Testing Trends and Return Value Estimation for Extreme Precipitation

• 발행기관: 한국자료분석학회
• 저자명: 황난아(Nan A Hwang) 김한메울(Han Mye Wool Kim) 박정수(Jeong Soo Park)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.9 No.5, 2109~2116쪽, 전체 8쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2007.10.30

영문 초록

This paper deals with usefulness of generalized extreme value distribution based. Annual maxima of daily rainfall data dating from 1901 to 2006 are modeled for ten locations in South Korea. The generalized extreme value distribution (GEVD) is fitted to data from each location. The location parameter of the GEVD is formulated as a function of time to describe the extremes of rainfall and to predict their future behaviors. We quantified the change in extreme rainfall for each location and provided return levels for the years 2016, 2026, 2056, 2106. We also derived estimates of return levels for extreme rainfall. This approach is applied to extreme daily rainfall data for Seoul Korea. The return level of heavy rainfall is calculated from the GEVD models.

목차

1. Introduction

2. Data

2. Data

4. Results of Data Analysis

5. Summary and Discussion

References

키워드

GEVD Gumbel return level non-stationarity