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

• 한국대기환경학회지
• /
• 제19권5호
• /
• pp.595-610
• /
• 2003

The statistical indexes such as RMSE (Root Mean Square Error), Mean Bias error, and IOA (Index of agreement) are used to evaluate 3 Dimensional wind and temperature fields predicted by operational meteorological model RAMS (Regional Atmospheric Meteorological System) implemented in CARIS (Chemical Accident Response Information System) for the dispersion forecast of hazardous chemicals in case of the chemical accidents in Korea. The operational atmospheric model, RAMS in CARIS are designed to use GDAPS, GTS, and AWS meteorological data obtained from KMA (Korean Meteorological Administration) for the generation of 3-dimensional initial meteorological fields. The predicted meteorological variables such as wind speed, wind direction, temperature, and precipitation amount, during 19 ∼ 23, August 2002, are extracted at the nearest grid point to the meteorological monitoring sites, and validated against the observations located over the Korean peninsula. The results show that Mean bias and Root Mean Square Error are 0.9 (m/s), 1.85 (m/s) for wind speed at 10 m above the ground, respectively, and 1.45 ($^{\circ}C$), 2.82 ($^{\circ}C$) for surface temperature. Of particular interest is the distribution of forecasting error predicted by RAMS with respect to the altitude; relatively smaller error is found in the near-surface atmosphere for wind and temperature fields, while it grows larger as the altitude increases. Overall, some of the overpredictions in comparisons with the observations are detected for wind and temperature fields, whereas relatively small errors are found in the near-surface atmosphere. This discrepancies are partly attributed to the oversimplified spacing of soil, soil contents and initial temperature fields, suggesting some improvement could probably be gained if the sub-grid scale nature of moisture and temperature fields was taken into account. However, IOA values for the wind field (0.62) as well as temperature field (0.78) is greater than the 'good' value criteria (> 0.5) implied by other studies. The good value of IOA along with relatively small wind field error in the near surface atmosphere implies that, on the basis of current meteorological data for initial fields, RAMS has good potentials to be used as a operational meteorological model in predicting the urban or local scale 3-dimensional wind fields for the dispersion forecast in association with hazardous chemical releases in Korea.

• 한국대기환경학회지
• /
• 제20권5호
• /
• pp.633-645
• /
• 2004

A critical component of air pollution modeling is the representation of meteorological fields within a model domain, since an accurate air quality simulation requires an accurate portrayal of the three-dimensional wind fields. The present study investigated data assimilation using surface observational data in the complex coastal regions to simulate an accurate meteorological fields. Surface observational data were categorized into three groups(Near coastal region, Far coastal regiln 1, Far costal region 2) by the locations where the data are. Experiments were designed and MM5 was used in each case of regions. Case 1 is an experiment without data assimilation, Case N is executed with data assimilation using observational data by meteorological stations and AWS data located in the near coastal region, within 1 km. Case F1 is also an experiment with data assimilation using observational data by meteorological stations and AWS data located in the far coastal regiln 1, more than 1km and less than 5km from the coastal lines. Case F2 is appled to data assimilation using observational data by meteorological stations and AWS data located in the far coastal region 2, beyond 5km from the coastal lines. The result of this study indicated that data assimilation using data in the far coastal region 1 and 2 provided an attractive method for generating accurate meteorological fields, especially in the complex coastal regions.

• 한국대기환경학회지
• /
• 제25권5호
• /
• pp.432-449
• /
• 2009

In this study, the effects of high-resolution land cover on the simulation of near-surface meteorological fields were evaluated in two different coastal regions using Weather Research and Forecasting (WRF) model. These analyses were performed using the middle classification land cover data upgraded by the Korean Ministry of Environment (KME). For the purpose of this study, two coastal areas were selected as follows: (1) the southwestern coastal (SWC) region characterized by complex shoreline and (2) the eastern coastal (EC) region described a high mountain and a simple coastline. The result showed that the application of high-resolution land cover were found to be notably distinguished between the SWC and EC regions. The land cover improvement has contributed to generate the realistic complex coastline and the distribution of small islands in the SWC region and the expansion of urban and built-up land along the sea front in the EC region, respectively. The model study indicated that the improvement of land cover caused a temperature change on wide areas of inland and nearby sea for the SWC region, and narrow areas along the coastal line for the EC region. These temperature variations in the two regions resulted in a decrease and an increase in land-breeze and sea-breeze intensity, respectively (especially the SWC region). Interestingly, the improvement of land cover can contribute large enough to change wind distributions over the sea in coastal areas.

