• Atmosphere
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• v.30 no.2
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• pp.169-181
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• 2020

We conducted a study on the impact of observation station density; this was done in order to enable the accurate estimation of spatial meteorological variables. The purpose of this study is to help operate an efficient observation network by examining distributions of temperature, relative humidity, and wind speed in a test area of a three-dimensional meteorological observation project in the Yeongdong region in 2019. For our analysis, we grouped the observation stations as follows: 41 stations (for Step 4), 34 stations (for Step 3), 17 stations (for Step 2), and 10 stations (for Step 1). Grid values were interpolated using the kriging method. We compared the spatial accuracy of the estimated meteorological grid by using station density. The effect of increased observation network density varied and was dependent on meteorological variables and weather conditions. The temperature is sufficient for the current weather observation network (featuring an average distance about 9.30 km between stations), and the relative humidity is sufficient when the average distance between stations is about 5.04 km. However, it is recommended that all observation networks, with an average distance of approximately 4.59 km between stations, be utilized for monitoring wind speed. In addition, this also enables the operation of an effective observation network through the classification of outliers.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1133-1144
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• 2017

Cluster analysis with meteorological data allows to segment meteorological region based on meteorological characteristics. By the way, meteorological observed data are not adequate for cluster analysis because meteorological stations which observe the data are located not uniformly. Therefore the clustering of meteorological observed data cannot reflect the climate characteristic of South Korea properly. The clustering of $5km{\times}5km$ gridded data derived from a numerical model, on the other hand, reflect it evenly. In this study, we analyzed long-term grid data for temperatures and precipitation using cluster analysis. Due to the monthly difference of climate characteristics, clustering was performed by month. As the result of K-Means cluster analysis is so sensitive to initial values, we used initial values with Ward method which is hierarchical cluster analysis method. Based on clustering of gridded data, cluster of meteorological stations were determined. As a result, clustering of meteorological stations in South Korea has been made spatio-temporal segmentation.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.5-8
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• 2002

Daily potential evapotranspiration was estimated using meteorological data which are observing regularly such as rainfall, temperature, humidity, wind speed, and duration of sunshine. Penman method is used practically in estimating evapotranspiration at present, and its regional coefficients were derived at 19 stations in the Korean Peninsular. Because meteorological data are observing at 77 stations under the Korea Meteorological Administration, the methodology of estimating evapotranspiration using meteorological data will be able to be applied in more regions than Penman method.

• Atmosphere
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• v.17 no.2
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• pp.185-193
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• 2007

This study investigates urbanization effect in warming trend of surface air temperature over Korea. The data used in this study consist of the daily minimum and maximum temperatures during the period of 32 years(1968-1999) from 16 stations of KMA. To calculate magnitude and trend of urbanization effect, stations were classified into urban and rural stations using population statistics. Urban stations were defined as those with population densities greater than 1000 persons per kilometer squared in 1995. The others were defined as rural stations. The urban stations were also subdivided into two groups according to their population totals. For estimates of urban effect magnitude, temperature change was calculated by comparing 16-year mean values between 1968-83 and 1984-99. Then, the difference between each urban station and every rural station was calculated. During the analysis period of 32 years, maximum temperature increase is $1.22^{\circ}C$. In the total temperature increase, urban effect is estimated by 28.7%. For minimum temperature, it becomes larger by about 10% than that in maximum temperature. Therefore, urban effect in an increasing trend of minimum temperature is 38.9% in the change of $1.13^{\circ}C$.

• Atmosphere
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• v.20 no.2
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• pp.63-71
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• 2010

In this study, we derived the wind speed at 50 m and 80 m above sea level from 567 stations over a period of 1 year and correlated to measured wind speed at 5 radiosonde sites. From these correlations, we derived and analyzed the spatial distribution of wind map over Korea based on hourly observational data recorded over a period of 5 years from 2004 to 2008. As a results, wind speed is generally high over seashores, mountains, and islands. Mean wind speed over Korea at 50 and 80 m above sea level for 5 years during 2004 to 2008 seasonally are highest at Spring, and then followed by Winter, Fall, and Summer. In 76 (14%) stations, mean wind speed at 80 m above sea level for 5 years during 2004 to 2008 are greater than $5ms^{-1}$. The prevailing winds over Korea at 80 m above sea level for 5 years during 2004 to 2008 are North (44%), Northwest (16%), and West (15%). In 99 stations, the % of wind faster than $5ms^{-1}$ was higher than 40%, and in 62 stations, the % of wind faster than $5ms^{-1}$ was higher than 50%. In 178 station, the % of prevailing winds was higher than 30%, and there are 7 stations which also have wind speeds over $5ms^{-1}$, ranking from highest to lowest, Dongsong, Daegwallyeong, Baekun Mt., Hyangrobong Mt., Sorak Mt., Gosan, and Misiryeong Mt..

• Journal of architectural history
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• v.23 no.2
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• pp.39-52
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• 2014

This study researched changes over time regarding the location and spatial characteristics of modern meteorological stations, and examined the characteristics of modern meteorological station construction using the location and spatial characteristics of the Busan Meteorological Station. First, meteorological stations were located in port areas, and then moved to high altitude areas for stable meteorological observation beginning in the transition phase. Here, office buildings and residences were joined, but were separated due to the increase in functions from the stabilization phase. Second, as for spatial composition, in the establishment phase, existing buildings were used, and the scale of newly constructed buildings differed according to time and area. However, after the Japan-Korea Annexation, with increased funds and increased observation equipment, floor plans subdivided by function started to appear. In the stabilization phase, space was subdivided with redundancy due to the increase in functions. In the wartime transition phase, '一' shaped floor plans with redundancy became the norm. Meanwhile, the location of the maritime customs where the first meteorological observations took place after the opening of the ports, and the location and construction of the Busan Temporary Observatory built in the meteorological observation transition phase (1905) were investigated. Also, through the investigation of the Busan Meteorological Observatory, newly constructed before 1934, the location and spatial characteristics of modern era meteorological observatories were studied.

