A Study of the Rainfall in Korea Using Outlier Detections (이상치 검정을 이용한 국내 강우의 연구)

Ho Geun Son (손호근); Jae Joon Lee (이재준)

doi:10.14251/crisisonomy.2019.15.10.95

A Study of the Rainfall in Korea Using Outlier Detections

Crisisonomy
Abbr : KRCEM
2019, 15(10), pp.95-108
DOI : 10.14251/crisisonomy.2019.15.10.95
Publisher : Crisis and Emergency Management: Theory and Praxis
Research Area : Social Science > Public Policy > Public Policy in general
Received : September 3, 2019
Accepted : September 26, 2019
Published : October 31, 2019

Ho Geun Son ¹, Jae Joon Lee ¹

¹금오공과대학교

Accredited

ABSTRACT

The outliers in annual maximum rainfall can play an important role in the frequency analysis that estimates the probability rainfall. To ensure reliability of the frequency analysis, this study detects the outliers and conducts a qualitative analysis to investigate the causes of rainfall based on selected outliers. The outliers in annual maximum 24-hr rainfalls at 57 stations in Korea were analyzed by four different methods, such as Grubbs and Beck method, IACWD method, modified z-score method and box-plot method. The causes of the selected rainfall events as high outliers were classified into changma, typhoon, severe rain storm and frontal rainfall. The comparison of the methods shows that less outliers were found with Grubbs and Beck method than the other methods. It is found that 51.0% of the outliers occurred due to typhoon, followed by severe rain storm (35.7%), frontal storm (7.2%) and changma (6.1%). Rainfall events as outliers were mostly caused by severe rain storm in inland regions while they were caused by typhoon in coastal regions. The probability rainfall calculated without outliers from the test was compared with that before the test.

KEYWORDS

outlier detection, cause of rainfall occurrence, probability rainfall

Citation status

* References for papers published after 2023 are currently being built.

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Crisisonomy 2023 KCI Impact Factor : 0.64

A Study of the Rainfall in Korea Using Outlier Detections

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Citation status

* References for papers published after 2023 are currently being built.

Crisisonomy 2023 KCI Impact Factor : 0.64

A Study of the Rainfall in Korea Using Outlier Detections

ABSTRACT

KEYWORDS

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