• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.313-318
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• 2017

Land surface temperature is essential for monitoring abnormal climate phenomena such as UHI (Urban Heat Islands), and for modeling weather patterns. However, the quality of surface temperature obtained from the optical space imagery is affected by many factors such as, revisit period of the satellite, instance of capture, spatial resolution, and cloud coverage. Landsat 8 imagery, often used to obtain surface temperatures, has a high resolution of 30 meters (100 meters rearranged to 30 meters) and a revisit frequency of 16 days. On the contrary, MODIS imagery can be acquired daily with a spatial resolution of about 1 kilometer. Many past attempts have been made using both Landsat and MODIS imagery to complement each other to produce an imagery of improved temporal and spatial resolution. This paper applied machine learning methods and performed downscaling which can obtain daily based land surface temperature imagery of 30 meters.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.501-504
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• 2001

The prototype biofilter was constructed in Suwon campus of Seoul National University and monitored for temperature and treatment efficiencies during a two-year programme. During the winter, daily influent wastewater temperature averages $7.7C^{\circ}$; without heating in 2000 experiment, the treatment efficiencies for BOD and SS droped down to 88.7% and 68.4%, respectively. However, as increased the influent wastewater by installting a heater tank before the biofilter tank in 2001 at the same period ($Feb.\;9{\sim}Mrach\;30$) of 2000 experiment, average daily influent temperature which was $7.2C^{\circ}$ increased to over $18.2C^{\circ}$. As a result, effluent quality remains excellent through the winter and even the post winter with BOD and SS values close to less than 10 mg/L. Nitrification follows temperature patterns. However, there was no improvement of treatment efficiency in total nitrogen (T-N) was observed by increasing temperature.

• Atmosphere
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• v.16 no.1
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• pp.49-53
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• 2006

The present study has examined interdecadal variations of the diurnal temperature range (DTR, daily maximum temperature minus daily minimum temperature) during the New Year season in Seoul for the period 1954-2005. Here, the average DTR for the New Year holidays (three consecutive days; one day before the New Year, the New Year day, and one day after the New Year) minus the average DTR for 14 days, 7 days before and 7 days after the New Year holidays, is defined for representing the New Year effect. The DTR index does not show notable trend until the late 1970s but shows obvious positive values afterward. For example, the difference of the average DTR between two periods (1980-2005 minus 1954-1979) is $0.65^{\circ}C$, which is meaningful at the 95% confidence level. This result demonstrates that intense human activity even for the limited period may provide climate impact in local regions. Its plausible causes are discussed.

• Journal of Korean Society of Rural Planning
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• v.22 no.1
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• pp.13-23
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• 2016

There is a need to analyze unconfined groundwater behavior since the demand of groundwater use has been increasing. While unconfined groundwater temperature is tend to be affected by air temperature, it is hard to find an empirical study in South Korea. In this research, we try to determine the relationship between daily average air temperature and daily average groundwater temperature by time-sequential analysis of groundwater monitoring wells in Galshin basin in Yesan-Gun, Chungcheongnam-Do. In addition, models to estimate groundwater temperature from air temperature were developed. In this research 101-day moving average method with measured air temperature is used to estimate groundwater temperature. To verify the developed model, estimated values of average groundwater temperature with 101 moving average are compared to the measured data from September 10 2007 to September 9 2008. And, Nash-Stucliff Efficiency and Coefficient of Determination were 0.970 and 0.976, therefore it was concluded that the model allowing groundwater temperature estimation from air temperature is with reasonable applicability.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.1
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• pp.90-100
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• 2021

In the north and northeast of Cheonsu Bay, short-term fluctuations of surface water temperature are large owing to shallow water depth, weak current, and freshwater runoff. However, in the south of the bay, water temperature fluctuations are small owing to the inflow of offshore water by tidal currents. The water temperature in the north of the bay is higher in spring and summer than in the south of the bay, but lower in autumn and winter. During spring season, the fluctuation in the northern surface water temperature is the highest. The temperature fluctuations owing to tides are in phase with the tide in autumn and winter, and in the reverse phase with the tide in spring and summer. The dominant periods of water temperature fluctuations are half a day, daily, 15 days, and 1 month owing to the tide and 7 to 10 days, which are estimated based on atmospheric factors. Half a day and daily water temperature fluctuations are also highly correlated with air temperature and wind fluctuations. The sea area where water temperature fluctuations are highly correlated is divided into the north and south of the bay. The fluctuation phase is faster in the north of the bay than in the south or in the center.

