• 대한원격탐사학회지
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• 제32권4호
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• pp.339-351
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• 2016

For the safety of sea, it is important to monitor sea fog, one of the dangerous meteorological phenomena which cause marine accidents. To detect and monitor sea fog, Moderate Resolution Imaging Spectroradiometer (MODIS) data which is capable to provide spatial distribution of sea fog has been used. The previous automatic sea fog detection algorithms were focused on detecting sea fog using Terra/MODIS only. The improved algorithm is based on the sea fog detection algorithm by Wu and Li (2014) and it is applicable to both Terra and Aqua MODIS data. We have focused on detecting spring season sea fog events in the Yellow Sea. The algorithm includes application of cloud mask product, the Normalized Difference Snow Index (NDSI), the STandard Deviation test using infrared channel ($STD_{IR}$) with various window size, Temperature Difference Index(TDI) in the algorithm (BTCT - SST) and Normalized Water Vapor Index (NWVI). Through the calculation of the Hanssen-Kuiper Skill Score (KSS) using sea fog manual detection result, we derived more suitable threshold for each index. The adjusted threshold is expected to bring higher accuracy of sea fog detection for spring season daytime sea fog detection using MODIS in the Yellow Sea.

• 대기
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• 제22권2호
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• pp.163-174
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• 2012

Brightness temperature (BT) difference between sea fog and sea surface is small, because the top height of fog is low. Therefore, it is very difficult to detect sea fog with infrared (IR) channels in the nighttime. To overcome this difficulty, we have developed a new algorithm for detection of sea fog that consists in three tests. Firstly, both stratus and sea fog were discriminated from the other clouds by using the difference between BTs $3.7{\mu}m$ and $11{\mu}m$. Secondly, stratus occurring at a level higher than sea fog was removed when the difference between cloud top temperature and sea surface temperature (SST) is smaller than 3 K. In this process, we used daily SST data from AMSR-E microwave measurements that is available even in the presence of cloud. Then, the SST was converted to $11{\mu}m$ BT based on the regressed relationship between AMSR-E SST and MTSAT-1R $11{\mu}m$ BT at 1733 UTC over clear sky regions. Finally, stratus was further removed by using the homogeneity test based on the difference in cloud top texture between sea fog and stratus. Comparison between the retrievals from our algorithm and that from Korea Meteorological Administration (KMA) algorithm, shows that the KMA algorithm often misconceived sea fog as stratus, resulting in underestimating the occurrence of sea fog. Monthly distribution of sea fog over northeast Asia in 2008 was derived from the proposed algorithm. The frequency of sea fog is lowest in winter, and highest in summer especially in June. The seasonality of the sea fog occurrence between East and West Sea was comparable, while it is not clearly identified over South Sea. These results would serve to prevent the possible occurrence of marine accidents associated with sea fog.

• 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.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2023년도 추계학술대회
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• pp.23-26
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• 2023

과거에는 주요 항로 인근의 해양안개(sea fog)를 관측하고 이를 선박들의 안전 운항을 위한 실시간 정보를 제공하는 데 있어서, 작동 원리가 유사한 기상관측용 시정계(Visibility Sensor) 또는 항로표지용 안개감지기(fog detector) 등을 설치하여, 장비가 설치된 곳 인근의 국지적인 안개를 관측하고 있었다. 하지만 먼지, 염분 및 꽃가루 등에 의한 오염이나 거미줄 같은 생물에 의한 감지 센서의 오동작이 자주 발생되어, 실시간 관측 정보의 신뢰성이 다소 낮은 상황이었기 때문에 실시간으로 해양안개 관측정보를 선박이나 이용자에게 즉각 제공하기에는 다소 무리가 있었다. 2019년부터 2022년까지 기상청과 해양수산부 항로표지과 등이 협업을 통해, 보다 신뢰성 있는 실시간 영상기반 해양안개관측 시스템을 전국 주요 항로에 있는 항로표지시설(Lighthouse) 100개 국소에 구축하여 신뢰성 있는 해양안개관측 정보를 매 10분마다 수집하고, 이를 실시간으로 대국민 서비스(웹페이지)를 수행하게 되었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.214-218
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• 1999

The aim of our study is to develop new algorism for sea fog detection by using Geostational Meteorological Satellite-5(GMS-5) and suggest the techniques of its continuous detection. So as to detect daytime sea fog/stratus(00UTC, May 10, 1999), visible accumulated histogram method and surface albedo method are used. The characteristic value during daytime showed A(min) > 20％ and DA < 10％ when visble accumulated histogram method was applied. And the sea fog region which detected is of similarity in composite image and surface albedo method. In case of nighttime sea fog(18UTC, May 10, 1999), infrared accumulated histogram method and maximum brightness temperature method are used, respectively. Maximum brightness temperature method(T_max method) detected sea fog better than IR accumulated histogram method. In case of T_max method, when infrared value is larger than T_max, fog is detected, where T_max is an unique value, maximum infrared value in each pixel during one month. Then T_max is beneath 700hpa temperature of GDAPS(Global Data Assimilation and Prediction System). Sea fog region which detected by T_max method was similar to the result of National Oceanic and Atmosheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) DCD(Dual Channel Difference). But inland visibility and relative humidity didn't always agreed well.

