In this study, monthly average values of BOD, COD, and TOC observed for 10 years (2008–2017) in the Nam River were estimated, and monthly variations of BOD, COD, and TOC were analyzed. Monthly average COD was always higher than monthly average BOD; monthly average TOC was high from June to September when rainfall was high. Monthly correlation coefficients between BOD and COD ranged from 0.57 to 0.94, those between BOD and TOC from 0.45 to 0.93, and those between COD and TOC from 0.75 to 0.93. The correlation coefficients were high from November to February when rainfall was low. Regression analyses for monthly average water quality data of the Nam River classified into dry season (October to April) and wet season (May to September) were conducted. Correlation coefficients were higher in the dry season than those in the wet season, and the determination coefficients of linear regression functions for BOD and COD with TOC were also higher in the dry season than those in the wet season. From this study, it can be concluded that it is appropriate to use monthly data to analyze the correlations among BOD, COD, and TOC in the stream. To analyze the relationship between TOC flowing into the stream and BOD/COD, it was found that seasonal characteristics should be considered.

Herein, we analyzed the spatial and temporal variation of DO (dissolved oxygen), BOD (biochemical oxygen demand), and COD (Chemical Oxygen Demand) with the monthly mean observed data for 10 years (2008~2017) in the main stream of the Nakdong River. The water quality of the stations declined in a downstream direction, with the BOD and COD showing their highest values at the ST5 station. From the analysis of the correlation of water quality components at 10 stations, the correlation coefficient between the DO and water temperature was more than –0.90, and that between BOD and Chl-a was 0.48~0.85, and that between COD and TOC was more than 0.65 except for the ST5 and ST10 stations. From the regression analysis using data collected from all stations, the water temperature and DO decreased linearly with a coefficient of determination of 0.90, and the Chl-a and BOD could be described by increasing power functions with a coefficient of determination of 0.83. The TOC and COD followed increasing logarithm functions with a coefficient of determination of 0.58. The TOC efficiency at the 10 stations was estimated and the average efficiencies of BOD and COD were 15.5~36.3% and 57.4~89.6%, respectively.

본 연구에서는 Cosmic-ray 토양수분량 관측시스템 구축 시 필요한 검증 네트워크 설계 기법 개발에 목적을 두고 유전율식(dielectric constant) 장비인 Frequency Domain Reflectometry (FDR)와 연계하여 Cosmic-ray 검증시스템을 구축·운영하였다. Cosmic-ray 검증시스템 평가에 필요한 시범지역은 기존 계측 장비와의 연계성과 다양한 수문자료의 활용성을 고려하여 설마천 유역에 구축하였다. 시범지역은 Cosmic-ray 장비와 FDR 센서(10개소)로 구축하였으며 2018년 7월부터 현재까지 운영되고 있다. 본 연구에서는 검증시스템의 신뢰도를 높이기 위해 코어법(soil core sampling method)을 통해 산출한 용적수분함량(volumetric water content)을 유전율식 장비와 정기적으로 검증하였다. 연구기간 중 수행한 코어법과 FDR 센서를 검증한 결과, 두 자료의 통계량이 bias=-0.03 m3/m3과 RMSE=0.03 m3/m3의 유의한 값을 보였다. 또한 연구기간 동안 FDR 센서의 시계열 특성은 모든 강우에 정상적으로 반응하였다. 그러나 일부 지점에서는 낙엽 및 캐노피의 차단과 상부사면의 유출 등으로 인해 상이한 특성을 보였다. Cosmic-ray 영향원(influence line) 내 FDR 센서의 대표성 분석은 시간 안정성 해석법(temporal stability analysis, TSA)을 이용하여 토심별(10 cm, 20 cm, 30 cm, 40 cm)로 분석하였다. 10개소에 대한 토심별 토양 수분량의 대표성을 TSA로 분석한 결과, 토심 10 cm에서는 FDR 5, 토심 20 cm에서는 FDR 8, 토심 30 cm에서는 FDR 2, 토심 40 cm에서는 FDR 1에서 가장 우수한 대표 특성을 보였다. 본 연구의 시범지역 운영 기간이 짧다는 한계는 있지만 지금까지의 분석 결과를 토대로 하여 볼 때, Cosmic-ray 관측시스템 구축 시에는 검증 장비로는 유전율식을 활용하고, Cosmic-ray 영향원 내 토양수분량의 대표성 분석은 TSA 방법으로 수행하는 것이 바람직할 것으로 판단된다.

