Annual Maximum Precipitation in Indonesia and Its Association to Climate Teleconnection Patterns: An Extreme Value Analysis SCIE SCOPUS

Cited 1 time in WEB OF SCIENCE Cited 2 time in Scopus
Title
Annual Maximum Precipitation in Indonesia and Its Association to Climate Teleconnection Patterns: An Extreme Value Analysis
Author(s)
Mubarrok, Saat; Jang, Chan Joo
KIOST Author(s)
Jang, Chan Joo(장찬주)
Alternative Author(s)
Saat Mubarrok; 장찬주
Publication Year
2022-09
Abstract
Extreme rainfall (ER) in Indonesia frequently leads to floods and landslides, disrupting economic activity and impacting human lives. Here, we investigate ER variability in association with climate teleconnection patterns (CTP) including the El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Madden-Julian Oscillation (MJO), using extreme value analysis based on daily rainfall data from 32 stations for 30 years (1985-2014). By fitting a generalized extreme value distribution, a significant association between the annual maximum rainfall (AMR) and CTP was found in 12 of 32 stations. The sensitivity test of location parameter showed that the AMR-CTP interconnection was spatially inhomogeneous. The positive (negative) significant association of ENSO and IOD to AMR was noticeable in south-western (eastern) Indonesia. Additionally, MJO positive (negative) association was detected at 4 (3) stations mostly located in Sumatra (Java) Island. Furthermore, the return level analysis shows that the 20-year ER intensity waiting time will be shorter and longer when CTP indexes strengthen and weaken, suggesting a potential increase and decrease in the likelihood of future ER occurrences, respectively. These results are relevant for understanding the relationship between ER and CTP that should be considered in the adaptation and mitigation plans to minimize the ER impacts.
ISSN
1349-6476
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/43261
DOI
10.2151/sola.2022-030
Bibliographic Citation
Scientific Online Letters on the Atmosphere, v.18, pp.187 - 192, 2022
Publisher
Meteorological Society of Japan/Nihon Kisho Gakkai
Type
Article
Language
English
Document Type
Article
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