이 연구는 지리산에 서식하는 반달가슴곰의 동면일과 동면기간 동안의 기온과의 관계를 밝히기 위해 조사되었다. 조사 결과, 동면 시작일은 평균 12월 7일이었으며, 동면 해제일은 4월 20일로 나타났으며, 출산한 암컷의 동면일은 167.8±22.6일이 었다. 동면 5일 전의 기온은 0.6±4.1℃였고, 동면 기간 동안 기온은 1.3±2.6℃, 동면 해제 5일 전의 기온은 12.6±3.1℃이 있다. 수컷과 출산을 하지 않은 암컷의 동면일은 각각 113.6±25.8일, 120.4±25.7일이었으며, 이들 그룹의 동면 5일 전의 평균 기온은 각각 –1.8±3.9℃, 2.1±4.2℃, 동면기간의 기온은 –0.4±2.4℃, -0.2±1.6℃, 동면 해제 5일전의 기온은 7.8±4. 4℃, 7.8±3.6℃였다. 이러한 결과로 볼 때 새끼를 출산한 암컷은 출산을 하지 않은 암컷과 수컷에 비해 동면 일수와 기온은 높은 것으로 나타났는데 이는 동면기간 새끼를 양육하는 과정에서 발생한 것이라 판단된다. 생애주기별 그룹에 대한 동면일수와 평균기온은 각 그룹간의 평균적인 차이가 없는 것으로 나타났다. 이번 연구를 통해 지리산에 서식하는 반달가슴곰의 구체적인 동면시기와 동면기간의 기온에 대해서 파악할 수 있었으며, 기온에 따른 성별, 출산한 암컷, 생애주기 그룹간의 어떠한 차이가 있는지 등 동면기 고유 행동특성이 밝혀졌다는 점에서 연구의 의의가 있다. 이러한 결과는 국제적 멸종위기종인 반달가슴곰의 겨울과 봄 시기에 인간과의 충돌방지와 보전 관리계획 수립 시 널리 활용될 것이다.

최근 기후에 대한 관심이 증가하면서 전국단위 뿐만 아니라 지역 단위에서도 기후 지도가 필요하게 되었다. 본 연구에서는 기상청에서 제공하고 있는 무인자동 기상관측장비(AWS) 자료와 LANDSAT 8호 열적외선 영상을 이용하여 지상 기온 분포도를 제작하는 과정을 제시하였다. 지상 기온 분포도 제작을 위하여 기존에 사용되었던 AWS 자료의 공간 보간 기법, 열적외선 영상으로 부터 지표 온도 추출 기법, AWS 자료와 위성영상을 이용한 지상 기온 추출 기법을 비교하고, 지상 기온 분포도에 적합한 지도 제작 기법을 파악하였다. 본 연구의 결과 지상 기온 분포도 제작을 위해 AWS 자료와 위성영상을 이용한 지상 기온 추출 기법이 가장 적합한 것으로 나타났다. 본 연구에서 제시한 과정을 통하여 다양한 지역단위의 기후 지도를 제작할 수 있을 것으로 예상된다.

We studied the distribution of air temperature using the high density urban climate observation network data of Daegu. The observation system was established in February 2013. We used a total of 38 air temperature observation points (23 thermometers and 18 AWSs). From the distribution of monthly averaged air temperatures, air temperatures at the center of Daegu were higher than in the suburbs. The daily minimum air temperature was more than or equal to 25℃ and the daily maximum air temperature was more than or equal to 35℃ at the elementary school near the center of Daegu. Also, we compared the time elements, which are characterized by the diurnal variation of surface air temperature. The warming and cooling rates in rural areas were faster than in urban areas. This is mainly due to the difference in surface heat capacity. These results indicate the influence of urbanization on the formation of the daily minimum temperature in Daegu.

Regional climate simulations for the CORDEX East Asia domain were conducted between 1981 and 2100 using five models to project future climate change based on RCP2.6, 4.5, 6.0, and 8.5 scenarios. By using the ensemble mean of five model results, future changes in climate zones and four extreme temperature events of South Korea were investigated according to Köppen-Trewartha’s classification criteria. The four temporal periods of historical (1981-2005), early future (2021-2040), middle future (2041-2070), and late future (2071-2100) were defined to examine future changes. The analysis domain was divided into 230 administrative districts of South Korea. In historical (1981-2005) period, the subtropical zones are only dominant in the southern coastal regions and Jeju island, while those tend to expand in the future periods. Depending on the RCP scenarios, the more radiative forcing results in the larger subtropical zone over South Korea in the future. The expansion of the subtropical zone in metropolitan areas is more evident than that in rural areas. In addition, the enlargement of the subtropical zone in coastal regions is more prominent than that of in inland regions. Particularly, the subtropical climate zone for the late future period of RCP8.5 scenario is significantly dominant in most South Korea. All scenarios show that cold related extreme temperature events are expected to decrease and hot related extreme temperature events to increase in late future. This study can be utilized by administrative districts for the strategic plan of responses to future climate change.

