• 한국지구과학회지
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• 제27권2호
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• pp.188-197
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• 2006

1924년부터 2004년까지 제주관측지점 자료를 이용하여 제주의 기온과 강수량의 변동 특성을 조사하였다. 지난 81년 동안 연평균 기온은 $0.02^{\circ}C/year$ 정도로 증가하였으며 1980년 이후에는 $0.05^{\circ}C/year$로 이전보다 큰 폭으로 증가하였다. 최저기온의 증가가 최고기온 증가보다 크게 나타나 결과적으로 최저기온의 상승이 평균기온의 상승을 유발한 것으로 보인다. 기온과 강수의 특이기후 발생빈도 또한 조사하였다. 최고기온 특이값 빈도에 대한 기온편차는 지구온난화경향과 더불어 1980년대에 증가하였으며, 최저기온 특이값은 여름과 겨울 동안 감소하는 것으로 나타났다. 강수일수는 감소하고 일강수량이 80 mm 이상인 호우일수의 빈도는 증가하여 강수강도가 강화되는 것으로 나타났다.

• Ocean and Polar Research
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• 제28권4호
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• pp.415-423
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• 2006

Interannual variation and long-term trends of coastal sea surface temperature (SST) in Korea were investigated by analyzing 27 coastal SST time series from 1969 to 2004. Long-term linear increasing trend was remarkable with the rate over $0.02^{\circ}C/year$ at almost all the stations. The slope of long-term linear trend was larger at the stations along the eastern coast than in the western and southern regions. It was also noticeable that there was a common tendency of interannual variability with the period of 3-5 years at most of the stations. SST was lower in the 1970's and early 1980's while it was higher in the 1990's and early 2000's after the increase in the late 1980's. The pattern of the interannual variability of SST was similar to that of air temperature. Increasing trend of minimum SST in winter was obvious at most stations na it was larger along the eastern coast, while the linear trend of maximum SST in summer was less definite. Therefore, the decreasing tendency of annual amplitude was mainly due to the increasing tendency of SST in winter.

• 대기
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• 제33권1호
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• pp.1-20
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• 2023

Holding the longest observation data from April 1904, Busan is one of the essential points to understand the climate variability of the Korean Peninsula without missing data since implementing the modern weather observation of the South Korea. Busan is featured by coastal areas and affected by various climate factors and fluctuations. This study aims to investigate climate variability and changes in climatic variables, extremes, and several weather indexes. The statistically significant change points in daily mean rainfall intensity and temperature were found in 1964 and 1965. Based on the change point detection, 117 years were divided into two periods for daily mean rainfall intensity and temperature, respectively. In the long-term temperature analysis of Busan, the increasing trend of the daily maximum temperature during the period of 1965~2021 was larger than the daily mean temperature and the daily minimum temperature. Applying Ensemble Empirical Mode Decomposition, daily maximum temperature is largely affected by the decadal variability compared to the daily mean and minimum temperature. In addition, the trend of daily precipitation intensity from 1964~2021 shows a value of about 0.50 mm day^-1, suggesting that the rainfall intensity has increased compared to the preceding period. The results in extremes analysis demonstrate that return values of both extreme temperatures and precipitation show higher values in the latter than in the former period, indicating that the intensity of the current extreme phenomenon increases. For Wet-Bulb Globe Temperature (effective humidity), increasing (decreasing) trend is significant in Busan with the second (third)-largest change among four stations.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.257-264
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• 2020

