• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.157-164
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• 2021

Wind and temperature were measured with a three-dimensional ultrasonic anemometer and the carbon dioxide concentration was measured using an infrared sensor in the tidal flat of Suncheon Bay. In general, as the temperature increases, the concentration of carbon dioxide increases, and as the temperature decreases, the carbon dioxide also decreases in the atmosphere. However, since photosynthesis declined immediately after the sunset, the concentration of carbon dioxide increased as the temperature decreased. In addition, near the high tide when the tidal flat is covered with seawater, the atmospheric turbulence was strong despite an increase in temperature, resulting in a decrease in carbon dioxide concentration. It is necessary to quantitatively evaluated the effects of photosynthesis, respiration and atmospheric turbulence on the change of carbon dioxide concentration over tidal flat ecosystems.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.35-49
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• 2014

In order to understand the impacts of surface characteristics and the distance from the urban heat island center to suburban areas on the mean night time air temperature, we analyzed GIS and AWS observational data. Spatial distributions of mean night time air temperature during the summer and winter periods of 2004-2011(six years) were utilized. Results show that the temperature gradients were different by distance and direction. We found high correlation between mean night-time air temperature and artificial land cover area within 1km and 200m radii during both summer(R=0.84) and winter(R=0.78) seasons. Regression models either from 1km and 200m land surface data explained the distribution of night-time temperature equally well if the input data had sufficient resolution with detailed attribute including building area and height.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.431-445
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• 2006

In this paper we review some methods for analyzing functional data and illustrate real application of functional data analysis. Representing methods for functional data by using basis function, analyzing functional variation by functional principal component analysis and functional linear models are reviewed. For a real application, we use temperature and precipitation data measured in Korea from the January of 1970 to the May of 2004. We apply functional principal component analysis for each data and test the significance of regional division done by using shining hours. We also estimate functional regression model for temperature and precipitation.

• Journal of Environmental Science International
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• v.7 no.2
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• pp.191-194
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• 1998

In this research, two stochastic models are considered to detect and estimate the effect of air temperature change due to Industrialization In Ulsan area. Using the monthly mean minimum air temperature anomalies, the data are divided Into pre-Industrialization part and Industrialization one for analysis. The ARM(autoregressive moving-average) model and intervention model have been applied to the data for the analysis. The results show that the variability of minimum temperature anomalies are very significant In 1989, and also significant In 1971 when the Industrialization have started. Therefore, It Is stochastically possible to estimate the time when the affection of Increase of the temperature concerning Industrialization to climate change In Usm area has happened.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.164-164
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• 2022

대기의 습한 정도는 기상 현상과 밀접한 관계를 가진다. 공기가 건조하면 가뭄이나 산불이, 반대로 습윤하면 홍수나 극한 강우가 내리기 쉽다. 산업화 이후 지구의 평균 기온이 상승하면서, 세계적으로 상대습도가 감소하는 경향성이 보고되고 있다. 이러한 경향이 우리나라에서도 확인되는지 파악하고자, 이 연구에서는 장기간에 걸친 상대습도 관측치가 존재하는 종관기상관측소 6개소의 자료를 분석하였다. 기온은 시간에 따라 증가하고, 포화 수증기압도 그에 따라 증가해온 것으로 나타났다. 하지만, 상대습도의 증감은 포화 수증기압뿐만 아니라 실제 수증기압의 변화에도 민감하게 반응한다. 우리는 실제 수증기압 변화의 원인을 수증기압에 영향을 주는 다양한 기후 변수들의 시계열 자료를 통해 분석해보았다. 우리나라 지역별로 상당한 변동성이 나타났는데, 대표적으로 동해안과 서해안 사이의 차이, 내륙과 해안의 차이에 대해 자세히 발표할 것이다.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.20 no.2
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• pp.79-82
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• 1984

Seasonal and secular variations of water temperature in Chungmu port were investigated with the data obtained from the Technical Reports(1976~1983) of Hydrographic Office. Monthly and annual range of water temperature were 2 to 8$^{\circ}C$ and 18 to 21$^{\circ}C$, respectively. The coefficients of variance of monthly mean water temperature were 0.015(February, 1976) to 0.208(December, 1980) and their values were smaller in the summer season than in the winter season. The result of harmonic analysis for investigating the seasonal variation of water temperature was T(t)=15.66+8.06 cos(10$^{\circ}$t-233.5)+0.92 cos(20$^{\circ}$t-216). The periods of secular variation were about 2 years and 3 years.