• Atmosphere
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• v.17 no.1
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• pp.45-53
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• 2007

In order to investigate the impacts of heat wave on human health, cluster analysis of meteorological elements (e.g., temperature, dewpoint, sea level pressure, visibility, cloud amount, and wind components) for identifying offensive synoptic air masses is employed. Meteorological data at Seoul during the past 30 years are used. The daily death data at Seoul are also employed. Occurrence frequency of heat waves which is defined by daily maximum temperature greater than the threshold temperature (i.e., $31.2^{\circ}C$) was analyzed. The result shows that the frequency and duration of heat waves at Seoul are increasing during the past 30 years. In addition, the increasing trend of the frequency and duration clearly appears in late spring and early autumn as well as summer. Factor analysis shows that 65.1% of the total variance can be explained by 4 components which are linearly independent. Eight clusters (or synoptic air masses) were classified and found to be optimal for representing the summertime air masses at Seoul, Korea. The results exhibit that cluster-mean values of meteorological variables of an offensive air mass (or cluster) are closely correlated with the observed and standardized deaths.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.6
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• pp.546-553
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• 2013

A clear increase in the average annual temperature is observed worldwide, and climate changes take place in response to that increase. This affects not only the ecosystem, but also to mankind. Of all those aspects of climate change, people are especially interested in the length of each season, and people acknowledge that the duration of spring and fall has been shortened over the past several years. Still, it is difficult to observe this kind of phenomenon with the simple analysis of dividing the seasons and calculating the duration. Therefore, this study attempted to set up a more intuitive standard which well reflects the current situation. This study also divided the daily climate into 4 states using the daily maximum and minimum temperature. Moreover, using the Hidden Markov Model, this study calculated the duration of each season and analyzed its tendency based on the daily temperature data of the last 53 years (1960~2012). According to the result, the duration of spring and fall showed mild decreasing tendency over the past 53 years, and the duration of fall decreased even more during the past 30 years in the Korean peninsula. After 1960, the start of spring was advanced, which decreased the length of winter for about 11 days. On the other hand, the duration of summer increased for about 25 days, which is consistent with the worldwide tendency of temperature increase.

• Journal of Climate Change Research
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• v.7 no.2
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• pp.205-215
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• 2016

The relationship between the climate and the number of heat-related patients in South Korea was analysed in this study. The number of the patients was 1,612 during the summer 2011 to 2015 according to the Heat-related Illness (HRI) surveillance system. The coefficient of determination between the number of the patients and the daily maximum temperature was higher than that between the number of them and the other elements: the daily mean/minimum temperature and relative humidity. The thresholds of daily maximum and minimum temperature in metropolitan cities (MC) were higher than those in regions except for MC (RMC). The higher the maximum and minimum temperature became, the more frequently the heat-related illness rate was observed. The regional difference of this rate was that the rate in RMC was higher than that in MC. Prolonged heat wave and tropical night tended to cause more patients, which continued for 20 days and 31 days of maximum values, respectively. On the other hand, the relative humidity was not proportional to the number of the patients which was rather decreasing at over 70% of relative humidity.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.766-770
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• 2005

Cascade-Correlation Neural Networks Model(CCNNM) is used to estimate daily evaporation using limited climatical variables such as atmospheric temperature, dewpoint temperature, relative humidity, wind speed, sunshine duration and radiation. DeBruln equation is applied to estimate daily free-surface evaporation. It is converted into pan evaporation using pan coefficient. The results of CCNNM shows better than those of Debruin equation. This research represents that the strong nonlinear relationship such as evaporation modeling can be generalized by the CCNNM ; a special type of Backpropagation algorithm Neural Networks Model.

• Korean Management Science Review
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• v.26 no.1
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• pp.77-91
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• 2009

It is the most important sucess factor for the electricity generation industry to minimize operations cost of surplus electricity generation through accurate demand forecasts. Temperature forecast is a significant input variable, because power demand is mainly linked to the air temperature. This study estimates the information value of the temperature forecast by analyzing the relationship between electricity load and daily air temperature in Korea. Firstly, several characteristics was analyzed by using a population-weighted temperature index, which was transformed from the daily data of the maximum, minimum and mean temperature for the year of 2005 to 2007. A neural network-based load forecaster was derived on the basis of the temperature index. The neural network then was used to evaluate the performance of load forecasts for various types of temperature forecasts (i.e., persistence forecast and perfect forecast) as well as the actual forecast provided by KMA(Korea Meteorological Administration). Finally, the result of the sensitivity analysis indicates that a $0.1^{\circ}C$ improvement in forecast accuracy is worth about $11 million per year.