• 한국대기환경학회지
• /
• 제21권2호
• /
• pp.169-178
• /
• 2005

A critical component of air pollution modeling is the representation of atmospheric flow fields within a model domain, since an accurate air quality simulation requires an accurate portrayal of the three-dimensional wind fields. The present study investigated data assimilation using surface observational data in the complex coastal regions to simulate a realistic atmospheric flow fields. Surface observational data were categorized into three groups (Near coastal region, Far coastal region 1, Far costal region 2) by the locations where the sites are. Experiments were designed according to the location of observational stations and MM5/CALPUFF was used. The results of numerical simulation of atmospheric flow fields are used as input data for CALPUFF which predicts dispersion fields of air pollutants. The result of this study indicated that data assimilation using data in the far coastal region 2 provided an attractive method for generating realistic meteorological fields and dispersion fields of air pollutants in Gwangyang area because data in the near coastal region are variable and narrow representation.

• Ocean and Polar Research
• /
• 제40권3호
• /
• pp.99-114
• /
• 2018

In the present study, we assess the GloSea5 (Global Seasonal Forecasting System version 5) near-surface ocean current forecasts using globally observed surface drifter dataset. Annual mean surface current fields at 0-day forecast lead time are quite consistent with drifter-derived velocity fields, and low values of root mean square (RMS) errors distributes in global oceans, except for regions of high variability, such as the Antarctic Circumpolar Current, Kuroshio, and Gulf Stream. Moreover a comparison with the global high-resolution forecasting system, HYCOM (Hybrid Coordinate Ocean Model), signifies that GloSea5 performs well in terms of short-range surface-current forecasts. Predictions from 0-day to 4-week lead time are also validated for the global ocean and regions covering the main ocean basins. In general, the Indian Ocean and tropical regions yield relatively high RMS errors against all forecast lead times, whilst the Pacific and Atlantic Oceans show low values. RMS errors against forecast lead time ranging from 0-day to 4-week reveal the largest increase rate between 0-day and 1-week lead time in all regions. Correlation against forecast lead time also reveals similar results. In addition, a strong westward bias of about $0.2m\;s^{-1}$ is found along the Equator in the western Pacific on the initial forecast day, and it extends toward the Equator of the eastern Pacific as the lead time increases.

• 대기
• /
• 제26권2호
• /
• pp.277-288
• /
• 2016

Polar lows are intense mesoscale cyclones that mainly occur over the sea in polar regions. Owing to their small spatial scale of a diameter less than 1000 km, simulating polar lows is a challenging task. At King Sejong station in West Antartica, polar lows are often observed. Despite the recent significant climatic changes observed over West Antarctica, adequate validation of regional simulations of extreme weather events such as polar lows are rare for this region. To address this gap, simulation results from a recent version of the Polar Weather Research and Forecasting model (Polar WRF) covering Antartic Peninsula at a high horizontal resolution of 3 km are validated against near-surface meteorological observations. We selected a case of high wind speed event on 7 January 2013 recorded at Automatic Meteorological Observation Station (AMOS) in King Sejong station, Antarctica. It is revealed by in situ observations, numerical weather prediction, and reanalysis fields that the synoptic and mesoscale environment of the strong wind event was due to the passage of a strong mesoscale polar low of center pressure 950 hPa. Verifying model results from 3 km grid resolution simulation against AMOS observation showed that high skill in simulating wind speed and surface pressure with a bias of $-1.1m\;s^{-1}$ and -1.2 hPa, respectively. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation of Antartic weather systems and the near-surface meteorological instruments installed in King Sejong station can provide invaluable data for polar low studies over West Antartica.