We analyzed diurnal variations in the surface air temperature using the high density urban climate observation network of Daegu in summer, 2013. We compared the time elements, which are characterized by the diurnal variation of surface air temperature. The warming and cooling rates in rural areas are faster than in urban areas. It is mainly due to the difference of surface heat capacity. In addition, local wind circulation also affects the discrepancy of thermal spatiotemporal distribution in Daegu. Namely, the valley and mountain breezes affect diurnal variation of horizontal distribution of air temperature. During daytimes, the air(valley breeze) flows up from urban located at lowlands to higher altitudes of rural areas. The temperature of valley breeze rises gradually as it flows from lowland to upland. Hence the difference of air temperature decreases between urban and rural areas. At nighttime, the mountains cool more rapidly than do low-lying areas, so the air(mountain breeze) becomes denser and sinks toward the valleys(lowlands). As the result, the air temperature becomes lower in rural areas than in urban areas.

This paper evaluates the applicability of a simple kriging with local means(SKLM) for highresolution spatial mapping of monthly mean temperature and rainfall in South Korea by using AWS observations in 2013 and elevation data. For an evaluation purpose, an inverse distance weighting(IDW) which has been widely applied in GIS and cokriging are also applied. From explanatory data analysis prior to spatial interpolation, negative correlations between elevation and temperature and positive correlation between elevation and rainfall were observed. Bias and root mean square errors are computed to compare prediction performance quantitatively. From the quantitative evaluation, SKLM showed the best prediction performance in all months. IDW generated abrupt changes in spatial patterns, whereas cokriging and SKLM ref lected not only the topographic effects but also the smoothing effects. In particular, local characteristics were better mapped by SKLM than by cokriging. Despite the potential of SKLM, more extensive comparative studies for data sets observed during the much longer time-period are required, since annual, seasonal, and local variations of temperature and rainfall are very severe in South Korea.

Agreement in the vertical profiles of the temperature trends from radiosonde observation (HadAT) and four kinds of reanalysis dataset (ERA40, ERA-I, NCEP-DOE, and 20CR) are examined for the period of 1979-2000. There are noticeable spread among reanalysis and observation datasets in the temperature trend depending on region and vertical level. East Asia shows large discrepancy among datasets, while Europe shows relatively good agreement. Generally, biases in temperature trends are larger in the upper troposphere (above 300 hPa) than in the lower and middle troposphere. Comprehensive comparison of the long-term temperature trends among reanalyses is made for horizontal distributions with height, latitude-pressure cross-sectional distributions, zonally-averaged meridional distributions with height, and area-averaged vertical profiles in both DJF and JJA. Consequently, we find that the degree of agreement among reanalyses significantly varies with vertical level, region, and season. The highest discrepancy is found over southern high-latitudes and in the upper troposphere over southern tropics. In the tropical upper troposphere above 200 hPa, observation (HadAT) shows cooling trend increases with height, but three reanalyses show warming trends except NCEP-DOE reanalysis in which cooling trend is overestimated. In conclusion, discrepancies in the vertical profiles of long-term temperature trends among four kinds of reanalysis datasets are quite large, and then a scrupulous approach should be needed when reanalysis dataset is used for climate change study.

This paper generated time-series temperature maps and analyzed the characteristics of temperature distributions from monthly average temperature observations between 2010 and 2011 in Jirisan areas using topographic data and geostatistics. From variogram modeling, all months except May to August showed that the spatial variability of temperature was the greatest along the direction perpendicular to coasts. Monthly temperature has negative correlations with elevation and distances from coasts and especially the correlation between temperature and distances from coasts was very weak in summer like the variogram modeling result. For temperature distribution mapping, kriging with a trend and ordinary kriging were separately applied as a univariate kriging algorithm by considering the spatial variability structures of temperature. Simple kriging with varying local means was applied as a multivariate kriging algorithm for integrating topographic data sets. From the cross validation results, the use of topographic data in spatial prediction of temperature showed the improved predictive performance, compared with univariate kriging. This improvement in predictive performance was dependent mainly on mean and variation values of monthly temperature and the spatial auto-correlation strength of residuals, as well as the correlation between topographic data and temperature. Based on these analysis results, spatial variability analysis using variogram is effectively used to account for spatial characteristics of monthly temperature and the correlation with topographic data. Topographic data can also be a useful information source for reliable temperature mapping.

