Analysis of Changes in Extreme Temperatures Using Quantile Regression

This study examines the changes in regional extreme temperature in South Korea using quantile regression, which is applied to analyze trends, not only in the mean but in all parts of the data distribution. The results show considerable diversity across space and quantile level in South Korea. In winter, the slopes in lower quantiles generally have a more distinct increase trend compared to the upper quantiles. The time series for daily minimum temperature during the winter season only shows a significant increasing trend in the lower quantile. In case of summer, most sites show an increase trend in both lower and upper quantiles for daily minimum temperature, while there are a number of sites with a decrease trend for daily maximum temperature. It was also found that the increase trend of extreme low temperature in large urban areas (0.80°C decade−1) is much larger than in rural areas (0.54°C decade−1) due to the effects of urbanization.