• 한국환경과학회지
• /
• 제18권5호
• /
• pp.489-499
• /
• 2009

In an effort to examine the Regional Atmospheric Modeling System (RAMS ver. 4.3) to the initial meteorological input data, detailed observational data of NOAA satellite SST (Sea Surface Temperature) was employed. The NOAA satellite SST which is currently provided daily as a seven-day mean value with resolution of 0.1 $^{\circ}$ grid spacing was used instead of the climatologically derived monthly mean SST using in RAMS. In addition, the RAMS SST data must be changed new one because it was constructed in 1993. For more realistic initial meteorological fields, the NOAA satellite SST was incorporated into the RAMS-preprocess package named ISentropic Analysis package (ISAN). When the NOAA SST data was imposed to the initial condition of prognostic RAMS model, the resultant performance of near surface atmospheric fields was discussed and compared with that of default option of SST. We got the good results that the new SST data was made in a standard RAMS format and showed the detailed variation of SST. As the modeling grid became smaller, the SST differences of the NOAA SST run and the RAMS SST43 (default) run in diurnal variation were very minor but this research can apply to further study for the realistic SST situation and the development in predicting regional atmospheric field which imply the regional circulation due to differential surface heating between sea and land or climatological phenomenon.

• 한국지구과학회지
• /
• 제34권6호
• /
• pp.561-574
• /
• 2013

본 연구에서는 낙동강 강정고령보 근처에서 2011년 7월부터 2012년 9월까지 1년 이상 관측된 에너지 플럭스 자료의 분석을 통해 강 주변 농경지와 도시에 따른 플럭스 특징을 알아보고 향후 영향평가에 활용 가능한 자료인지 평가하고자 하였다. 연구 대상지는 농경지로 둘러싸인 시골지역과 도시공단 지역에 위치하였다. 현열 및 잠열 플럭스를 풍향에 따라 분석하였다. 여름에 바람이 강쪽에서 불어올 때 두 관측지점 모두 현열은 감소하고 잠열은 증가하는 형태를 보였다. 이는 강으로부터 전달된 수분에 의한 것으로 파악된다. 보웬비, 에너지 수지 닫힘, 운동량 플럭스, 안정도에 대한 분석 또한 이루어졌다. 두 지점간 보웬비를 비교한 결과 전 계절에 걸쳐 도시 지역의 보웬비가 농경지 지역의 보웬비보다 더 높았다. 에너지 수지 닫힘은 도시 지역에서 더 낮게 나타났는데 이는 도시 지역에서 저장항 계산이 배제되었기 때문으로 보인다. 운동량 플럭스는 여름과 겨울 두 계절 모두 도시 지역에서 더 높게 나타났다. 강한 난류를 보이는 주간과 여름에 불안정한 상태가 장시간 지속되었다. 이들 지점에서 관측된 자료는 향후 강이 주변지역에 미치는 영향에 대한 연구에 사용하기 적절한 것으로 보인다.

• 한국콘텐츠학회논문지
• /
• 제19권11호
• /
• pp.12-21
• /
• 2019

4차산업혁명시대에 드론은 새로운 기술과 접목할 수 있는 유연한 기기로 자리매김하였다. 드론은 처음에 군사용 무인 항공기로 개발되었으며, 지금은 다양한 분야(건설, 물류·운송, 소방·안전, 환경·기상, 농업, 뉴스·미디어, 등)에 활용되고 있다. 환경 기상 관측 부분에서 대기경계층은 지표면에 가까워 기상현상이 가장 활발히 일어나는 대기층으로 인간 활동에 밀접한 영향을 준다. 이러한 대기 경계층의 연구 수행을 위하여 하층 대기에 대한 정밀 관측이 필요하며, 이에 따른 관측 기술의 확보가 필수적이다. 기상 분야에서의 드론은 항공기, 라디오존데 등 기존 장비에 비하여 비교적 저렴한 유지비용으로 기상관측에 활용이 가능하며, 다양한 센서와 함께 활용할 경우, 대기경계층 및 국지 기상연구에 폭넓게 활용될 수 있다. 본 연구에서는 국립기상과학원에서 보유중인 드론에 복합기상센서 및 라디오존데 센서를 탑재후 연직 기상관측(온도, 습도) 실험을 수행함으로써 드론을 활용한 기상관측의 가능성을 확인하였다.