• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• Journal of Environmental Science International
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• v.23 no.2
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• pp.275-289
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• 2014

Asian dust (or yellow sand) occurring mainly in spring in East Asia is affected by the distribution of weather systems. This study was performed to investigate the characteristics of suspended particulate for Asian dust at Busan, Korea in 20 March 2010, which was one of the extreme case for the last 10 years. There was used the data of weather chart, satellite, automatic weather system (AWS), $PM_{10}$, laser particle counter (LPC), and backward trajectories model. In synoptically, the high pressure was located in the northwestern part and low pressure was located in the northeastern part of Korea. The strong westerly winds from surface to upper layer makes it possible to move air masses rapidly. Air masses passing through Gobi Desert in Mongolia and Inner Mongolia plateau covered the entire Korean peninsula. As the results of aerosol analysis, $PM_{10}$ concentration at Gudeok mountain in Busan was recorded $2,344{\mu}g/m^3$ in 2300 LST 20 March 2010 and their concentration was markedly increased at coarse mode particle. In surface condition, westerly wind about 3 ~ 5 m/s was dominant and small particles of $0.3{\sim}0.5{\mu}m$ were distributed on the whole. In heavy metal components analysis, the elements from the land was predominated.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.3
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• pp.325-331
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• 2010

Three-cup anemometers are popular devices for measuring wind speeds in automated weather stations, environmental monitoring systems, and wind turbines. Cup anemometers usually suffer from lack of long-term stability owing to the wear of the bearing systems that support the rotational parts. The bearing systems are susceptible to external pollutants, vibrations, and gusts. Therefore, these anemometers have to be calibrated regularly to maintain the desired characteristics for measuring wind speed. In the present study, a new in-situ calibration system to help reduce cost and save time by calibrating the cup anemometers at the installation site is proposed. A portable in-situ calibrator was fabricated. After the characteristics of this calibrator were verified, it was used to calibrate cup anemometers. Some of the calibration results were compared with the data obtained by wind tunnel testing.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Atmosphere
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• v.21 no.4
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• pp.447-454
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• 2011

As dust storms originated in Neimongu Plateau and Manchuria became more frequent in Korea, there was a growing need for Asian Dust (Hwangsa) monitoring stations in North Korea, which is a pathway of Asian Dust to South Korea. The South Korean and the North Korean Governments agreed to build the Automatic Weather System and the PM10 measurement instruments in the Gaeseong Industrial Zone and the Keumgangsan Tourist Region, North Korea in 2007. PM10 mass concentration data in the Keumgangsan Tourist Region could be collected only during the period from September 2007 to May 2008. In this study, daily, monthly and diurnal variations of PM10 mass concentration of the Keumgangsan are analyzed and compared with those of Sokcho and Gwangdeoksan. Three sites show similar variations in daily and monthly means. Correlation coefficients (r) between Sokcho and Keumgangsan, and between Gwangdeoksan and Keumgangsan are 0.89 and 0.67, respectively. But diurnal variation at Keumgangsan has a distinct feature compared to the other sites. Diurnal PM10 variation shows two peaks around 8 AM and 4-5 PM and very low at night. The difference between the daily maximum and minimum is $20{\sim}60{\mu}g\;m^{-3}$ during September to November 2007. Temperature, relative humidity and wind speed from the Keumgangsan AWS data were compared with those from the Changjon station, and showed good correlation each other except wind speed.

• Atmosphere
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• v.29 no.4
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• pp.417-427
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• 2019

The purpose of this study is to build urban canopy model (Met Office Reading Urban Surface Exchange Scheme, MORUSES) based to Unified Model (UM) by using urban building information data in Seoul, and then to compare the improving urban canopy model simulation result with that of Seoul Automatic Weather Station (AWS) observation site data. UM-MORUSES is based on building information database in London, we performed a sensitivity experiment of UM-MOURSES model using urban building information database in Seoul. Geographic Information System (GIS) analysis of 1.5 km resolution Seoul building data is applied instead of London building information data. Frontal-area index and planar-area index of Seoul are used to calculate building height. The height of the highest building in Seoul is 40m, showing high in Yeoido-gu, Gangnam-gu and Jamsil-gu areas. The street aspect ratio is high in Gangnam-gu, and the repetition rate of buildings is lower in Eunpyeong-gu and Gangbuk-gu. UM-MORUSES model is improved to consider the building geometry parameter in Seoul. It is noticed that the Root Mean Square Error (RMSE) of wind speed is decreases from 0.8 to 0.6 m s^-1 by 25 number AWS in Seoul. The surface air temperature forecast tends to underestimate in pre-improvement model, while it is improved at night time by UM-MORUSES model. This study shows that the post-improvement UM-MORUSES model can provide detailed Seoul building information data and accurate surface air temperature and wind speed in urban region.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.185-194
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• 2016

The effect of artificial changes in geographical features on local wind was analyzed at the construction site of bridge and fill-up bank in the southern part of Haui-do. Geographic Information System (GIS) data and Computational Fluid Dynamics (CFD) model were used in this study. Three-dimensional numerical topography based on the GIS data for the target area was constructed for the surface boundary input data of the CFD model. The wind observations at an Automatic Weather Station (AWS) located in Haui-do were used to set-up the model inflows. The seasonal simulations were conducted. The differences in surface wind speed between after and before artificial changes in geographical features were analyzed. The surface wind speed decreases 5 to 20% at the south-western part and below 2% of the spatial average for salt field. There was also marked the effect of artificial changes in geographical features on local wind in the westerly wind case for the target area.

