• 대기
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• 제25권1호
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• pp.67-83
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• 2015

Predicting the location and intensity of precipitation still remains a main issue in numerical weather prediction (NWP). Resolution is a very important component of precipitation forecasts in NWP. Compared with a lower resolution model, a higher resolution model can predict small scale (i.e., storm scale) precipitation and depict convection structures more precisely. In addition, an ensemble technique can be used to improve the precipitation forecast because it can estimate uncertainties associated with forecasts. Therefore, NWP using both a higher resolution model and ensemble technique is expected to represent inherent uncertainties of convective scale motion better and lead to improved forecasts. In this study, the limited area ensemble prediction system for the convective-scale (i.e., high resolution) operational Unified Model (UM) in Korea Meteorological Administration (KMA) was developed and evaluated for the ensemble forecasts during August 2012. The model domain covers the limited area over the Korean Peninsula. The high resolution limited area ensemble prediction system developed showed good skill in predicting precipitation, wind, and temperature at the surface as well as meteorological variables at 500 and 850 hPa. To investigate which combination of horizontal resolution and ensemble member is most skillful, the system was run with three different horizontal resolutions (1.5, 2, and 3 km) and ensemble members (8, 12, and 16), and the forecasts from the experiments were evaluated. To assess the quantitative precipitation forecast (QPF) skill of the system, the precipitation forecasts for two heavy rainfall cases during the study period were analyzed using the Fractions Skill Score (FSS) and Probability Matching (PM) method. The PM method was effective in representing the intensity of precipitation and the FSS was effective in verifying the precipitation forecast for the high resolution limited area ensemble prediction system in KMA.

• 한국농림기상학회지
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• 제14권2호
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• pp.53-62
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• 2012

고해상도 기상자료 제공과 농림 분야에서의 요구를 충족시키기 위하여 LAPS를 이용하여 경기도 지역을 100m 해상도로 분석하였다. 구축된 시스템은 수치예보과에서 생산되는 6시간 간격 예측자료를 초기추정치로 사용하고, 각 관측자료를 동화하여 지표 온도와 습도 바람을 분석한다. 기존 분석시스템의 기상관측자료의 수집 방식을 개선하여 자료 수집에 소요되는 시간을 성공적으로 단축시킴으로써 약 20분 내에 기온, 상대습도, 풍향, 풍속에 대한 고해상도 분석결과 제공이 가능하게 되었다. 그러나 앞으로 LAPS 분석결과를 이용하여 관측이 가능한 지역 이외에 어느 지역에서든 정확한 농업기상정보를 산출할 수 있게 하려면 다양한 기상자료의 활용과 지표이용도의 개선, 관측지점의 영향반경을 최적화 시키는 과정들이 추가로 연구되어야 할 것이다. 현재 구축된 시스템의 분석결과 정확도는 떨어지지만 LAPS의 내부 알고리즘에 대한 미세한 조정으로 향상이 가능하므로 농업기상요소 생성을 위한 최적화 작업들을 수행한다면 정확도 향상을 꾀할 수 있을 것이다. 또한 다양한 기상요소에 대한 분석이 가능하기 때문에 특별한 기상요소들을 필요로 하는 농림 분야의 요구를 충족 시킬 수 있도록 분석요소의 확장이 가능 할 것이다.

• 한국환경과학회지
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• 제13권10호
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• pp.891-902
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• 2004

In order to predict air pollution and Yellow-sand dispersion precisely, it is necessary to clarify the sensitivity of meteorological field input interval. Therefore numerical experiment by atmospheric dynamic model(RAMS) and atmospheric dispersion model(PDAS) was performed for evaluating the effect of temporal and spatial resolution of meteorological data on particle dispersion. The results are as follows: 1) Base on the result of RAMS simulation, surface wind direction and speed can either synchronize upper wind or not. If surface wind and upper wind do not synchronize, precise prediction of Yellow-sand dispersion is strongly associated with upwelling process of sand of particle. 2) There is no significant discrepance in distribution of particle under usage of difference temporal resolution of meteorological information at early time of simulation, but the difference of distribution of particles become large as time goes by. 3) There is little difference between calculated particles distributions in dispersion experiments with high temporal resolution of meteorological data. On the other hand, low resolution of meteorological data occur the quantitative difference of particle density and there is strong tendency to the quantitative difference.