최근 국지기후 특성을 분석할 수 있는 고해상도 기후자료 산출의 필요성이 증가하고 있다. 이 연구에서는 지상관측소의 관측치를 이용한 고해상도의 기온 및 강수 분포도 작성에 고도자료를 통합한 공동크리깅 내 삽기법의 적용 가능성을 검토하였다. 이를 위하여 2007년 1월, 4월, 8월, 10월에 관측된 428개 자료와 1km 해상도의 수치표고모델 자료를 이용하여 월평균기온 및 월강수량 분포도를 작성하였으며, 거리만의 함수인 역 거리가중 기법을 적용한 결과와 비교하였다. 작성된 월평균기온 및 월강수량 분포도에서의 추정값과 107개 검증 지점의 관측자료 사이 편이(bias)와 평균제곱근오차(RMSE)를 분석한 결과 역거리가중 결과에 비해 공동크리깅 결과가 모두 감소한 것으로 나타났다. 이는 역거리가중에 비하여 지형효과를 반영하는 공동크리깅이 고해상도의 기후자료 산출에 더 효과적임을 보여준다.

In order to clarify the impact of regional warming on the meteorological field and air quality over southeastern part of Korean Peninsula, several numerical experiment were carried out. Numerical models used in this study are WRF for the estimate the meteorological elements and CMAQ for assessment of ozone concentration. According to the global warming impact, initial air temperature were changed and its warming rate reach at 2 degree which was based on the global warming scenarios provided by IPCC. The experiments considering the global warming at initial stage were presented as case T_UP. Air temperature over inland area during night time for case T_UP is higher than that for Base case. During time since the higher temperature over inland area is maintained during daytime more intensified sea breeze should be induced and also decrease the air temperature in vicinity of coast area. In case of T_UP, high level concentrations ozone distribution area was narrowed and their disappearance were faster after 1800LST. As a results, wind and temperature fields due to the global warming at initial stage mainly results in the pattern of ozone concentration and its temporal variation at South-Eastern Part of the Korean Peninsula.

본 연구는 1998년부터 2004년까지 65개의 지상관측소와 309개의 AWS 지점의 일 최고 기온, 일 최저 기온, 일교차 자료를 이용하여 한반도의 기온 분포의 특성을 분석하고 인자 및 군집분석을 통하여 지역구분을 시도하였다. 우리나라 기온의 공간 분포는 기온 자료에 따라 다르게 나타난다. 일 최고 기온은 고도가 높은 산지를 제외하고 남부지역으로 갈수록 높은 기온 분포를 보이며, 일 최저 기온은 지형과 해양의 영향을 많이 반영하며, 일교차는 해양과 대륙의 분포에 의한 공간 패턴을 보인다. 인자분석을 통해 고유값 1.0이 넘는 3개의 인자와 이를 바탕으로 군집분석을 하여 5개의 지역으로 구분하였다. 이러한 지역구분은 국지 예보 구역 설정을 위한 연구와 국지규모에서의 기후 시나리오 작성 및 기후변화 영향평가를 위한 중요한 기초 자료로 활용될 것이다.

종관기상자료만으로 충족시킬 수 없는 농업분야 국지기상정보 수요에 대처하기 위해 지형기후 관계식에 의거한 제주도 전역의 정밀기후 추정 및 표출방법을 개발하였다. 먼저 도전역을 250m 간격의 직교격자로 구획하고 교차점의 해발고도를 지형도상에서 판독하여 사방 1km 지역(단위격자)의 평균해발고도, 평균경사도, 그리고 평균 경사방향 등 지형내자를 계산, 정량화하였다. 18개의 기존 및 신설 기상관측소가 위치한 단위격자의 지형 인자값과 실제 관측된 일최저기온값을 중회귀분석하여 지형일기온 관계식을 도출하고 이로부터 미관측 격자에 대하여 주정치를 계산하였다. 구체적으로 겨울철 일최저기온에 대하여 3개의 전형적인 기압계 유형별로 최적 추정식을 만들어 해안지대에 위치한 제주 및 서귀포 관측자료와 기압계 유형판별만으로 도전역의 일최저온 분포 예측을 가능케 하였다.

The climate of a given region is determined by the combination of the various climatic elements. But among them, the temperature is the most important element to classify the climatic type. The author attempted to classify the climatic types in Korea by making a analysis of the characteristics of temperature distribution. To accomplish the study, the author analyzed the daily and yearly range of temperature, the warmest and coldest months, continentality and oceanicity, thermal anomaly, and relative temperature, etc. The data of 153 weather stations are used for the analysis of the above five criteria. As a result of the study, the climate of Korea can be divided into three types, namely, the continental, coastal and intermediate(or transitional) type. The Pronounced continental type is appeared in the northern part of highland area. And the coastal type is limited to the east and south coast areas, and the southern part of the west coast area. The continentality is larger, and the oceanicity smaller, than those of Siberia, Mongolia and the inland area of China where the continental climate is most remarkable in the world. The reason why the west coast area is more continental than the east coast area may be due to the terrain effect and the warm current going north along the east coastline.