• Korean Journal of Environment and Ecology
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• v.31 no.2
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• pp.135-151
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• 2017

Waterbirds were surveyed once a week from Oct. 2015 to Apr. 2016 to study the conditions of temperature of staying waterbirds on Wonju-Stream. The population staying on Wonju-Stream was in inverse proportion to the temperature change; birds increased as the temperature went down, and showed the highest peak counts on the 16th(27-Jan) survey, which was the lowest in temperature. decreasing as the temperature rose. The total population of Wonju River water birds increased with increasing freezing rate in proportion to the freezing rate of nearby reservoirs and tributaries. To clarify the relation of the numbers of the birds to temperature fluctuation, the correlation of the first period of wintering (1st~16th) and that of the later period(17th~27th) as well as the whole period was surveyed, based on the 16th which was the lowest in temperature. While most wintering waterbirds showed a negative correlation to the temperature, Egretta garzetta, Phalacrocorax carbo, and Ardea cinerea were positive in temperature relativity. Anas poecilorhyncha was in the highest relation to temperature fluctuation showing (7D/H3A(r=-0.960, P<0.000000001)) at 1-16 correlation(Cor.), with the whole wintering waterbird species showing the maximum correlation at 4D/LA in the every correlation(1~27Cor.(r=-0.942, P<0.01), 1~16Cor.(r=-0.947, P<0.01), 16~27Cor.(r=-0.958, P<0.01)). Each waterbird showed the correlation to the temperature variation(AT, HT, LT) and th duration(1D~7D) depending on the species differently. Most species demonstrated a bigger correlation to the lowest temperature rather than to the highest temperature. During the first half period of the wintering with the temperature falling it showed a high correlation to the temperature at the duration of 4D~7D, While it was for D1~D3 during the next half period.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.186-186
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• 2015

본 연구에서는 해안도시(부산광역시 수영구) 지역의 토지이용도와 미기상인자를 고려하여 증발산량을 산정하였으며, 증발산량 변동에 대한 미기상인자의 영향성을 구명하였다. 수영구 지역의 토지이용도와 미기상인자는 2001년 12월부터 2011년 11월에 관측된 일별 자료를 사용하였다. 토지이용도는 불투수(건물, 도로 등) 및 산림(임야), 초지(논밭, 공원 등), 수계(하천, 호수 등) 지역으로 분류하였으며, 4개 지역 특성을 고려한 최적의 추정식을 적용하여 증발산량을 산정하였다. 수영구 지역의 전체 증발산량은 4개 지역에서 산정된 증발산량에 토지이용 비율을 곱하여 구하였다. 연간 증발산량 변동은 1월부터 7월까지 증가하다가 8월부터 12월까지 감소하는 형태를 보였다. 수영구 지역에서 증발산량은 강수량의 약 13.3% 정도이었으며, 이는 연구지역의 72%에 해당하는 불투수 지역에서 배수로를 통한 물의 유출이 강우 발생 후 짧은 시간 동안 다량 발생하였기에 지속적인 증발산이 가능한 잠재수량의 저유량이 적었기 때문이다. 증발산량과 미기상인자 간의 상관분석을 수행하였으며, 증발산량과 이슬점 온도의 상관계수가 0.63으로 가장 높았다. 증발산량에 대한 기온 및 강수량, 순복사 인자의 상관계수는 0.5 이상으로 양의 상관성을, 기압 및 일조시간은 0.5 이상의 음의 상관성을 보였다. 증발산량에 대한 상관계수가 0.5 이상인 미기상인자(이슬점온도와 기온, 순복사, 기압, 강수량)에 대한 회귀 분석을 수행하였다. 이슬점온도와 기온, 순복사, 기압에 대한 증발산량 회귀함수 그래프는 강수의 유무에 따라 2가지 경향을 보였다. 이슬점온도에 따른 증발산량 회귀함수는 강수 발생 시에는 $ET=0.004x+0.7$, 무강수 시에는 $ET=0.25{\times}e^{0.04x}$로 추정되었으며, 결정계수는 각각 0.48과 0.96 정도로서 무강수 시에 높게 나타났다. 기온에 따른 증발산량 회귀함수는 강수 발생 시에는 $ET=0.004x+0.53$, 무강수 시에는 $ET=0.13{\times}e^{0.06x}$로 추정되었으며, 결정계수는 각각 0.39와 0.89 정도로서 무강수 시에 높게 나타났다. 순복사에 따른 증발산량 회귀함수는 강수 발생 시에는 $ET=0.79x+0.49$, 무강수 시에는 $ET=0.22x+0.03$로 추정되었으며, 결정계수는 각각 0.34와 0.89 정도로서 무강수 시에 높게 나타났다. 기압에 따른 증발산량 회귀함수는 강수 발생 시에는 $ET=-0.04x+37.91$, 무강수 시에는 $ET=5.18{\times}10^{22}{\times}e^{-0.05x}$로 추정되었으며, 결정계수는 각각 0.25와 0.45 정도로 나타났다. 강수량에 따른 증발산량 회귀함수는 $ET=0.23lnx+0.90$으로 추정되었으며, 결정계수 0.61정도 나타났다.

• Journal of the Korean Geographical Society
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• v.46 no.1
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• pp.36-49
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• 2011

This paper aims to investigate the frequency and intensity variations of Okhotsk high pressure system focused on the Korean Peninsula. Weather chart (00UTC), daily weather data and reanalysis data were used. The first occurrence date of Okhotsk high pressure system tends to be earlier in those years that surrounding land air temperature in April is high. The frequency of Okhotsk high has recently decreased, and its intensity tends to be stronger when the difference between sea surface temperature and surrounding land air temperature is big. The frequency of Okhotsk high in April, May, June and July increases when surrounding land air temperature is high, and its intensity grows when the difference between surrounding land air temperature and sea surface temperature is big. The frequency of Okhotsk high may increase and its intensity may increase when the first occurrence date comes earlier. In June, however, the reverse may apply.