• 한국대기환경학회지
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• 제24권6호
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• pp.649-661
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• 2008

The impact of the detailed surface data on regional meteorological fields in complex coastal area is studied using RAMS. Resolutions of topography and land use data are very important to numerical modeling, because high resolution data can reflect correct terrain height and detail characteristics of the surface. Especially, in complex coastal region such as Gwangyang area, southern area in Korean Peninsula, high resolution topography and land use data are indispensable for accurate modeling results. This study investigated the effect of resolutions of terrain data using SRTM with 3 second resolution topography and KLU with 1 second resolution land use data. Case HR was the experiment using high resolution data, whereas Case LR used low resolution data. In Case HR, computed surface temperature was higher than Case LR along the coastline and wind speed was $1{\sim}2m/s$ weaker than Case LR. Time series of temperature and wind speed indicated great agreement with the observation data. Moreover, Case HR indicated outstanding results on statistical analysis such as regression, root mean square error, index of agreement.

• 대기
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• 제32권3호
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• pp.179-189
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• 2022

The purpose of this study is to build and evaluate a high-resolution (50 m) KMAPP (Korea Meteorological Administration Post Processing) reflecting building data. KMAPP uses LDAPS (Local Data Assimilation and Prediction System) data to detail ground wind speed through surface roughness and elevation corrections. During the detailing process, we improved the vegetation roughness data to reflect the impact of city buildings. AWS (Automatic Weather Station) data from a total of 48 locations in the metropolitan area including Seoul in 2019 were used as the observation data used for verification. Sensitivity analysis was conducted by dividing the experiment according to the method of improving the vegetation roughness length. KMAPP has been shown to improve the tendency of LDAPS to over simulate surface wind speeds. Compared to LDAPS, Root Mean Square Error (RMSE) is improved by approximately 23% and Mean Bias Error (MBE) by about 47%. However, there is an error in the roughness length around the Han River or the coastline. Accordingly, the surface roughness length was improved in KMAPP and the building information was reflected. In the sensitivity experiment of improved KMAPP, RMSE was further improved to 6% and MBE to 3%. This study shows that high-resolution KMAPP reflecting building information can improve wind speed accuracy in urban areas.

• 대기
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• 제31권1호
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• pp.1-15
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• 2021

High-resolution wind resources maps (maps, here after) with spatial and temporal resolutions of 100 m and 3-hours, respectively, over South Korea have been produced and evaluated for the period from July 2016 to June 2017 using Korea Meteorological Administration (KMA) Post Processing (KMAPP). Evaluation of the 10 m- and 80 m-level wind speed in the new maps (KMAPP-Wind) and the 1.5 km-resolution KMA NWP model, Local Data Assimilation and Prediction System (LDAPS), shows that the new high-resolution maps improves of the LDAPS winds in estimating the 10m wind speed as the new data reduces the mean bias (MBE) and root-mean-square error (RMSE) by 33.3% and 14.3%, respectively. In particular, the result of evaluation of the wind at 80 m which is directly related with power turbine shows that the new maps has significantly smaller error compared to the LDAPS wind. Analyses of the new maps for the seasonal average, maximum wind speed, and the prevailing wind direction shows that the wind resources over South Korea are most abundant during winter, and that the prevailing wind direction is strongly affected by synoptic weather systems except over mountainous regions. Wind speed generally increases with altitude and the proximity to the coast. In conclusion, the evaluation results show that the new maps provides significantly more accurate wind speeds than the lower resolution NWP model output, especially over complex terrains, coastal areas, and the Jeju island where wind-energy resources are most abundant.

• 대기
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• 제32권4호
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• pp.307-322
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• 2022

A drone has recently got attention as an instrument for weather observation in lower atmosphere because it can produce the high spatiotemporal resolution weather data even though the weather phenomenon is inaccessible. Sea fog is a weather phenomenon occurred in lower atmosphere, and has observational limitations because it occurs on the sea. Therefore, goal of this study is to analyze the vertical structures about inflow, development and dispersion of sea fog using the high-resolution weather data with the meteorological sensor-equipped drone. This study observed sea fogs in the west coast of the Korean peninsula from March to October 2021 and investigated one sea fog inflowed into the coast on June 8th 2021. θ_e - q_v diagrams (θ_e: equivalent potential temperature, q_v: water vapor ratio) and vertical wind structures were analyzed. At inflow of sea fog, moist adiabatically stable layer was formed in 0-300 m and prevailing wind was switched from south-southwesterly to west-southwesterly under 120 m. Both changes are favorable for sea fog on the location. θ_e and q_v plummeted in a layer 0-183 m. The inflowed sea fog developed from 183 m to 327 m by mixing with ambient atmosphere on top of sea fog. Also, strong mechanical turbulence near ground drove a vertical mixing under stable layer. At dispersion of sea fog, as θ_e on ground gradually increased, air condition was changed to neutral. Evaporation occurred on both bottom and top in sea fog. These results induced dissipation of sea fog.

