during a certain period can be described by using a stochastic process model. Furthermore, the dependency of typhoon occurrences in different time periods and the probability distribution of typhoon occurrence intervals are explored. The suggested model is employed to discuss the probability of typhoon on Naozhou Island in South China Sea during May to September from year 2000–2016 subject to the absence of the event in May. The results reveal that the probability distribution of typhoon events predicted by the suggested model is more reliable in comparison with conventional approach as it considered the typhoon occurrence in time domain, which can provides useful information for predicting the probability of typhoons occurrence and intervals in engineering practice.

Original languageEnglish
Article number107489
JournalOcean Engineering
Volume209
DOIs
Publication statusPublished - 1 Aug 2020
Externally publishedYes

Keywords

  • Risk analysis
  • Statistical characteristics
  • Stochastic process
  • Typhoon frequency

ASJC Scopus subject areas

  • Environmental Engineering
  • Ocean Engineering

Fingerprint

Dive into the research topics of 'Research on the statistical characteristics of typhoon frequency'. Together they form a unique fingerprint.

Cite this