This paper examines the annual highest daily maximum temperature （DMT） in Korea by using data from 56 weather stations and employing spatial extreme modeling. Our approach is based on max-stable processes （MSP） wi...This paper examines the annual highest daily maximum temperature （DMT） in Korea by using data from 56 weather stations and employing spatial extreme modeling. Our approach is based on max-stable processes （MSP） with Schlather＇s characterization. We divide the country into four regions for a better model fit and identify the best model for each region. We show that regional MSP modeling is more suitable than MSP modeling for the entire region and the pointwise generalized extreme value distribution approach. The advantage of spatial extreme modeling is that more precise and robust return levels and some indices of the highest temperatures can be obtained for observation stations and for locations with no observed data, and so help to determine the effects and assessment of vulnerability as well as to downscale extreme events.展开更多
The associations of onset and withdrawal of the rainy season in South Korea (called Changma) have been examined. Composite studies showed that there are significant differences in circulations between extremely early ...The associations of onset and withdrawal of the rainy season in South Korea (called Changma) have been examined. Composite studies showed that there are significant differences in circulations between extremely early and late onset (or withdrawals) not only over East Asia, but also over remote areas. The in situ significant differences include the upper-level jet over East Asia and the subtropical anticyclone over the western North Pacific at lower levels. The significant remote associations include the Indian monsoon and ENSO. The Indian summer monsoon is related to both onset and withdrawal of the Changma, while ENSO has a significant relation only to onset, but not to withdrawal. Key words Changma - Onset - Withdrawal - Interannual variation - Association This study was supported by the National Key Programme for Developing Basic Sciences (G1998040900, Part I), Brain Pool Program (Grant No. 991-5-8) funded by Korea Science and Engineering Foundation, and the Natural Hazard Prevention Research Project, one of the Critical Technology-21 Programs, funded by the Ministry of Science and Technology of Korea.展开更多
文摘This paper examines the annual highest daily maximum temperature （DMT） in Korea by using data from 56 weather stations and employing spatial extreme modeling. Our approach is based on max-stable processes （MSP） with Schlather＇s characterization. We divide the country into four regions for a better model fit and identify the best model for each region. We show that regional MSP modeling is more suitable than MSP modeling for the entire region and the pointwise generalized extreme value distribution approach. The advantage of spatial extreme modeling is that more precise and robust return levels and some indices of the highest temperatures can be obtained for observation stations and for locations with no observed data, and so help to determine the effects and assessment of vulnerability as well as to downscale extreme events.
基金the National Key Programme for Developing Basic Sciences(G1998040900, Part I) Brain Pool Program (Grant No. 991-5-8) funde
文摘The associations of onset and withdrawal of the rainy season in South Korea (called Changma) have been examined. Composite studies showed that there are significant differences in circulations between extremely early and late onset (or withdrawals) not only over East Asia, but also over remote areas. The in situ significant differences include the upper-level jet over East Asia and the subtropical anticyclone over the western North Pacific at lower levels. The significant remote associations include the Indian monsoon and ENSO. The Indian summer monsoon is related to both onset and withdrawal of the Changma, while ENSO has a significant relation only to onset, but not to withdrawal. Key words Changma - Onset - Withdrawal - Interannual variation - Association This study was supported by the National Key Programme for Developing Basic Sciences (G1998040900, Part I), Brain Pool Program (Grant No. 991-5-8) funded by Korea Science and Engineering Foundation, and the Natural Hazard Prevention Research Project, one of the Critical Technology-21 Programs, funded by the Ministry of Science and Technology of Korea.