• Journal of Radiation Protection and Research
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• 제48권1호
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• pp.28-43
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• 2023

Background: High-fidelity meteorological data is a prerequisite for the realistic simulation of atmospheric dispersion of radioactive materials near nuclear power plants (NPPs). However, many meteorological models frequently overestimate near-surface wind speeds, failing to represent local meteorological conditions near NPPs. This study presents a new high-resolution (approximately 1 km) meteorological downscaling method for modeling short-range (< 100 km) atmospheric dispersion of accidental NPP plumes. Materials and Methods: Six considerations from literature reviews have been suggested for a new dynamic downscaling method. The dynamic downscaling method is developed based on the Weather Research and Forecasting (WRF) model version 3.6.1, applying high-resolution land-use and topography data. In addition, a new subgrid-scale topographic drag parameterization has been implemented for a realistic representation of the atmospheric surface-layer momentum transfer. Finally, a year-long simulation for the Kori and Wolsong NPPs, located in southeastern coastal areas, has been made for 2016 and evaluated against operational surface meteorological measurements and the NPPs' on-site weather stations. Results and Discussion: The new dynamic downscaling method can represent multiscale atmospheric motions from the synoptic to the boundary-layer scales and produce three-dimensional local meteorological fields near the NPPs with a 1.2 km grid resolution. Comparing the year-long simulation against the measurements showed a salient improvement in simulating near-surface wind fields by reducing the root mean square error of approximately 1 m/s. Furthermore, the improved wind field simulation led to a better agreement in the Eulerian estimate of the local atmospheric dispersion. The new subgrid-scale topographic drag parameterization was essential for improved performance, suggesting the importance of the subgrid-scale momentum interactions in the atmospheric surface layer. Conclusion: A new dynamic downscaling method has been developed to produce high-resolution local meteorological fields around the Kori and Wolsong NPPs, which can be used in short-range atmospheric dispersion modeling near the NPPs.

• 대기
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• 제30권3호
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• pp.277-291
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• 2020

Low-level wind shear (LLWS) events on glide path at Jeju International Airport (CJU) are evaluated using the Aircraft Meteorological Data Relay (AMDAR) and Korea Meteorological Administration Post-Processing (KMAPP) with 100 m spatial resolution. LLWS that occurs in the complex terrains such as Mt. Halla on the Jeju Island affects directly aircraft approaching to and/or departing from the CJU. For this reason, accurate prediction of LLWS events is important in the CJU. Therefore, the use of high-resolution Numerical Weather Prediction (NWP)-based forecasts is necessary to cover and resolve these small-scale LLWS events. The LLWS forecasts based on the KMAPP along the glide paths heading to the CJU is developed and evaluated using the AMDAR observation data. The KMAPP-LLWS developed in this paper successfully detected the moderate-or-greater wind shear (strong than 5 knots per 100 feet) occurred on the glide paths at CJU. In particular, this wind shear prediction system showed better performance than conventional 1-D column-based wind shear forecast.

• 한국농공학회논문집
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• 제59권5호
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• pp.31-40
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• 2017

The aim of this study is to estimate net irrigation requirements for red pepper during growing period using soil moisture model. The soil moisture model based on water balance approach simulates soil moisture contents of 4 soil layers in crop root zone considering soil moisture extraction pattern. The LAMP (Land-Atmosphere Modeling Package) high resolution meteorological data provided from National Center for AgroMeteorology (NCAM) was used to simulate soil moisture as the input weather data. Study area for the LAMP data and soil moisture simulation covers $36.92^{\circ}{\sim}37.40^{\circ}$ in latitude and $127.36^{\circ}{\sim}127.94^{\circ}$ in longitude. Soil moisture was monitored using FDR (Frequency Domain Reflectometry) sensors and the data were used to validate the simulation model from May 24 to October 20 in 2016. The results showed spatially detailed soil moisture pattern under different weather conditions and soil texture. Net irrigation requirements were also different by location reflecting the spatially distributed weather condition. The average of the requirements was 470.7 mm and averages about soil texture were 466.8 mm, 482.4 mm, 456.0 mm, 481.7 mm, and 465.6 mm for clay loam, sandy loam, silty clay loam, clay, and sand respectively. This study showed spatial differences of soil moisture and the irrigation requirements of red pepper about spatially uneven weather condition and soil texture. From the results, it was demonstrated that high resolution meteorological data could provide an opportunity of spatially different crop water requirement estimation during the irrigation management.