We developed a small sensor observation system (SSOS) at a relatively low cost to observe the atmospheric boundary layer. The accuracy of the SSOS sensor was compared with that of the automatic weather system (AWS) and meteorological tower at the Korea Meteorological Administration (KMA). Comparisons between SSOS sensors and KMA sensors were carried out by dividing into ground and lower atmosphere. As a result of comparing the raw data of the SSOS sensor with the raw data of AWS and the observation tower by applying the root-mean-square-error to the error, the corresponding values were within the error tolerance range (KMA meteorological reference point: humidity ± 5%, atmospheric pressure ± 0.5 hPa, temperature ± 0.5℃. In the case of humidity, even if the altitude changed, it tends to be underestimated. In the case of temperature, when the altitude rose to 40 m above the ground, the value changed from underestimation to overestimation. However, it can be confirmed that the errors are within the KMA’s permissible range after correction.

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

This study suggested the estimation method of the ground response spectra at a structure location using earthquake acceleration data from seismological observatories. To suggest estimation method based on measured earthquake acceleration data, a algorithm for determining the observations near the structure site was suggested and a module for calculating a ground response spectrum was developed associated with a listed station determining algorithm.

This study tries to reveal abnormal trends in climate change from 60 stations in Korea during 1981-2010 by comparisons to the standard station, Chupungnyeong station. Trends in climate change from station with the abnormalities, and their implication and causes are also discussed. Although Wando, Wonju, Mungyeong and Mokpo stations show the most abnormalities, normal trends in climate change from some climate data are also found from Mokpo station. On the other hand, some climate data from Suwon, Jeonju, Jinju, Icheon and Geumsan stations indicate the most normalities. It should be noted that variabilities of climate data are largely different, indicating that clear trends in climate change may not be extracted. The fact that some stations with the abnormalities from some climate data also show the normalities should be also noted. This study suggests that most stations with the most abnormalities may be relevant to relocation of station.

강우는 물순환 시스템을 이해를 증가 시킬 뿐만 아니라, 효율적인 수자원 확보 및 관리에 있어서 가장 핵심적인 인자이다. 본 연구는 2015년을 대상으로 한반도에서의 92개의 ASOS 지점자료와 최근에 발사된 GPM 위성강우 자료의 비교를 통하여 활용가능성을 평가하였다. 또한 지점 자료의 장점과 인공위성 자료의 장점을 융합함으로써 보다 개선된 강우자료를 산출하기 위해 3가지의 상세화 방법(Geographical Differential Analysis, Geographical Ratio Analysis, Conditional Merging)들을 적용하였다. 이 연구에서 도출된 결과는 다음과 같다. 1) ASOS 자료와의 검증을 통해 GPM 강우자료가 약간 과대산정되는 편향을 가지고 있는 것을 확인하였으며, 특히 여름 기간에 오차가 높게 발생하는 것으로 나타났다. 2) Jackknife 방법을 통하여 각 합성방법에 대해서 검증하였을 때, 공간해상도가 높아짐에 따라서 오차가 줄어드는 것을 확인하였으며, 상세화 방법 중 conditional merging 방법이 가장 좋은 성능을 나타내었다.

This study reviewed the applicability of the existing flood discharge calculation method on Jeju Island Han Stream and compared this method with observation results by improving the mediating variables for the Han Stream. The results were as follows. First, when the rain-discharge status of the Han Stream was analyzed using the flood discharge calculation method of the existing design (2012), the result was smaller than the observed flood discharge and the flood hydrograph differed. The result of the flood discharge calculation corrected for the curve number based on the terrain gradient showed an improvement of 1.47 - 6.47% from the existing flood discharge, and flood discharge was improved by 4.39 - 16.67% after applying the new reached time. In addition, the sub-basin was set separately to calculate the flood discharge, which yielded an improvement of 9.92 - 32.96% from the existing method. In particular, the steepness and rainfall-discharge characteristics of Han Stream were considered in the reaching time, and the sub-basin was separated to calculate the flood discharge, which resulted in an error rate of –8.77 to 8.71%, showing a large improvement of 7.31 - 28.79% from the existing method. The flood hydrograph also showed a similar tendency.

This study analyzes relationship between land cover change and local climate data of 46 weather stations in South Korea from the 1980s to 2000s. The used area shows proportional relationships to mean daily min. temperature and mean temperature, and a reverse relationship is found between the used area and relative humidity. However, the forest indicates reverse relationships to mean daily min. temperature and mean temperature. The agricultural land causes to increase in relative humidity and decrease in mean wind speed, while the water increases mean daily min. temperature, daily min. temperature and mean temperature as well as mean wind speed. The urbanization type (used area + barren) shows high correlations with temperature and humidity. The suburbanization type (agricultural land + forest + grass + wetland) has high correlations with temperature and wind speed. High correlations are also found between the waterfront type (wetland + water), and temperature and wind speed. It can be concluded that change in land cover around weather station obviously influences on climate data of the weather station and it is also expected that reliability and homogeneity of climate data from a weather station can be enhanced by this study.