Objective: To investigate test-retest reliability and responsiveness of Equivital Lifemonitor and photoplethysmography based wristwatch tools in assessing physiological parameters during a simulated fatigue task. Methods: Ten university students (Mean age, 30.6 ± 1.7 years) participated in this pilot study. Participants were asked to perform a 30-minute of a simulated fatigue task in an experimental setup in a lab. The physiological parameters (e.g., heart rate, heart rate variability, respiratory rate, electrodermal activity, and skin temperature) were measured at baseline and immediately after the fatigue task. An intraclass correlation coefficient (ICC2,1) was used to evaluate the test-retest reliability of each tool in assessing physiological measures. In addition, the responsiveness of each tool to measure changes from baseline to posttest was calculated using a standardized response mean. Results: The Equivital Lifemonitor has shown good to excellent test-retest reliability for the assessment of heart rate (ICC, 0.97), heart rate variability (ICC, 0.86), respiratory rate (ICC, 0.77), and local skin temperature (ICC, 0.76). However, photoplethysmography based wristwatch showed moderate to good test-retest reliability for the assessment of heart rate (ICC, 0.71), heart rate variability (ICC, 0.73), electrodermal activity (ICC, 0.80), and skin temperature (ICC, 0.72). A large standardized response mean (>0.8) indicates that both tools can capture the changes in heart rate, heart rate variability, respiratory rate, skin temperature, and electrodermal activity after a 30-minute of fatigue task. Conclusions: The Equivital Lifemonitor and photoplethysmography based wristwatch devices are reliable in measuring physiological parameters after the fatigue task. Additionally, both devices can capture the fatigue response after a simulated construction task. Future field studies with a larger sample should investigate the sensitivity and validity of these tools in measuring physiological parameters for fatigue assessment at construction sites.

• 한국수자원학회논문집
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• 제43권5호
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• pp.483-493
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• 2010

본 연구에서는 국내 기상관측소 중 관측년수가 30년 이상인 관측소 63개 지점에 대한 5개의 수문기상수문인자 즉, 연강수량, 연강수일수, 연평균기온, 연평균상대습도, 연일조시간 자료를 각 지점별로 수집하고, 통계학적 기법인 Wald-Wolfowitz 검정, Mann-Whitney 검정을 이용하여 변동성 분석과 Wavelet Transform을 이용하여 주기성을 분석하였다. 변동성 분석결과 연평균상대습도, 연평균기온에서 공통적으로 변동성이 나타났으며, 연강수량, 연강수일수, 연일조시간은 지역에 따라 상이한 결과를 보였다. 주기성 분석에서는 연강수량, 연강수일수에서 각 지점별로 주기가 나타났으나, 연평균기온, 연평균상대습도, 연일조시간에서는 뚜렷한 주기가 나타나지 않았다.

• Communications for Statistical Applications and Methods
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• 제18권1호
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• pp.1-12
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• 2011

우리는기온의변화와기온변동성을알아보기위해한국의다섯지점에서측정한월평균기온, 일최고기온, 일최저기온에 대한 50년간의 장기시계열을 분석하였다. 그 결과 기온은 1960년대에 비해 2000년대에 월평균기온을 기준으로 울산은 연평균 $1.26^{\circ}C$, 서울은 $1.19^{\circ}C$ 상승하였으나 추풍령은 $0.13^{\circ}C$ 상승하여 지점별로 큰 차이가 있었다. 또 계절별로 다른 현상을 나타내기도 하였다. 그러나 기온변동성에 대한 분석결과, 변동성의 증가는 확인할 수 없었다.

• 한국기후변화학회지
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• 제9권2호
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• pp.171-179
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• 2018

The causal relationship between El Nino-Southern Oscillation (ENSO) and winter climate variability in Korea is tested by analyzing Korea Meteorological Administration Automatic Synoptic Observing System datasets for the past 59 years. Consistent with previous studies, positive phase of ENSO (El Nino) tends to cause warmer temperature and heavier precipitation in Korea in early winter with three-week lead time. This causality is quantified by performing Granger causality test. It turns out that ENSO explains an additional 9.25% of the variance of early-winter temperature anomalies in Korea, beyond that already provided by temperature itself. Likewise, 22.18% additional information is gained to explain early-winter precipitation variance by considering ENSO. This result, which differs from simple lead-lag correlation analysis, suggests that ENSO needs to be considered in predicting early-winter surface climate variability in Korea.

