• 한국지구과학회지
• /
• 제44권6호
• /
• pp.578-593
• /
• 2023

2017년 7월 15일 서울과 수도권에 집중호우를 발생시킨 깊은 대류운과 강수 발달에 대한 종관 기상 메커니즘을 규명하고 중국 동부지역으로부터의 PM_2.5 에어로졸의 간접효과를 WRF-Chem 실험을 통해 분석하였다. WRF-Chem 모델에 에어로졸과 복사의 피드백, 구름 화학 과정, 습식 세정을 모두 포함한 ARI (Aerosol Radiation Interaction) 실험과 에어로졸과 복사의 피드백을 제외하고 구름 화학 과정, 습식 세정만을 포함한 ACR (Aerosol Cloud Radiation interaction) 실험 결과의 차이로부터 PM_2.5 에어로졸 간접효과를 산출하였다. 2017년 7월 15일 새벽에 황해와 한반도에서는 동아시아 대륙에서 저기압-북서 태평양의 고기압 분포로 인해 중국 남동 지역과 동중국해로부터 덥고 습한 기류가 수렴하고 있었다. 이러한 황해의 종관 기상에 의해 발달하는 대류운은 높이 12 km 이상이며 고체 수상체를 형성하고 있었는데, 이는 주로 대륙 위에서 발달하는 한랭운(많은 빙정을 형성하며 운정고도가 8 km 이상)의 특성을 나타내고 있었다. 특히, WRF-Chem 모델 실험을 통해 중국 동부지역으로부터 확산하는 PM_2.5 에어로졸이 구름물 형성에 5.7%, 고체 수상체 형성에 10.4%, 그리고 액체 수상체 형성에 10.8%로 대류운이 한랭운으로 발달하는 데 기여하고 있었다. 본 연구는 황해 위에서 깊은 대류운이 발달하는 과정에 대한 기상적 메커니즘과 더불어 중국 동부지역으로부터 에어로졸에 의한 간접효과의 영향을 제시하였다.

• 한국가스학회지
• /
• 제19권1호
• /
• pp.51-56
• /
• 2015

To assess downward positions of water spray for the small-scale release of chlorine gas, dispersion coefficients for the Gaussian dispersion model were validated at the small-scale release experiment. And the downwind distances of water spray were assessed with the simulated results. As results, the Gaussian plume model using the Briggs' dispersion coefficient well estimated the dispersed characteristics for small-scale release of chlorine gas. The best adequate downwind position of water spray is the position of the maximum concentration of chlorine at the ground level. And the adequate vertical and horizontal dimensions of water spray consider the maximum width and height of cloud.

• Water Engineering Research
• /
• 제3권2호
• /
• pp.123-134
• /
• 2002

A developed Quantitative Flood Forecasting (QFF) model was applied to the mid-Atlantic region of the United States. The model incorporated the evolving structure and frequency of intense weather systems of the study area for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters associated with synoptic atmospheric conditions as Input. Here, we present results from the application of the Quantitative Flood Forecasting (QFF) model in 2 small watersheds along the leeward side of the Appalachian Mountains in the mid-Atlantic region. Threat scores consistently above 0.6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 40% and up to 55 % were obtained.

• Water Engineering Research
• /
• 제3권2호
• /
• pp.113-122
• /
• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict flash floods. In this study, a Quantitative Flood Forecasting (QFF) model was developed by incorporating the evolving structure and frequency of intense weather systems and by using neural network approach. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as lifetime, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. All these processes stretched leadtime up to 18 hours. The QFF model will be applied to the mid-Atlantic region of United States in a forthcoming paper.

• 대한조선학회논문집
• /
• 제61권3호
• /
• pp.143-151
• /
• 2024

In this study, we present a mapping framework for 3D spatial reconstruction of digital twin model using navigation and perception sensors mounted on an Autonomous Surface Vehicle (ASV). For improving the level of realism of digital twin models, 3D spatial information should be reconstructed as a digitalized spatial model and integrated with the components and system models of the ASV. In particular, for the 3D spatial reconstruction, color and 3D point cloud data which acquired from a camera and a LiDAR sensors corresponding to the navigation information at the specific time are required to map without minimizing the noise. To ensure clear and accurate reconstruction of the acquired data in the proposed mapping framework, a image preprocessing was designed to enhance the brightness of low-light images, and a preprocessing for 3D point cloud data was included to filter out unnecessary data. Subsequently, a point matching process between consecutive 3D point cloud data was conducted using the Generalized Iterative Closest Point (G-ICP) approach, and the color information was mapped with the matched 3D point cloud data. The feasibility of the proposed mapping framework was validated through a field data set acquired from field experiments in a inland water environment, and its results were described.

• 한국환경과학회지
• /
• 제32권12호
• /
• pp.899-914
• /
• 2023

Various seeding materials for cloud seeding are being used, and sodium chloride powder is one of them, which is commonly used. This study analyzed the experimental results of multi-aircraft cloud seeding in connection with Republic of Korea Air Force (CN235) and KMA/NIMS(Korea Meteorological Administration/National Institute of Meteorological Sciences) Atmospheric Research Aircraft. Powdered sodium chloride was used in CN235 for the first time in South Korea. The analysis of the cloud particle size distributions and radar reflectivity before and after cloud seeding showed that the growth efficiency of powdery seeding material in the cloud is slightly higher than that of hygroscopic flare composition in the distribution of number concentrations by cloud aerosol particle diameter (10 ~ 1000 ㎛). Considering the radar reflectivity, precipitation, and numerical model simulation, the enhanced precipitation due to cloud seeding was calculated to be a maximum of 3.7 mm for 6 hours. The simulated seeding effect area was about 3,695 km², which corresponds to 13,634,550 tons of water. In the precipitation component analysis, as a direct verification method, the ion equivalent concentrations (Na⁺, Cl^-, Ca²⁺) of the seeding material at the Bukgangneung site were found to be about 1000 times higher than those of other non-affected areas between about 1 and 2 hours after seeding. This study suggests the possibility of continuous multi-aircraft cloud seeding experiments to accumulate and increase the amount of precipitation enhancement.