Manufacturing and technology industries produce large amounts of air pollutants. Ulsan Metropolitan City, South Korea, is well-known for its large industrial complexes; in particular, the concentration of SO2 here is the highest in the country. We assessed SO2 monitoring sites based on conditional and joint entropy, because this is a common method for determining an optimal air monitoring network. Monthly SO2 concentrations from 12 air monitoring sites were collected, and the distribution of spatial locations was determined by kriging. Mean absolute error, Root Mean Squared Error (RMSE), bias and correlation coefficients were employed to evaluate the considered algorithms. An optimal air monitoring network for Ulsan was suggested based on the improvement of RMSE.

In this paper, we used a nonhomogeneous Gaussian regression model (NGR) as the postprocessing techniques to calibrate probabilistic forecasts that take the form of probability density functions for temperature. We also performed the alternative implementation techniques of NGR, which are stationspecific ensemble model output statistics (EMOS) model. These techniques were applied to forecast temperature over Pyeongchang area using 24-member Ensemble Prediction System for Global (EPSG). The results showed that the station-specific EMOS model performed better than the raw ensemble and EMOS model.

A model coupling a meteorological predictive model and a vegetation photosynthesis and respiration model was used to simulate CO2 concentrations over coastal basin areas, and modeling results were estimated with aircraft observations during a massive sampling campaign. Along with the flight tracks, the model captured the meteorological variables of potential temperature and wind speed with mean bias results of 0.8℃, and 0.2 m/s, respectively. These results were statistically robust, which allowed for further estimation of the model’s performance for CO2 simulations. Two high-resolution emission data sets were adopted to determine CO2 concentrations, and the results show that the model underestimated by 1.8 ppm and 0.9 ppm at higher altitude over the study areas during daytime and nighttime, respectively, on average. Overall, it was concluded that the model’s CO2 performance was fairly good at higher altitude over the study areas during the study period.

Land cover around weather station can affect various climatic elements such as temperature, precipitation, wind and moisture. This study tries to reveal patterns and causes in land cover changes around weather stations in South Korea and to classify types of the land cover changes. The agricultural land, forest and used area have occupied most areas around un-relocated 47 weather stations with enough weather observation durations for the past 20-30 years. Area of the agricultural land shows steady decrease with remarkable areal decrease in the wetland, while steady areal increase is found in the used area. Due to urban expansions and new town developments around the weather stations, areas of the urbanization type (used area+barren) and suburbanization type (agricultural land+forest+grass+wetland) show steady increase and decrease, respectively. On the other hand, accurate changes in land cover are not reflected in the water-front type (wetland+water) due to errors and limitations in land cover classification using satellite images. It is expected that the results in this study can contribute to reliability and homogeneity enhancement of weather data.

In order to simulate a typhoon precisely, the satellite observation data has been assimilated using WRF (Weather Research and Forecasting model) three-Dimensional Variational (3DVAR) data assimilation system. The observation data used in 3DVAR was GPS Radio Occultation (GPS-RO) data which is loaded on Low-Earth Orbit (LEO) satellite. The refractivity of Earth is deduced by temperature, pressure, and water vapor. GPS-RO data can be obtained with this refractivity when the satellite passes the limb position with respect to its original orbit. In this paper, two typhoon cases were simulated to examine the characteristics of data assimilation. One had been occurred in the Western Pacific from 16 to 25 October, 2015, and the other had affected Korean Peninsula from 22 to 29 August, 2012. In the simulation results, the typhoon track between background (BGR) and assimilation (3DV) run were significantly different when the track appeared to be rapidly change. The surface wind speed showed large difference for the long forecasting time because the GPS-RO data contained much information in the upper level, and it took a time to impact on the surface wind. Along with the modified typhoon track, the differences in the horizontal distribution of accumulated rain rate was remarkable with the range of 600~500 mm. During 7 days, we estimated the characteristics between daily assimilated simulation (3DV) and initial time assimilation (3DV_7). Because 3DV_7 demonstrated the accurate track of typhoon and its meteorological variables, the differences in two experiments have found to be insignificant. Using observed rain rate data at 79 surface observatories, the statistical analysis has been carried on for the evaluation of quantitative improvement. Although all experiments showed underestimated rain amount because of low model resolution (27 km), the reduced Mean Bias and Root-Mean-Square Error were found to be 2.92 mm and 4.53 mm, respectively.