• Journal of Environmental Science International
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• v.19 no.3
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• pp.281-293
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• 2010

The present study explores time and spatial thermal environment for Daegu, which is a city built on a basin area, according to varying land cover conditions of the earth's surface by analyzing data derived from meteorological observation and satellite images. The study has classified land use by utilizing MODIS satellite images and analyzed land surface temperature. Also, by using data acquired from automatic weather system, the study has evaluated the effects of atmospheric heating caused by city pavements by analyzing the sensible heat flux between the city's land surface and the atmosphere. The results are as follows. 1) Classification of land use in the Daegu area shows 46.64% of urban and built-up area, 1.39% of watersides, 35.19% of forest, 11.43% of crops, and 5.37% grasslands. 2) During the weekdays throughout the year, the land surface temperature was high for Dalseogu, Bukgu, and Seogu regions where industrial complexes could be found. Comparatively, lower temperature could be observed in the woodlands. 3) While the land surface temperature displayed the effects of pushing air upwards during the weekdays in urban areas, the reverse was true for forest regions. During the night, the temperature did not exert any significant influence on air movement.

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.51-51
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• 2010

본 연구에서는 태풍 초기화된 수치모델과 AWS (Automatic Weather System) data를 이용하여 제주도를 통과하는 태풍들의 바람 강도 특성을 분석하였다. 태풍이 내습했을 때 제주도 전 지역에서 동시 관측을 하기에는 불가능하다. 따라서 중규모 수치 모델인 Advanced Research WRF v3.0.1을 사용하여 분석하였으며 더욱 정확한 태풍 모의를 위해 Kwon and Cheong (2009)에 의해 개발된 정교한 태풍 초기화 기법을 적용하였다. 태풍 초기화된 자료에 의해 모의된 결과는 The Regional Specialized Meteorological Center (RSMC) Tokyo의 예보 오차와 비교했을 때 더 향상된 결과를 보였으므로 태풍 초기화 기법의 사용은 본 연구에서 하고자하는 태풍들의 바람 강도 분석에 타당하다고 판단하였다. 그리고 모의된 결과는 그에 상응하는 AWS data와의 joint distribution (Moskaitis, 2008) 분석을 통해 비교되었다. 태풍 경로에 따른 제주도 지역의강 풍을 고려하기 위해 각각 제주도의 오른쪽과 왼쪽을 지나가는 2003년 6호 태풍 'SOUDELOR'와 2004년 7호 태풍 'MINDULLE'를 선정하였다. 또한, 모의 결과로부터 제주도 지역에 태풍이 내습했을 때 강풍의 상대적인 크기의 비교를 위해 모의된 태풍의 최대 풍속을 수치 모의로 얻은 10m 바람장의 모든 격자점에 나누어 정규화 하였다. 이를 시간에 대해 평균하여 태풍이 제주도 지역을 통과하는 전체시간에 대한 상대적인 강도 특성을 분석하였다. 수치 모의 결과와 관측 자료와의 joint distribution 분석 결과, 바람의 크기와 경향이 비교적 잘 일치하였다. 강한 풍속과 약한 풍속이 나타나는 지역은 제주도 지역의 주풍향과 지형의 영향에 크게 좌우되었다. 정규화된 바람은 산악의 정상에서 강풍이 관측되고 주 풍향에 대해 풍상측과 풍하측에서 비교적 낮은 풍속이 관측되는 결과를 보였다. 이는 Hoinka (1985)의 산악 위에서의 바람의 특성에 관한 연구에서 얻어진 결과와 유사하다. 서로 다른 경로로 통과하는 두 태풍의 모의 결과에서 제주도의 북서쪽 지역과 남동쪽 지역에서 상대적으로 약한 풍속이 관측되었다. 따라서 해당지역에서는 태풍에 동반되는 강풍의 피해를 적게 입을 것이라는 것을 알 수 있었다.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.2
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• pp.69-79
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• 2017

In this study, we developed real-time urban stream discharge forecasting model using short-term rainfall forecasts data simulated by a regional climate model (RCM). The National Centers for Environmental Prediction (NCEP) Climate Forecasting System (CFS) data was used as a boundary condition for the RCM, namely the Global/Regional Integrated Model System(GRIMs)-Regional Model Program (RMP). In addition, we make ensemble (ESB) forecast with different lead time from 1-day to 3-day and its accuracy was validated through temporal correlation coefficient (TCC). The simulated rainfall is compared to observed data, which are automatic weather stations (AWS) data and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA 3B43; 3 hourly rainfall with $0.25^{\circ}{\times}0.25^{\circ}$ resolution) data over midland of Korea in July 26-29, 2011. Moreover, we evaluated urban rainfall-runoff relationship using Storm Water Management Model (SWMM). Several statistical measures (e.g., percent error of peak, precent error of volume, and time of peak) are used to validate the rainfall-runoff model's performance. The correlation coefficient (CC) and the Nash-Sutcliffe efficiency (NSE) are evaluated. The result shows that the high correlation was lead time (LT) 33-hour, LT 27-hour, and ESB forecasts, and the NSE shows positive values in LT 33-hour, and ESB forecasts. Through this study, it can be expected to utilizing the real-time urban flood alert using short-term weather forecast.