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복합극한기후지수를 이용한 우리나라 여름철과 겨울철 극한기후현상의 공간 범위 변화와 미래전망 분석
민숙주,최영은,문자연,김유진,김맹기,최다솜,문희수 건국대학교 기후연구소 2021 기후연구 Vol.16 No.1
This paper has presented not only the spatial coverage change of climate extreme events in summer and winter seasons during the period of 2000-2017, but also their future projections in 2021-2100, South Korea through analysis of a Combined Climate Extreme Index (CCEI). The CCEI quantifies the spatial coverage of climate extreme events based on a set of five indicators. MK (Modified Korean)-PRISM (Parameter-elevation Regression on Independent Slopes Model)v1.2 (1×1km) and RCP scenario data (1×1km) were applied to CCEI. Results indicated that in average, 21.7% of the areas in the summer and 23.6% in the winter experienced climate extremes from 2000 to 2017 regardless of types of climate extreme events in South Korea. The summer of 2003 and 2009 was relatively cool and humid, while the summer of 2014 and 2015 was cool and dry and the summer of 2016 was warm and dry. The extreme events with much above normal maximum and minimum temperature during the study period were detected but not much below normal maximum and minimum temperature after 2015. For RCP2.6 and RCP8.5 scenarios, there were statistically significant trends with spatial coverage expansion of climate extreme events in the future. It might be concluded that climate extreme events in the summer and winter seasons were affected simultaneously by two or more indicators than a single indicator in South Korea.
우리나라 대표 기상관측지점의 지리적 특성 분류에 관한 연구
민숙주,최영은,허인혜,권재일,김정용,최다솜,정현서,박금보라 건국대학교 기후연구소 2024 기후연구 Vol.19 No.1
In this study, we classified 219 representative weather stations in the Republic of Korea based on geographical features such as altitude, distance from the coastal line, total population, population density, and urban-related land cover ratios, and analyzed climate characteristics by the classified categories. The representative weather stations were categorized into six groups: mountain, plain inland city, plain inland rural, coastal city, and coastal rural stations. The most prevalent group was plain inland rural stations with 41.6%, followed by plain inland city ones with 22.8%, coastal rural ones with 21.9%, coastal city ones with 9.1%, and mountain ones with 4.6%. The climate characteristics among these geographical groups revealed significant differences (α=0.05) for annual average temperature except for coastal city and coastal rural group. However, annual precipitation was only significantly different between plain inland city and plain inland rural ones, and between coastal city and plain inland rural ones. The analyses of hot extreme climates revealed distinct differences among the six groups. At plain inland city ones, heat wave days were notably greater (15.8 days) than mountain ones (3.3 days), indicating the effect of city and elevation. Conversely, cold wave days were significantly much more in mountain stations (18.3 days) than coastal rural (1.5 days) and city (1.3 days) groups largely due to the modulation of warmer oceans in winter, elevation and city. The results of this study might be used for basic information for establishing future climate change adaptation strategies in the Republic of Korea.
우리나라 겨울철 온난화가 미래 산림 분포의 변화에 미치는 영향
민숙주,최영은,허인혜,최다솜,편도의,김정용,이도영 건국대학교 기후연구소 2022 기후연구 Vol.17 No.3
In this study, we examined the impacts of winter warming on the expected future forest change in the Republic of Korea (ROK) by analyzing winter temperature and the minimum temperature of the coldest month index (MTCI). The historical and future climate data from 60 Automated Synoptic Observing System (ASOS) stations, MK-PRISMv2.1, SSP1-2.6, and SSP5-8.5 scenarios were used. During the period of 1973-2020, the winter mean temperature increased by 0.3°C/10 years which was greater than the annual mean temperature (0.2°C/10 years) over the ROK with larger variabilities. In the far future (2081-2100), the winter mean temperature is expected to rise 2.9°C under the SSP1-2.6 scenario and 6.7°C under the SSP5-8.5, compared to those in the near future (2021-2040). The potential ratio of evergreen needle-leaved trees estimated by MTCI in ROK is projected to decrease with 13.9% under the SSP1-2.6 and 31.8% under the SSP5-8.5, except for the Pinus thunbergii which has higher MTCI. As a result of the overlapping climate types and MTCI, in the far future of the SSP1-2.6 scenario, the expected regions of Camellia japonica and the area of Cfa type were almost identical. Although the potential ratio of Camellia japonica in the far future of the SSP5-8.5 scenario is expanded to 57.5%, the coastal regions of the southern and Jeju areas in Cfa have been excluded from the Camellia japonica range due to rising the winter temperature.
