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초록·키워드 목차

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<SUP>th</SUP>, 50<SUP>th</SUP>, and 5<SUP>th</SUP> percentiles of daily maximum (T<SUB>max</SUB>) and minimum temperatures (T<SUB>min</SUB>) by using quantile regression method. It is found that in most stations linear trends of T<SUB>max</SUB> and T<SUB>min</SUB> are generally stronger in winter than in summer, and warming trend of the 5<SUP>th</SUP> percentile temperature (cold extreme) is stronger than that of the 95<SUP>th</SUP> 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<SUP>th</SUP> and 50t<SUP>h</SUP> percentiles of summer T<SUB>min</SUB> 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. #Quantile regression #extreme surface air temperature #long-term trend

Abstract
1. 서론
2. 자료 및 방법
3. 1차(선형) 추세 분석
4. 2차 추세 분석
5. 유의성 검정
6. 결론
REFERENCES

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