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

다국어 초록 (Multilingual 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 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.

참고문헌 (Reference)

1 김철희, "한반도 기후 변화 적응을 위한 취약성 지수 산정에 관한 고찰" 한국환경과학회 20 (20): 789-798, 2011

2 김연희, "한반도 강수의 양극화 현상" 기후연구소 5 (5): 1-15, 2010

3 고재경, "지방자치단체 기후변화 취약성 유형 및 적응방안 연구:경기도 사례를 중심으로" 서울행정학회 22 (22): 93-118, 2011

4 김은화, "정규지상관측자료를 이용한 기후변 화 취약성 지수 산정" 부산대학교 2010

5 유정아, "전국 지자체 단위 기후변화 부문별 취약성평가 표준화 방법론 개발" 154-, 2011

6 최현아, "시･공간정보기반 기후변화 취약성 평가" 한국공간정보시스템학회 11 (11): 63-69, 2009

7 진영훈, "남방진동지수의 범주구분에 의한 강수량에 미치는 ENSO 영항의 통계학적 분석" 대한토목학회 25 (25): 443-450, 2005

8 기상연구소, "기후변화협약대응 지역기후 시 나리오 산출기술개발(III)" 60-69, 2004

9 배덕효, "기후변화에 따른 홍수취약성 평가와 사례분석" 344 : 20-31, 2010

10 이재범, "기후변화에 따른 대기 질 취약성 평가" 363-365, 2010

11 한국환경정책·평가연구원, "기후변화 취약성 평가지표의 개발 및 도입방안" 4-52, 2008

12 국립환경과학원, "기후 및 대기환경 통합시스 템 구축 및 운영(II)" 3-27, 2009

13 국립환경과학원, "기후 및 대기환경 통합시스 템 구축 및 운영" 63-69, 2008

14 국립환경과학원, "기후 및 대기환경 통합 모델 링 구축 및 운영(III)" 3-10, 2010

15 류상범, "기상청 기 후자료의 균질성 문제(I):관측지점의 이전" 16 (16): 215-223, 2006

16 경기개발연구원, "경기도 기후변화 취약성 평가 연구" 3-100, 2009

17 Moss, R. H., "Vulnerability to climate change: A quantitative approach" U.S. Department of Energy. 2001

18 Trenberth, K. E., "Trends and variability in columnintegrated atmospheric water vapour" 24 : 741-758, 2005

19 Collins, W. D., "The formulation and atmospheric simulation of the Community Atmosphere Model version 3(CAM3)" 19 : 2144-2161, 2006

20 Wehbe, M. B., "Social methods for assessing agricultural producer’s vulnerability to climate variability and change based on the notion of sustainability, Assessments of Impacts and Adaptations of Climate Change Working Papers" 2005

21 Cutter, S. L., "Social Vulnerability to Environmental Hazards" 84 (84): 242-261, 2003

22 USEPA, "Science Algorithms of the EPA Models-3 Community Multi-scale Air Quality(CMAQ) Modeling System" Office of Research and Development 1999

23 Byun, D. W, "Science Algorithms of the EPA Models-3 Community Multi-scale Air Quality (CMAQ) Modeling System, EPA Report" NERL, Research Triangle Park 1999

24 Wentz,F.J., "Precise climate monitoring using complementary satellite data sets" 403 : 414-416, 2000

25 Dai,A., "Precipitation characteristics in eighteen coupled climate models" 19 : 4605-4630, 2006

26 Colman, R. A., "On the structure of water vapour feedbacks in climate models" 31 : 21109-, 2004

27 Bey, I., "Global modeling of tropospheric chemistry with assimilated meteorology:Model description and evaluation" 106 (106): 073-095, 2001

28 IPCC, "Climate Change 2007: Impacts, adaptation, and vulnerability, Foruth Assessment Report" Cambridge University Press 2007

29 IPCC, "Climate Change 2001: Impacts, adaptation, and vulnerability, Third Assessment Report" Cambridge University Press 2001

30 Soden, B. J, "An assessment of climate feedbacks in coupled ocean-atmosphere models" 19 : 3354-3360, 2006

31 UNDP, "Adaptation policy frameworks for climate change: Developing strategies, policies, and measures" Cambridge University Press 2005

32 Grell, G. A., "A description of the Fifth- Generation Penn State/NCAR Mesoscale Model (MM5), NCAR Tech" 138-, 1995