기후변화 취약성 지수 산출을 위한 한반도 관측 기후 특성 분석
Analysis of Climate Characteristics Observed over the Korean Peninsula for the Estimation of Climate Change Vulnerability Index
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Climate vulnerability index is usually defined as a function of the climate exposure,sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature,and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed,and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability,implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend,suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the Climate vulnerability index is usually defined as a function of the climate exposure,sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature,and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed,and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability,implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend,suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.
Abstract
Climate vulnerability index is usually defined as a function of the climate exposure,sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature,and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed,and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability,implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend,suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the Climate vulnerability index is usually defined as a function of the climate exposure,sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature,and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed,and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability,implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend,suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.
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