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http://dx.doi.org/10.14191/Atmos.2014.24.3.379

Linear and Nonlinear Trends of Extreme Temperatures in Korea  

Kim, Sang-Wook (School of Earth and Environmental Sciences, Seoul National University)
Song, Kanghyun (School of Earth and Environmental Sciences, Seoul National University)
Kim, Seo-Yeon (School of Earth and Environmental Sciences, Seoul National University)
Son, Seok-Woo (School of Earth and Environmental Sciences, Seoul National University)
Franzke, C. (Meteorologisches Institut Universitat Hamburg)
Publication Information
Atmosphere / v.24, no.3, 2014 , pp. 379-390 More about this Journal
Abstract
This study explores the long-term trends of surface air temperatures in 11 KMA stations over the period of 1960~2012. Both linear and nonlinear trends are examined for the $95^{th}$, $50^{th}$, and $5^{th}$ percentiles of daily maximum ($T_{max}$) and minimum temperatures ($T_{min}$) by using quantile regression method. It is found that in most stations linear trends of $T_{max}$ and $T_{min}$ are generally stronger in winter than in summer, and warming trend of the $5^{th}$ percentile temperature (cold extreme) is stronger than that of the $95^{th}$ percentile temperature (warm extreme) in both seasons. The nonlinear trends, which are evaluated by the second order polynomial fitting, show a strong nonlinearity in winter. Specifically, winter temperatures have increased until 2000s but slightly decreased afterward in all percentiles. This contrasts with the $95^{th}$ and $50^{th}$ percentiles of summer $T_{min}$ that show a decreasing trend until 1980s then an increasing trend. While this result is consistent with a seasonal dependence of the recent global warming hiatus, most of the nonlinear trends are statistically insignificant, making a quantitative attribution of nonlinear temperature trends challenging.
Keywords
Quantile regression; extreme surface air temperature; long-term trend;
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Times Cited By KSCI : 1  (Citation Analysis)
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