• Journal of Environmental Policy
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• v.13 no.2
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• pp.21-38
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• 2014

In response to global warming, the effect of the air temperature on water temperature has been noticed. The change in water temperature in river environment results in the change in water quality and ecosystem, especially Dissolved Oxygen (DO) level, and shifts in aquatic biota. Efforts need to be made to predict future water temperature in order to understand the timing of the projected river temperature. To do this, the data collected by the Ministry of Environment and the Korea Meteororlogical Administration has been used to build a nonlinear relationship between air and water temperature. The logistic function that includes four different parameters was selected as a working model and the parameters were optimized using SCE algorithm. Weekly average values were used to remove time scaling effect because the time scale affects maximum and minimum temperature and then river environment. Generally speaking nonlinear logistic model shows better performance in NSC and RMSE and nonlinear logistic function is recommendable to build a relationship between air and water temperature in Korea. The results will contribute to determine the future policy regarding water quality and ecosystem for the decision-driving organization.

• Journal of Environmental Policy
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• v.12 no.2
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• pp.17-32
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• 2013

The potential impact of water temperature on air temperature in response to recent anthropogenic global warming has been noticed. To predict climate, induced change in river aquatic environment, it is necessary to understand the thermal constrains of fish species and the timing of the projected river temperature. As a preliminary study, air-water temperature relationship was analyzed on the basis of the observed data during the time period of 2009-2011 and the number of data corresponds to 873-1083. As a result of analyzing the auto-and cross-correlation coefficient between air-water temperature, high correlation is shown (~0.9). It is also found that the correlation coefficient of air temperature is higher than that of water temperature at the lag time less than approximately 10 days. Observed data was divided into two groups to investigate hysteresis: rising limb and falling limb. For some stations there is strong evidence that hysteresis exist between air-water temperature relationships. Consequently it is recommended that seasonal hysteresis needs to be included in determining an airwater relationship.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.3
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• pp.213-221
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• 2007

In response to anthropogenic global warming due to a buildup greenhouse gas, the effect of the air temperature on water temperature has been noticed and some efforts have been made to build an air/water temperature relationship at the Masan Bay area by the Ministry of Maritime Affairs & Fisheries (MOMAF). As a result of analyzing the auto- and cross-correlation coefficient between air/water temperature, high correlation $(\sim0.9)$ is shown and the correlation coefficient of air temperature is higher than that of water temperature at the lag time less than approximately 10 days. Separate functions are fitted to the air/water relationship at the Masan Bay to take hysteresis into account. The slopes of the straight line for the rising limb are 0.829 and 0.774 for MA1 and MA2 station respectively, while 1.385 and 1.444 ($\sim1.75$ times larger) for the falling limb. Consequently, the seasonal hysteresis should be considered in order to determine an air/water relationship and accurately estimate the water temperature using the air temperature at Masan Bay.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.2
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• pp.128-135
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• 2007

In response to anthropogenic global warming due to a buildup greenhouse gas, the effect of the air temperature on water temperature has been noticed. Therefore, effects have been made to build an air/water temperature relationship at three study regions using the data collected by the Ministry of the Maritime Affairs and Fisheries (MOMAF). The air/water relationship varies with time-scale and weekly time-scale was chosen for the study. The data were fitted to the S-shaped non-linear relationship, and the parameters for the S-curve were derived using a single-criteria multi-parameter optimization scheme. Separate regression curves were fitted to consider seasonal hysteresis at the Masan site. The study results support the S-shaped non-linear relationship is the best fit for the air/water relationship at the Korean coastal zone. This study will contribute to determine the future policy regarding water quality and ecosystem for the decision-driving organization.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.17 no.2
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• pp.65-69
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• 1981

The oceanic effect on the climate of the southern coast of Korea was analysed based on the sea surface temperature and in order to study relationships between the fluctuation of the sea surface temperature and that of climatic elements. Meteolorogical data from 1960 to 1979 were used. In the year when difference between the air and water temperature was maximum, the air temperature in southern coast was higher than normal year. A fluctuation of the sea surface temperature plays an important influence to determine the variation of the air temperature in the coastal area. Humidity of the coastal climate depends upon the oceanic effect in summer, but not in winter. This results may be due to prevailing wind effect. The oceanic effect on the precipitation in the coastal area is not found.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.17 no.2
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• pp.105-108
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• 1981

The oceanic effect on the climate of the southern coast of Korea was analysed based on the sea surface temperature and in order to study relationships between the fluctuation of the sea surface temperature and that of climatic elements. Meteolorogical data from 1960 to 1979 were used. In the year when difference between the air and water temperature was maximum, the air temperature in southern coast was higher than normal year. A fluctuation of the sea surface temperature plays an important influence to determine the variation of the air temperature in the coastal area. Humidity of the coastal climate depends upon the oceanic effect in summer, but not in winter. This results may be due to prevailing wind effect. The oceanic effect on the precipitation in the coastal area is not found.

• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.1 s.24
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• pp.23-32
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• 2006

This study was conducted to find out the effects of meterological factors on oceanic conditions when cold and dry continental air mass passes through the western sea of Korea The change of ocean conditions during the winter season were more obvious in coastal area than open sea And sea surface temperature (SST) during February is lower by $3^{\circ}C$ than December but in coastal area SST dropped by $3^{\circ}C$. As for the salinity, there was not much difference between areas except southern area of Mokpo. In the coastal regions, air temperature(AT) and SST showed a positive correlation; as the air temperature goes up with the increase of SST and when the former goes down the latter decrease. SST of open sea seems to be changed by latent (Qe) and sensible heat (Qs), when the open sea lose its heat by Qe and Qs then SST goes down And when they get the heat then the SST goes up. 1here was a positive correlation between the AT of the coastal region and sea surface salinity (SSS), when the AT goes up then SSS increase and when the former goes down the latter decrease. Precipitation during the summer seasons (June$\sim$September) appeared to the more closely related with salinity of February of the following year than those of October and December.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.953-968
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• 2018

In order to understand the change of surface water temperature in the East China Sea (ECS), this study analyzed the relationship between sea surface temperature (SST), air temperature (AT) and heat flux using satellite and model reanalysis data from 2003 to 2017. SST in the ECS showed the lowest (average : $13.72^{\circ}C$) in March and the highest (average : $28.12^{\circ}C$) in August. AT is highly correlated with SST and shows a similar seasonal change. In August, SST is higher than AT and then continuously higher than AT until winter. To analyze the change of the summer SST in the ECS, we used the SST anomaly value in August to classify the periods with positive (04', 06', 07', 13', 16', 17') and negative (03', 05', 08', 09', 10', 11', 12', 14', 15') values. Spatial similarity between the two periods indicates that SSTs are relatively larger variations in the northern part than in the southern part, and in the western part than in the eastern part in the study area. AT and net heat flux values also show similar changes with SST. However, the periods of the positive SST anomaly have the relatively increasing SST, AT and heat flux values compared to the periods of the negative SST anomaly in the summer season of the ECS. Although the change of SST in the summer season generally well correlates with AT, there were the periods when it was different from general trends between SST and AT (10', 12', 15', 16'). SST in August 2010 and 2012 decreased by $0.5^{\circ}C$ from AT. It suggests that the decreasing SST was considered to be caused by the effects of the typhoon passing through the study area. In August 2015, AT was relatively lower than SST (> $0.5^{\circ}C$), which is might be weakening of the East Asian Summer Monsoon. In August 2016, SST and AT show the highest values during the whole study periods, but SST is higher than AT (> $1^{\circ}C$). From satellite and heat flux data, the variations of SST have been shown to be relatively higher in the area of the expansion Changjiang Diluted Water (CDW) originated from the China coast. More research is needed to analyze this phenomenon, it is believed as not only the effect of rising AT but also the expansion of the low-salinity water.

• Proceedings of KOSOMES biannual meeting
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• 2003.11a
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• pp.181-185
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• 2003

the effect if atmosphere is more important in the West sea of Korea than in other seas because of shallow water and heat storage if the water. The serial oceanographic observation data and coastal station data from NFRID, and the atmosphere data from KMA were used in order to find out the relationship between them The highest water temperature, salinity and weather factor were recorded in Aug, and the lowest of them in Feb. As the water deepens, the maximum time leg in water temperature and the minimum time leg in salinity. Water temperature have the maximum in Oct, the minimum in Apr at 75m of the 311-07 station with 100m depth water temperature (WT)-air temperature, WT-precipitation (Preci.) and salinity (Sal)-wind speed (WS) were in direct proportion, but WT-WS, Sal-AT and Sal-Preci in inverse proportion Water temperature and salinity I-ave time leg at the same depth the maximum had more the delay of $2\~4$ months at a depth if 20 meters than at the surface in all stations except for salinity at 307-05.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.5
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• pp.278-284
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• 2014

Water temperature due to climate change can be estimated using the air temperature because the air and water temperatures are closely related and the water temperatures have been widely used as the indicators of the environmental and ecological changes. It is highly necessary to estimate the frequency distribution of the air and water temperatures, for the climate change derives the change of the coastal water temperatures. In this study, the distribution function of the air temperatures is estimated by using the long-term coastal air temperature data sets in Korea. The candidate distribution function is the bi-modal distribution function used in the previous studies, such as Cho et al.(2003) on tidal elevation data and Jeong et al.(2013) on the coastal water temperature data. The parameters of the function are optimally estimated based on the least square method. It shows that the optimal parameters are highly correlated to the basic statistical informations, such as mean, standard deviation, and skewness coefficient. The RMS error of the parameter estimation using statistical information ranges is about 5 %. In addition, the bimodal distribution fits good to the overall frequency pattern of the air temperature. However, it can be regarded as the limitations that the distribution shows some mismatch with the rapid decreasing pattern in the high-temperature region and the some small peaks.