• Korean Journal of Remote Sensing
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• v.32 no.4
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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.

• Atmosphere
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• v.22 no.2
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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.

• Atmosphere
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• v.32 no.4
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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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.23-26
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• 2023

In the past, in observing the sea fog on the major sea route and providing real-time information for the safe operation of ships, a visibility sensor or a fog detector with similar operating principles was installed to observe local fog near the place where it was installed. However, it was somewhat unreasonable to immediately provide sea fog observation information to ships and users because the reliability of real-time observation information was somewhat low due to pollution caused by dust, salt, and pollen, or malfunctions of detection sensors by organisms such as spider webs. From 2019 to 2022, the Korea Meteorological Administration and the Ministry of Oceans and Fisheries collaborated to build a more reliable real-time image-based sea fog observation system in 100 regions of the Lighthouse on major sea routes across the country to collect reliable sea fog observation information every 10 minutes and perform real-time public service(webpage).

• Proceedings of the KSRS Conference
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• 1999.11a
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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.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.14 no.4
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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.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.8 no.2
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• pp.121-131
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• 2003

We have found that the east coast of Korea has had few sea fogs on January, February, November and December for the past 20 years by the analysis of monthly fog frequency and duration time. These phenomena appear to relate to the topographical characteristics of which the Taebaek Mountains descends toward the east to bar the radiation fog. On the other hand, the cause of occurring the spring and summer fog which has 90% of the whole frequency is divided into three cases. The first is the steam fog caused by the advection of the northeast cold air current on the East Sea due to the extension of Okhotsk High. The second is the advection fog caused by cooling and saturation of warm airmass advected on cold sea surface. And the last is the frontal fog caused by the supply of enough vapor due to the movement of low-pressure system and the advection of cold air behind a cold front. While, we simulate the sea fog for the period of the case studies by implementing fog prediction system(DUT-METRI) that makes it possible to forecast the fog in the vertical section of neighborhood of the East Sea and to predict the sea surface wind, relative humidity, ceiling height, visibility etc. Finally we verified this result by satellite image.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.571-581
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• 2008

The sea fog occurs frequently in the west coast of Korea in spring and summer. This study focused on the detection of sea fog using MODIS satellite images. We presented a method for sea fog detection based on the homogeneity level between low stratus and sea fog, which was that the top surface of sea fog had a homogeneous aspect while that of low stratus had a heterogenous aspect. The results showed that the both homogeneity of $11{\mu}m$ brightness temperature (BT) and brightness temperature difference (BTD, $BT_{3.7{\mu}m}-BT_{11{\mu}m}$) were available to discriminate sea fog from low stratus. The frequency of difference between BT in fog/stratus area and BT in clear area provided reasonable result. In addition, the threshold values of standard deviations of BT and BTD in the fog/stratus area were applicable to differentiate fog from low stratus.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.1
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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.

• Journal of Environmental Science International
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• v.29 no.3
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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).