민숙주(Sook-Ju Min),임은정(Eun-Jeong Lim),배인한(Ihn-Han Bae) 한국멀티미디어학회 2008 한국멀티미디어학회 학술발표논문집 Vol.2008 No.2
오늘날 우리 생활에서 한자ㆍ한자어ㆍ한문의 필요성은 매우 강조되고 있다. 이러한 시대적 상황에서 볼 때 한자 및 한문 학습에 있어서 교수ㆍ학습 방법의 개발을 통하여 정확하게 한자를 읽고 쓸 수 있게 가르치고 배우는 것이 절실하게 필요하다. 따라서 본 논문에서는 과거의 전통적인 한자 교육 방법에서 벗어나 신세대 학생들에게 맞는 모바일 한자 학습 콘텐츠를 제안한다. 이 모바일 한자 학습 콘텐츠는 초ㆍ중학생이 한자능력검정시험 7급 수준의 한자 학습을 목표로 개발한다.
도시지역 토지이용분류를 위한 1:1,000 수치지형도 활용에 관한 연구
민숙주(Min Sookjoo),김계현(Kim Kyehyun) 대한토목학회 2006 대한토목학회논문집 D Vol.26 No.1D
기존의 토지이용 분류방법은 현장조사에 의존하거나 항공사진 판독기법을 사용하므로 상대적으로 시간과 비용의 소요가 큰 편이다. 특히나 도시지역은 토지이용이 복잡하고 집약적이므로 위성영상을 활용해 분류하는데 한계가 있는 실정이다. 이러한 배경에서 본 연구에서는 1:1,000 수치지형도와 IKONOS 위성영상을 혼합 활용하는 토지이용 분류기법을 제기하였다. 본 연구에서 제기한 분류기법의 활용가능성을 파악하기 위하여 서울시 일부지역을 대상으로 실험분석을 수행하였으며, 그 결과 95%의 전체정확도와 14개의 토지이용 항목이 분류되었다. 실험분석의 결과로 미루어 본 연구에서 제기한 분류기법은 도시지역 토지이용분류에 적용 가능한 것으로 판단된다. Existing method of landuse classification using aerial photographs or field survey requires relatively higher amount of time and cost due to necessary manual work. Especially in urban area where the pattern of land use is densely aggregated, a land use classification using satellite image is more complex. In this background, this study proposes a landuse classification method to utilize 1:1,000 digital topographic data and IKONOS satellite image. To prove the possibility of this method, the method was applied to Seoul metropolitan area. The results shows the total accuracy of approximately 95% and 14 landuse classes extracted. Based on the results from the pi lot study, this method is applicable to land use classification in urban area.
AR6 대응 시나리오 기반 행정구역 전망정보 자동생산 방안 연구
최영은,민숙주,오충원,김유진,김민기,박미나,문자연 건국대학교 기후연구소 2019 기후연구 Vol.14 No.2
Cell based grid data of future temperature and precipitation produced with four RCP scenarios were converted into polygon based data for administrative districts using three simple vectorizing methods; (1) KMA Dong-Nae forecast point based, (2) areal ratio based and (3) central point based methods. The results were compared the existed KMA areal weight based methods to identify which methods were more efficient than others. Simple statistical methods such descriptive statistics, correlation coefficient, and Bland & Altman plots (B&A) were used to compare agreements between them. When central point and areal ratio based methods were applied to administrative districts of Eup-Myeon-Dong or some Gus, NULLs were found because their sizes are smaller than the cell of 1x1 km. Therefore, KMA Dong-Nae forecast point based methods were better when sizes of administrative districts are smaller than the cell size. For Do and Metropolitan cities, there were no greater differences among methods except for the KMA Dong- Nae forecast points. The greater the areas of administrative districts the more distortions from the KMA Dong-Nae forecast points because only KMA Dong-Nae forecast one point were used for the calculation. In conclusion, the KMA Dong-Nae forecast point based method was appropriate when sizes of administrative districts are smaller than the grid cell. For the greater areal sizes such as Do and Metropolitan cities, areal ratio and central point based methods were better.