• Title/Summary/Keyword: GHRSST Level 4

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Pattern Analysis of Sea Surface Temperature Distribution in the Southeast Sea of Korea Using a Weighted Mean Center (가중공간중심을 활용한 한국 남동해역의 표층수온 분포 패턴 분석)

  • KIM, Bum-Kyu;YOON, Hong-Joo;KIM, Tae-Hoon;CHOI, Hyun-Woo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.3
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    • pp.263-274
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    • 2020
  • In the Southeast Sea of Korea, a cold water mass is formed intensively in summer every year, causing frequent abnormal sea conditions. In order to analyze the spatial changes of sea surface temperature distribution in this area, ocean fields buoy data observed at Gori and Jeongja and reanalyzed sea surface temperature(SST) data from GHRSST Level 4 were used from June to September 2018. The buoy data were used to analyze the time-series water temperature changes at two stations, and the GHRSST data were used to calculate the daily SST variance and weighted mean center(WMC) across the study area. When the buoy's water temperature was lowered, the variance of SST in the study area trend to increase, but it did not appear consistently for the entire period. This is because GHRSST is a reanalysis data that does not reflect sensitive changes in water temperature along the coast. As such, there is a limit to grasping the local small-scale water temperature change in the coast or detecting the location and extent of the cold water zone only by the statistical variance representing the SST change in the entire sea area. Therefore, as a result of using WMC to quantitatively determine the spatial location of the cold water mass, when the cold water zone occurred, WMC was located in the northwest sea area from the mean center(MC) of the study area. This means that it is possible to quantitatively identify where and to what extent the distribution of cold surface water temperature appears through SST's WMC location information, and we could see the possibility of WMC's use in detecting the scale of cold water zones and the extent of regional spread in the future.

Study on the Correlation Between the Upwelling Cold Waters and Cochlodinium polykrikoides Red Tide in the Southeast Sea of Korea (한국 남동해역의 냉수대 발생 변화와 Cochlodinium polykrikoides 적조와의 상관성 연구)

  • Kim, Bum-Kyu;Hwang, Do-Hyun;Bak, Su-Ho;Kim, Heung-Min;Unuzaya, Enkhjargal;Kim, Dae-Hyun;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.3
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    • pp.559-572
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    • 2019
  • In the southeast sea of Korea, the cold water is concentrated in every summer, showing in abnormal oceanic conditions. Cold water occurred in the southeast sea is dominantly influenced by wind, which occurs when the south wind is continuously blowing for 3 to 7 days more. In this study, water temperature, wind speed and direction data of KMA, KHOA and KHNP, Chlorophyll-a of COMS/GOCI, GHRSST Level 4 SST of NASA, and red tide alert data of the National Institute of Fisheries Science were used to analyze the correlation between occurrence and change of the cold water and the red tide of Cochlodinium polykrikoides. The upwelling cold water mass showed a characteristic of moving northward along the current and occurrence a high concentration of chlorophyll along the water mass. Also, when the warm current were strong, the characteristic of red tide showed a northward moving.

A Study on the Distribution of Cold Water Occurrence using K-Means Clustering (K-Means Clustering을 활용한 냉수대 발생 분포에 관한 연구)

  • Kim, Bum-Kyu;Yoon, Hong-Joo;Lee, Jun Ho
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.2
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    • pp.371-378
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    • 2021
  • In this study, in order to analyze the spatial distribution of cold water occurred in the Southeast Sea of Korea, the K-means clustering method was used to analyze the ocean observatory buoy of Gori and Yangpo and GHTSST Level 4 from 2016 to 2018. The buoy data was used to identify the change in sea water temperature and the cold water occurrence at Gori and Yangpo in the Southeast Sea. As a result, the sea water temperature of Gori and Yangpo decreased equally at the cold water occurrence. Therefore, the reciprocal of the sea water temperature and the variance of SST were compared to see the changes of SST when the cold water occurs. When the reciprocal of the sea water temperature increases, the dispersion of SST also increases. Through this, it can be seen that there is a change in the water temperature distribution of SST in the sea when the cold water occurs. After that, K-means clustering was used to classify the cold water. After analyzing the optimal K value for clustering by using the Elbow method, it was possible to classify a region with cold water. Through this, it is estimated that the spatial distribution and diffusion range of the cold water, and it can be estimated and used in future studies to identify damage caused by the cold water and predict spatial spread.