Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: Pao-Shin Chu x
  • Journal of Applied Meteorology and Climatology x
  • All content x
Clear All Modify Search
Pao-Shin Chu and Jianxin Wang

Abstract

Tropical cyclones in the vicinity of Hawaii have resulted in great property damage. An estimate of the return periods of tropical cyclone intensities is of particular interest to governments, public interest groups, and private sectors.

A dimensionless quantity called relative intensity (RI) is used to combine all available information about the tropical cyclone characteristics at different places and times. To make a satisfactory estimate of the return periods of tropical cyclone intensities, a large number of RIs are simulated by the Monte Carlo method based on the extreme value distribution. The return periods of RIs and the corresponding maximum wind speeds associated with tropical cyclones are then estimated by combining the information about the intensities and occurrences. Results show that the return periods of maximum wind speeds equal to or greater than 125, 110, 100, 80, 64, 50, and 34 kt are estimated to be 137, 59, 33, 12, 6.6, 4, and 3. 2 years, respectively.

The Monte Carlo method is also used to estimate the confidence intervals of the return periods of tropical cyclone intensities. The sensitivity test is conducted by removing the portion of the data prior to satellite observations. For maximum wind speeds less than 80 kt, estimates of return periods from the shorter dataset (1970–95) are almost identical to those when the complete duration time series are used (1949–95).

Full access
Pao-Shin Chu, Xin Zhao, Ying Ruan, and Melodie Grubbs

Abstract

Heavy rainfall and the associated floods occur frequently in the Hawaiian Islands and have caused huge economic losses as well as social problems. Extreme rainfall events in this study are defined by three different methods based on 1) the mean annual number of days on which 24-h accumulation exceeds a given daily rainfall amount, 2) the value associated with a specific daily rainfall percentile, and 3) the annual maximum daily rainfall values associated with a specific return period. For estimating the statistics of return periods, the three-parameter generalized extreme value distribution is fit using the method of L-moments. Spatial patterns of heavy and very heavy rainfall events across the islands are mapped separately based on the aforementioned three methods. Among all islands, the pattern on the island of Hawaii is most distinguishable, with a high frequency of events along the eastern slopes of Mauna Kea and a low frequency of events on the western portion so that a sharp gradient in extreme events from east to west is prominent. On other islands, extreme rainfall events tend to occur locally, mainly on the windward slopes. A case is presented for estimating return periods given different rainfall intensity for a station in Upper Manoa, Oahu. For the Halloween flood in 2004, the estimated return period is approximately 27 yr, and its true value should be no less than 13 yr with 95% confidence as determined from the adjusted bootstrap resampling technique.

Full access