Variability of Extreme Temperatures in South Korea Using Generalized Extreme Value Distributions

Title
Variability of Extreme Temperatures in South Korea Using Generalized Extreme Value Distributions
Author(s)
Kwon, Minho; Lee, Kang Jin
KIOST Author(s)
Kwon, Min Ho(권민호)Lee, Kang Jin(이강진)
Alternative Author(s)
권민호; 이강진
Publication Year
2018-04-09
Abstract
Seasonal prediction skills of extreme temperature in the Northeast Asian region including China, Korea, and Japan are relatively low using state-of-the-art climate models. It is introduced that parameters of the generalized extreme value distribution for extreme temperatures have significant interannual variability, in particular in summertime using station data in South Korea. Generally, a distribution for the extreme values of a random variable is fitted to the generalized extreme value distribution (GEV). GEV has three parameters as one of parametric distributions. Those are shape, scale, and location parameters. These distribution parameters have a strong interannual variability due to ENSO (El Nino and Southern Oscillation). This study discusses variability of the distributions for the extreme temperature associated with climate variability such as global warming and ENSO. It would be expected that this study could contribute to a seasonal prediction system for extreme temperatures.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/39596
Bibliographic Citation
European Geosciences Union General Assembly 2018, 2018
Publisher
European Geosciences Union
Type
Conference
Language
English
Publisher
European Geosciences Union
Related Researcher
Research Interests

climate dynamics,climate prediction,기후역학,기후예측

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