• 한국항공운항학회지
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• 제14권4호
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• pp.94-100
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• 2006

The purpose of this case study is to determine the possibility of Numerical Forecasting of sea fog at West Sea in spring time. For practical method of analyzing the data collected from 24th to 26th March 2003, Numerical Weather Prediction model MM5(Mesoscale Model Version 5) and synoptic field study using synoptic chart, upper level chart, and sea surface temperature were employed. The results of synoptic field analysis summarized that sea fog at West sea in spring is intensified by the inflow of the warm flow from west or southwest, low sea surface temperature to increase the temperature difference between air and sea surface, and inversion layer to disturb the disperse. It appears that the possibility of sea fog forecasting by MM5, in view of the result that the MM5 output is similar to the synoptic fields analysis.

• 한국해양학회지:바다
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• 제8권2호
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• pp.121-131
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• 2003

동해안에서 지난 20년 동안 발생한 월별 안개 발생빈도와 지속시간 분석에 의하면 1월, 2월, 11월, 12월의 안개 발생빈도는 거의 전무함을 알 수 있다. 이 현상은 태백산맥으로부터 동쪽으로 경사를 이루어 복사 안개의 발생이 어려운 지형 특징을 가지고 있기 때문으로 사료된다. 반면에 안개발생빈도의 90%이상을 차지하는 봄, 여름철의 안개 발생 원인은 크게 3가지로 분류된다. 첫 번째는 증기해무로서 오호츠크해 고기압의 확장으로 찬 북동기류가 동해상으로 이류하여 발생한다. 두 번째는 이류해무로서 따뜻한 기단이 상대적으로 찬 해수면 위로 이류하여 냉각, 포화되어 발생한다. 세 번째는 전선해무로써 저기압이 동해상으로 이동하여 수증기가 공급된 상태에서 한랭 전선 후면의 찬공기가 이류하면서 발생한다 한편, 해상풍, 상대습도, 운저고도, 시정 등의 예측과 동해 해역의 수직단면에서 안개 예측이 가능한 해무예측시스템(DUT-METRI)을 구축하여 사례기간의 해무를 모사하였, 위성자료로부터 이를 검증하였다.

• 대한원격탐사학회지
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• 제24권6호
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• pp.571-581
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• 2008

한반도의 서해에서 해무는 봄과 여름에 자주 발생한다. 본 연구의 목적은 MODIS 위성 영상을 사용하여 해무를 탐지하는 데 있다 하층운의 운정 표면은 불균질한 반면에 해무의 표면은 균질한 특징이 있으므로, 하층운과 해무의 균질성을 이용한 해무 탐지 방법이 제시되었다. 11 um의 밝기온도(BT), 3.7um와 11um의 밝기온도차(BTD)는 하층운으로부터 해무를 구별하는데 유용하였다. 안개/하층운 지역의 밝기 온도와 맑은 지역에서의 밝기 온도의 차이를 이용한 방법과 안개/하층운 지역에서 밝기 온도와 밝기온도차의 표준편차 임계값을 이용한 방법은 안개와 하층운을 구별하는데 적용될 수 있었다.

• 한국항공운항학회지
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• 제25권1호
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• pp.1-10
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• 2017

A heavy foggy event accompanying with complex coastal fog was investigated in this study. This heavy foggy event occurred on FEB 11, 2015. Due to reduced visibility with this foggy event induced more than 100times serial traffic accidents over the Young-jong highway, and Flights from 04:30 AM to 10:00 AM were cancelled on Inchon International Airport. This heavy foggy event was occurred in synoptic and mesoscale environments but dense coastal fog were combined with a combination of sea fog, steam fog, and radiation fog. This kind of coastal fog can predicted by accurate analysis of the direction of the air flow, sea surface temperature(SST), and 925hPa isotherms from numerical weather prediction charts and real time analysis charts.

• 한국환경과학회지
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• 제29권3호
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• pp.257-272
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• 2020

This study investigates the temporal and spatial variations of marine meterological elements (air temperature (Temp), Sea Surface Temperature (SST), and Significant Wave Height (SWH)) in seven coastal waters of South Korea, using hourly data observed at marine meteorological buoys (10 sites), Automatic Weather System on lighthouse (lighthouse AWS) (9 sites), and AWS (20 sites) during 2013-2017. We also compared the characteristics of Temp, SST, and air-sea temperature difference (Temp-SST) between sea fog and non-sea-fog events. In general, annual mean values of Temp and SST in most of the coastal waters were highest (especially in the southern part of Jeju Island) in 2016, due to heat waves, and lowest (especially in the middle of the West Sea) in 2013 or 2014. The SWH did not vary significantly by year. Wind patterns varied according to coastal waters, but their yearly variations for each coastal water were similar. The maximum monthly/seasonal mean values of Temp and SST occurred in summer (especially in August), and the minimum values in winter (January for Temp and February for SST). Monthly/seasonal mean SWH was highest in winter (especially in December) and lowest in summer (June), while the monthly/seasonal variations in wind speed over most of the coastal waters (except for the southern part of Jeju Island) were similar to those of SWH. In addition, sea fog during spring and summer was likely to be in the form of advection fog, possibly because of the high Temp and low SST (especially clear SST cooling in the eastern part of South Sea in summer), while autumn sea fog varied between different coastal waters (either advection fog or steam fog). The SST (and Temp-SST) during sea fog events in all coastal waters was lower (and more variable) than during non-sea-fog events, and was up to -5.7℃ for SST (up to 5.8℃ for Temp-SST).