Long-term Trend Analysis of Extreme Temperatures in East Asia Using Quantile Regression

• DOI: 10.15531/ksccr.2018.9.2.157
• Publication Date: 2018-07-20T05:11:28Z
• Authors: Sang-Wook Kim; Kanghyun Song; Young-Eun Yoo; Seok-Woo Son; Su-Jong Jeong
• Keywords: Quantile; Quantile regression; Trend analysis

This study explores the long-term trends of extreme temperatures 270 observation stations in East Asia (China, Japan, and Korea) for 1961-2013. The 5th percentile daily minimum (TN05%) 95th maximum (TX95%), derived from quantile regression, are particularly examined term their linear nonlinear trends. warming TN05% typically stronger than those TX95% with more significant winter summer most stations. In both seasons, tend to amplify latitudes. trends, quantified by 2SUPnd/SUP-order polynomial fitting, exhibit different structures seasons. While were accelerated time, underwent weakening since 2000s. These results suggest that temperature not homogeneous time space.