차량용 강우센서는 강우에 따라 와이퍼의 동작 속도를 제어하기 위해 만들어졌다. 따라서 강수의 많고 적음을 대략적으로 판단하여 와이퍼의 속 도단계를 결정하기 위한 장치이다. 하지만 기술의 발달로 인하여 강우센서의 성능이 개선됨에 따라 와이퍼의 속도단계 결정 외에 강우량의 크기를 좀 더 정확히 판단할 수 있는 기술이 개발되고 있다. 본 연구에서는 강우입자로 인한 빛의 산란을 이용한 강우계측 방법을 이용하였다. 센서에서 광 신호를 보내고 전면부 유리창에 반사되어 돌아오는 광신호를 이용하는 방법으로 물방울 입자가 커지면 빛의 산란으로 센서의 광 감지량이 줄어들 게 된다. 강우량의 정확도를 높이기 위하여 강우센서의 검지면적과 검지채널을 기존 강우센서에 비해 크게 확장하였다. 또한 센서의 감지 신호 (Signal)를 강우량으로 환산하기 위하여 실내 강우발생 실험 장치를 이용하여 와이퍼의 속도단계(W)에 따른 특정 강우(R) 발생시 센서 감지량(S) 과의 관계를 이용한 W-S-R 관계식을 개발하였다. 이 관계식을 통하여 차량 강우센서의 신호체계를 실제 강우량으로 환산하여 사용자에게 제공한 다면 차량관측망이 강우측정망이 되어 실제 강우측정망보다 고해상도의 강우정보를 생산할 수 있을 것으로 판단된다.

To analyze the cooling effect of urban green areas, we conducted micrometeorological measurements in these areas and their surroundings in Seoul, Korea. From the average hourly temperature measurements through each month for the last two years (March 2013 to February 2015), we found that the maximum temperature difference between urban and green areas was about 2.9℃ at 16:00 LST in summer, and the minimum was about 1.7℃ at 22:00 LST in winter. In summer, the temperature difference was the largest during the day, rather than at night, due mainly to shading by the tree canopy. The specific humidity difference between the two areas was about 1.5 g kg-1 in summer, and this decreased in the winter. The specific humidity difference between urban and green areas in summer is relatively large during the day, due to the higher evapotranspiration level of biologically active plants.

We investigated the local climatological characteristics of the mountain adjacent the Dongyeong herb garden in Chilgok. We established one set of automatic weather system (AWS) on a hill where development of herb garden is in progress. The observations were continued for 2 years(2013. 07-2015.06). In this study, we analyzed the observed data comparing the data of Gumi meteorological observatory (GMO). The results showed that the air temperature(relative humidity) of Dongyeong herb garden were lower(higher) than those of GMO. Especially the differences are more during warm climate season. It means that the gaps of thermal environment between two points are mainly caused by the evaporation effects of forest. In addition, we analyzed the warmth indices(warmth index and coldness index) with the observed air temperature. The warmth and coldness indices indicate about 107 and –12, respectively. The values correspond to warm temperature climate.

Relocation of weather station leads to changes in geographical climate factors such as latitude, longitude, elevation, topographical relief and land cover of surrounding area that inf luence on local climate. This study analyzes spatio-temporal characteristics and relationships between geographical factors such as location, topographical relief and land cover, and changes in climate data such as temperature, precipitation and wind due to relocation of 12 weather stations in South Korea. Changes in temperature and moisture are attributed to changes in land cover by the relocation. Wonju and Gumi where the stations were relocated from rural to new built-up area show increases in temperature, while temperature in Sokcho, Changwon, Cheonan, Daejeon, Gunsan and Mokpo decreased with the relocations from urban to rural area. Relative humidity in Mokpo, Gunsan and Daejeon increases due to increase in farming land. Changes in topographical relief influence on precipitation, wind and duration of sunshine. The relocation in Chungju to interior of basin led to decreases in precipitation and duration of sunshine, and Boryeong shows decrease in precipitation by the relocation from windward slope to hilly coastal area. Wind speed in Gunsan with the relocation from coastal to inland area decreased due to influence of neighboring hills. Shadow effect by neighboring building or vegetation can be attributed to changes in duration of sunshine in Gwangju and Wonju.

본 연구에서는 GCOM-W1 위성에 탑재된 Advanced Microwave Scanning Radiometer 2 (AMSR2) 센서의 토양수분 자료를 Land Parameter Retrieval Model (LPRM) 알고리즘을 통해 전처리하여 2014년도 한반도 지점관측 자료와의 비교 분석을 수행, 위성 토양수분 자료 의 적합성을 평가하였다. 통계 분석 결과 AMSR2 X-band의 토양수분 자료는 38개의 지점관측 자료와 비교해 0.03의 평균 bias, 0.16의 평균 RMSE의 낮은 오차 수준을 보였으며, 최대상관계수는 0.67로 나타났다. 또한 AMSR2 센서의 ascending, descending 시간대별 위성 토양수분 자료 분석과 X, C1, C2-band의 주파수 영역별 위성 토양수분 자료 분석 결과, ascending overpass time 시간대와, X-band 주파수의 토양수분 자료가 지점 관측 자료와 더 좋은 상관관계를 보였다. 본 연구의 분석 결과는 한반도에서 최근 문제가 되고 있는 가뭄을 비롯한 각종 재해 분석 시 토양수분의 공간적 분포를 연구하는데 활용 될 수 있을 것으로 기대된다.