• Spatial Information Research
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• 제16권4호
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• pp.467-478
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• 2008

본 연구에서는 서울지역에서 기온($^{\circ}C$) 및 강수(mm)의 시 공간 구조 분석 및 변화경향과 변이성을 도출하였다. 1997년 1월부터 2006년 12월까지의 기상청에서 제공하는 31개 자동기상관측망의 기온 및 강수자료를 이용하였으며, 미 관측지점의 값을 추정하기 위하여 거리자승역산가중 (IDSW: Inverse Distance Squared Weighing)을 적용하여 보간 하였다. 기온과 강수량의 변이성을 평가하기 위하여 연평균 및 더운 날과 추운 날의 빈도를 알아보았다. 그 결과 최고 기온 값은 1999년의 $32.80^{\circ}C$, 최저기온은 2001년의 $-19.94^{\circ}C$로 나타났다. 더운 날의 빈도가 가장 많았던 해는 79일을 기록한 2006년이며, 2004년과 2005년에도 비슷한 기록을 보였다. 추운날의 빈도가 가장 많았던 해는 105일을 기록한 2001년이다. 또한 기온과 강수량 모두 지난 10년 동안 기온이 약 $1.03^{\circ}C$, 강수량이 약 483.09mm 증가한 것으로 나타났다. 과거 10년 동안 기온변이의 경우 고도가 높은 산림지역과 고도가 낮은 주거지역에서 차이가 크게 나타난 반면, 강수량의 경우 지형 및 토지이용에 따른 변이성의 차이가 미미한 것으로 나타났다.

• 한국지역지리학회지
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• 제4권1호
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• pp.1-13
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• 1998

본 연구는 전국의 66개 관측지점을 대상으로 $1961{\sim}1990$년의 일 평균 기온을 월별로 변동률을 산출하여 기후특성을 고찰하였다. 우리나라의 봄은 4 5월, 여름은 $6{\sim}9$월, 가을은 10월, 겨울은 $11{\sim}3$월로 구성된다. 기온 변동률의 변화는 겨울에 가장 크게 나타나고 여름에 가장 작게 출현하며, 봄과 가을은 그 중간이다. 기온 변동률의 분포는 영서 지방에서 남해안과 서해안 지방으로 이동함에 따라 감소 경향을 보이는데, 봄 한여름 한겨울에 뚜렷하다. 한국의 기후 지역은 크게 중부형과 남부형으로 구분되고, 서안형 내륙형 동안형 남해안형으로 세분된다. 여름의 지역 구분은 특이하나 여타 계절의 구분 형태는 비슷하다.

• Ocean and Polar Research
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• 제30권3호
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• pp.277-287
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• 2008

We collected information on seasonal and interannual variability of surface chlorophyll a concentration between 1997-2007 from the Northwest Pacific Ocean. Satellite data were used to acquire chlorophyll a and sea surface temperature from six regions: East Sea/Ulleung Basin, East China Sea, Philippin Sea, Warm Pool region, Warm Pool North region, and Warm Pool East region. Mixed layer depth (MLD) was calculated from temperature profiles of ARGO floats data in four of the six regions during 2002-2007. In the East Sea/Ulleung Basin, seasonal variability of chlorophyll a concentration was attributed to seasonal change of MLD, while there was no significant relationship between chlorophyll a concentration and MLD in the Warm Pool region. Interannual anomaly in sea surface temperature were similar among the East Sea, East China Sea, Philippin Sea, and Warm Pool North region. The anomaly pattern was reversed in the Warm Pool East region. However, the anomaly pattern in the Warm Pool region was intermediate of the two patterns. In relation to chlorophyll a, there was a reversed interannual anomaly pattern between Warm Pool North and Warm Pool East, while the anomaly pattern in the Warm Pool region was similar to that of Warm Pool North except for the El $Ni\tilde{n}o$ years (1997/1998, 2002/2003, 2006/2007). However, there was no distinct relationship among other seas. Interestingly, in the Warm Pool and Warm Pool East regions, sea surface temperature showed a pronounced inverse pattern with chlorophyll a. This indicates a strong interrelationship among sea surface temperature-MLD-chlorophyll a in the regions. In the Warm Pool and Warm Pool East, zonal distribution of chlorophyll a concentration within the past 10 years has shown a good relationship with sea surface temperature which reflects ENSO variability.