• Journal of Environmental Science International
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• v.13 no.4
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• pp.377-387
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• 2004

This study has been performed to clarify the characteristics of temporal and spatial distribution of surface ozone concentration over Jeju Island, one of the cleanest areas in Korea with low emissions of air pollutants. Ozone data are monitored at four sites in Jeju Island. These monitoring sites are located at two urban area(referred to Ido and Donghong), coastal area(Gosan site) and forest site(Chuna site). Ozone data has been routinely collected at these sites for the late four years. The patterns of seasonal cycle of ozone concentrations at all stations show the bimodal with the peaks on spring and autumn and a significant summer minimum. However, the patterns of diurnal variations at rural station, i.e., Gosan and Chuna sites are considerably different to those at urban stations such as Ido and Donghong sites. The patterns of $\DeltaO_3$ variations are very similar with those of monthly mean ozone concentrations and $\DeltaO_3$ values are exceeded 30 ppb, at urban stations. This may be that urban stations are more influenced by local photochemical reactions rather than rural stations. In order to assess the potential roles of meteorological parameters on ozone formation, the meteorological parameters, such as radiation, temperature, and wind are monitored together with ozone concentrations at all stations. The relationships of meteorological parameters to the corresponding ozone concentration are found to be insignificant in Jeju Island. However, at Gosan and Donghong stations, when the sea breeze blew toward the station, the ozone concentration is considerably increased.

• Atmosphere
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• v.20 no.4
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• pp.437-449
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• 2010

The relocation effect of observation station (REOS) on the homogeneity of seasonal mean of maximum and minimum temperature, diurnal temperature range (DTR) and relative humidity (RH) was investigated using surface observation data and document file. Twelve stations were selected among the 60 stations which have been operated more than 30 years and relocated over one time. The data from Chunpungryeong station were used as a reference to separate the impacts of station relocation from the effects caused by increased green house gases, urbanization, and others. The REOS was calculated as a difference between REOS of relocated station and REOS of reference station. Although the REOS is clearly dependent on season, meteorological elements, and observing stations, statistically significant impacts are found in many stations, especially the environment of observing station after relocation is greatly changed. As a result, homogeneity of seasonal mean of meteorological elements, especially DTR and RH, is greatly reduced. The results showed that the effect of REOS, along with the effect of urbanization, should be eliminated for the proper estimation of climate change from the analysis of long-term observation data.

• Korean Journal of Agricultural Science
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• v.38 no.1
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• pp.129-143
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• 2011

In this study, to select the incoming solar radiation equation which is most suitable for the estimation of Penman evaporation, 12 incoming solar radiation equations were selected. The Penman evaporation rates were estimated using 12 selected incoming solar radiation equations, and the estimated Penman evaporation rates were compared with measured pan evaporation rates. The monthly average daily meteorological data measured from 17 meteorological stations (춘천, 강능, 서울, 인천, 수원, 서산, 청주, 대전, 추풍령, 포항, 대구, 전주, 광주, 부산, 목포, 제주, 진주) were used for this study. To evaluate the reliability of estimated evaporation rates, mean absolute bias error(MABE), root mean square error(RMSE), mean percentage error(MPE) and Nash-Sutcliffe equation were applied. The study results indicate that to estimate pan evaporation using Penman evaporation equation, incoming solar radiation equation using meteorological data such as precipitation, minimum air temperature, sunshine duration, possible duration of sunshine, and extraterrestrial radiation are most suitable for 11 study stations out of 17 study stations.

• Atmosphere
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• v.32 no.2
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• pp.135-148
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• 2022

This study investigates the influence of atmospheric river (AR) on precipitation over South Korea with a focus on regional characteristics. The 42-year-long catalog of ARs, which is obtained by applying the automatic AR detection algorithm to ERA5 reanalysis data and the insitu precipitation data recorded at 56 weather stations across the country are used to quantify their relationship. Approximately 51% of the climatological annual precipitation is associated with AR. The AR-related precipitation is most pronounced in summer by approximately 58%, while only limited fraction of precipitation (26%) is AR-related in winter. The heavy precipitation (> 30 mm day^-1) is more prone to AR activity (59%) than weak precipitation (5~30 mm day^-1; 33%) in all seasons. By grouping weather stations into the four sub-regions based on orography, it is found that the contribution of AR precipitation to the total is largest in the southern coast (57%) and smallest in the eastern coast (36%). Similar regional variations in AR precipitation fractions also occur in weak precipitation events. The regional contrast between the northern and southern stations is related to the seasonal variation of AR-frequency. In addition, the regional contrast between the western and eastern stations is partly modulated by the orographic forcing. The fractional contribution of AR to heavy precipitation exceeds 50% in all seasons, but this is true only in summer along the eastern coast. This result indicates that ARs play a critical role in heavy precipitation in South Korea, thus routine monitoring of ARs is needed for improving operational hydrometeorological forecasting.