STATISTICAL ANALYSIS FOR THE DURATION AND TIME INTERVALS OF TROPICAL CYCLONES, HONG KONG

摘要

Hong Kong is impacted by tropical cyclones from April to December each year. The duration of tropical cyclones is one key factor to impact the normal operation of port or coastal engineering, and longer time interval between two tropical cyclones can provide longer operation or construction time. Therefore, it is quite important to study on the long-term laws of the duration and time intervals of tropical cyclones which attacked Hong Kong. The Hong Kong Observatory issues the warning signals to warn the public of the threat of winds associated with a tropical cyclone. Choose the tropical cyclones with warning signal No. 3 or above as the research object. A statistical study was conducted on the duration of each tropical cyclone, the time interval between every two continuous tropical cyclones during the year, and the time interval between the last cyclone of each year and the first cyclone of the following year. Poisson compound extreme value distributions are constructed to calculate the return values, which can make people know how long a tropical cyclone with a fixed duration or time interval occurs once in statistical average sense. Based on bivariate copulas, the joint probability distribution of duration and time intervals of tropical cyclones are presented. Then when the duration of a tropical cyclone is known, the conditional probability that the time interval before the next tropical cyclone occurs is greater than a certain value can be calculated. The results provide corresponding conditional probability distributions. Similarly, for the sum of the duration of tropical cyclones each year, and the time interval between the last cyclone of each year and the first cyclone of the following year, their joint probability distribution and conditional probability distributions are also presented. The conditional probability can provide the probabilistic prediction of the length of the stationary period (with no impact of tropical cyclones).