• 대한의용생체공학회:의공학회지
• /
• 제44권2호
• /
• pp.147-156
• /
• 2023

Efforts to employ smart home sensors to monitor the indoor activities of elderly single residents have been made to assess the feasibility of a safe and healthy lifestyle. However, the bathroom remains an area of blind spot. In this study, we have developed and evaluated a new edge computer device that can automatically detect water usage activities in the bathroom and record the activity log on a cloud server. Three kinds of sound as flushing, showering, and washing using wash basin generated during water usage were recorded and cut into 1-second scenes. These sound clips were then converted into a 2-dimensional image using MEL-spectrogram. Sound data augmentation techniques were adopted to obtain better learning effect from smaller number of data sets. These techniques, some of which are applied in time domain and others in frequency domain, increased the number of training data set by 30 times. A deep learning model, called CRNN, combining Convolutional Neural Network and Recurrent Neural Network was employed. The edge device was implemented using Raspberry Pi 4 and was equipped with a condenser microphone and amplifier to run the pre-trained model in real-time. The detected activities were recorded as text-based activity logs on a Firebase server. Performance was evaluated in two bathrooms for the three water usage activities, resulting in an accuracy of 96.1% and 88.2%, and F1 Score of 96.1% and 87.8%, respectively. Most of the classification errors were observed in the water sound from washing. In conclusion, this system demonstrates the potential for use in recording the activities as a lifelog of elderly single residents to a cloud server over the long-term.

• 대기
• /
• 제20권2호
• /
• pp.131-151
• /
• 2010

This study establishes a conceptual model to analyze heavy rainfall events in Korea using multi-functional transport satellite-1R satellite images. Three heavy rainfall episodes in two major synoptic types, such as synoptic low (SL) type and synoptic flow convergence (SC) type, are analyzed through a conceptual model procedure which proceeds on two steps: 1) conveyer belt model analysis to detect convective area, and 2) cloud top temperature analysis from black body temperature (TBB) data to distinguish convective cloud from stratiform cloud, and eventually estimate heavy rainfall area and intensity. Major synoptic patterns causing heavy rainfall are Changma, synoptic low approach, upper level low in the SL type, and upper level low, indirect effect of typhoon, convergence of tropical air in the SC type. The relationship between rainfall and TBBs in overall well resolved areas of heavy rainfall. The SC type tended to underestimate the intensity of heavy rainfall, but the analysis with the use of water vapor channel has improved the performance. The conceptual model improved a concrete utilization of images and data of satellite, as summarizing characteristics of major synoptic type causing heavy rainfall and composing an algorism to assess the area and intensity of heavy rainfall. The further assessment with various cases is required for the operational use.

• 한국대기환경학회지
• /
• 제24권5호
• /
• pp.604-612
• /
• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.

• 한국수자원학회논문집
• /
• 제53권11호
• /
• pp.973-983
• /
• 2020

최근 인공위성 자료를 기반으로 한 수자원 관측 분야에서는 공간해상도의 한계를 극복하기 위한 방안으로 SAR (Synthetic Aperture Radar) 센서에 대한 관심이 높아지고 있다. 토양수분을 관측하는 기존 위성 자료가 10 km 이상의 공간해상도를 지닌 반면, SAR 센서는 후방산란계수를 10 m 까지 관측할 수 있으므로 공간적인 분포를 보다 세밀하게 분석할 수 있다. 이러한 자료를 활용하기 위해서는 관측된 후방산란계수에 다양한 수문인자 및 환경적 요인이 미치는 영향을 다각적으로 분석하여 토양수분을 산출하는 과정이 필요하다. 본 연구는 토양수분 산정에 주로 적용되고 있는 WCM(Water Cloud Model)과 선형회귀 기법을 국내 5개 지점에 적용함으로써, SAR 영상을 기반으로 토양수분을 산정하고 이를 지점 관측 자료와 비교하여 평가하고자 하였다. WCM의 경우 토양수분의 즉각적인 변화를 관측하기에 용이하나 오차에 대한 보정이 필요한 것으로 판단되며, 선형회귀 방법은 순간적인 토양수분의 변동이 크게 나타나지 않았으나 안정적인 오차 범위를 나타내었다. 또한 토양수분이 후방산란계수에 미치는 영향은 토지피복, 식생의 분포, 식생 내 수분량의 정도에 따라 모델별로 크게 상이한 결과를 나타냄을 알 수 있으며, 기존의 모델을 동일하게 적용하기에는 한계점이 많음을 알 수 있다. 따라서 복잡한 지형적, 수문학적 특성을 가진 한반도에서 SAR 영상을 수자원 분야에 적용하기 위해서는, 추후 각 지점 별 특성에 따른 영향을 다각적으로 분석하는 과정이 필수적이며 한반도에 적합한 토양수분 모델을 구축하기 위한 연구가 수행되어야 할 것으로 판단된다.