• 제목/요약/키워드: Satellite SST

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Recent Trends of Abnormal Sea Surface Temperature Occurrence Analyzed from Buoy and Satellite Data in Waters around Korean Peninsula

  • Choi, Won-Jun;Yang, Chan-Su
    • 대한원격탐사학회지
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    • 제38권4호
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    • pp.355-364
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    • 2022
  • In this study a tendency of abnormal sea surface temperature (SST) occurrence in the seas around South Korea is analyzed from daily SST data from satellite and 14 buoys from August 2020 to July 2021. As thresholds 28℃ and 4℃ are used to determine marine heatwaves(MHWs) and abnormal low water temperature (ALWT), respectively, because those values are adopted by the National Institute of Fisheries Science for the breaking news of abnormal temperature. In order to calculate frequency of abnormal SST occurrence spatially by using satellite SST, research area was divided into six areas of coast and three open seas. ALWT dominantly appeared over a wide area (7,745 km2) in Gyeonggi Bay for total 94 days and it was also confirmed from buoy temperature showing an occurrence number of 47 days. MHWs tended to be high in frequency in the coastal areas of Chungcheongdo and Jeollabukdo and the south coastal areas while in case of buoy temperature Jupo was the place of high frequency (32 days). This difference was supposed to be due to the low accuracy of satellite SST at the coasts. MHWs are also dominant in offshore waters around Korean Peninsula. Although detecting abnormal SST by using satellite SST has advantage of understanding occurrence from a spatial point of view, we also need to perform detection using buoys to increase detection accuracy along the coast.

초기 입력 자료의 개선에 의한 RAMS 기상장의 예측 I - NOAA SST자료의 적용 - (A RAMS Atmospheric Field I Predicted by an Improved Initial Input Dataset - An Application of NOAA SST data -)

  • 원경미;정기호;이화운;정우식;이강열
    • 한국환경과학회지
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    • 제18권5호
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    • pp.489-499
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    • 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.

온배수 확산 평가를 위한 열적외선 위성관측 비교 (The Comparison of Thermal Infrared Satellite Observation for Plume Assessment of Thermal Discharge)

  • 정종철
    • 환경영향평가
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    • 제24권4호
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    • pp.367-374
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    • 2015
  • 해수 표층 수온은 원자력발전소의 온배수 영향을 조사하기 위해서 위성원격탐사에 의해 관측되는 가장 중요한 정보들 중 하나이다. 하지만 Landsat 7 위성과 Landsat 8 위성의 열적외선 센서로부터 추출한 표층수온과 실측치를 비교한 연구는 부족하다. Landsat 8 위성은 표층수온을 추출하기 위해 열적외선 센서에 두 개의 분리된 밴드를 가지고 있지만, Landsat 7은 한 개의 밴드를 사용하고 있다. 그럼에도 불구하고 본 연구에서는 Landsat 7 ETM+센서가 Landsat 8 TIRS 보다 표층수온의 보정에 유용하다는 것을 제시하였다. 본 연구에서는 Landsat 114-36 지역의 15개 위성자료를 가지고 ENVI와 IDL을 이용한 표층수온 알고리즘을 처리하였다. 국립해양조사원으로부터 수집한 표층수온 실측자료와 위성에서 추출한 표층수온을 비교하였고, 위성관측 시계열 자료와 측정지점의 실측자료를 통해 정확도를 비교하였다.

Prediction of SST for Operational Ocean Prediction System

  • Kang, Yong-Quin
    • Ocean and Polar Research
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    • 제23권2호
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    • pp.189-194
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    • 2001
  • A practical algorithm for prediction of the sea surface temperatures (SST)from the satellite remote sensing data is presented in this paper. The fluctuations of SST consist of deterministic normals and stochastic anomalies. Due to large thermal inertia of sea water, the SST anomalies can be modelled by autoregressive or Markov process, and its near future values can be predicted provided the recent values of SST are available. The actual SST is predicted by superposing the pre-known SST normals and the predicted SST anomalies. We applied this prediction algorithm to the NOAA AVHRR weekly SST data for 18 years (1981-1998) in the seas adjacent to Korea (115-$145^{\circ}E$, 20-$55^{\circ}N$). The algorithm is applicable not only for prediction of SST in near future but also for nowcast of SST in the cloud covered regions.

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Estimation of the air temperature over the sea using the satellite data

  • Kwon B. H.;Hong G. M.;Kim Y. S.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.392-393
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    • 2005
  • Due to the temporal and spatial simultaneity and the high-frequency repetition, the data set retrieved from the satellite observation is considered to be the most desirable ones for the study of air-sea interaction. With rapidly developing sensor technology, satellite-retrieved data has experienced improvement in the accuracy and the number of parameters. Nevertheless, since it is still impossible to directly measure the heat fluxes between air and sea, the bulk method is an exclusive way for the evaluation of the heat fluxes at the sea surface. It was noted that the large deviation of air temperature in the winter season by the linear regression despite good correlation coefficients. We propose a new algorithm based on the Fourier series with which the SST and the air temperature. We found that the mean of air temperature is a function of the mean of SST with the monthly gradient of SST inferred from the latitudinal variation of SST and the spectral energy of air temperature is related linearly to that of SST. An algorithm to obtain the air temperature over the sea was completed with a proper analysis on the relation between of air temperature and of SST. This algorithm was examined by buoy data and therefore the air temperature over the sea can be retrieved based on just satellite data.

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Validation of Sea Surface Temperature (SST) from Satellite Passive Microwave Sensor (GPM/GMI) and Causes of SST Errors in the Northwest Pacific

  • Kim, Hee-Young;Park, Kyung-Ae;Chung, Sung-Rae;Baek, Seon-Kyun;Lee, Byung-Il;Shin, In-Chul;Chung, Chu-Yong;Kim, Jae-Gwan;Jung, Won-Chan
    • 대한원격탐사학회지
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    • 제34권1호
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    • pp.1-15
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    • 2018
  • Passive microwave sea surface temperatures (SST) were validated in the Northwest Pacific using a total of 102,294 collocated matchup data between Global Precipitation Measurement (GPM) / GPM Microwave Sensor(GMI) data and oceanic in-situ temperature measurements from March 2014 to December 2016. A root-mean-square (RMS) error and a bias error of the GMI SST measurements were evaluated to $0.93^{\circ}C$ and $0.05^{\circ}C$, respectively. The SST differences between GMI and in-situ measurements were caused by various factors such as wind speed, columnar atmospheric water vapor, land contamination near coastline or islands. The GMI SSTs were found to be higher than the in-situ temperature measurements at low wind speed (<6 m/s) during the daytime. As the wind speed increased at night, SST errors showed positive bias. In addition, other factors, coming from atmospheric water vapor, sensitivity degradation at a low temperature range, and land contamination, also contributed to the errors. One of remarkable characteristics of the errors was their latitudinal dependence with large errors at high latitudes above $30^{\circ}N$. Seasonal characteristics revealed that the errors were most frequently observed in winter with a significant positive deviation. This implies that SST errors tend to be large under conditions of high wind speeds and low SSTs. Understanding of microwave SST errors in this study is anticipated to compensate less temporal capability of Infrared SSTs and to contribute to increase a satellite observation rate with time, especially in SST composite process.

한반도 연안 위성합성 및 수치모델 재분석 해수면온도 자료의 정확도 (The Accuracy of Satellite-composite GHRSST and Model-reanalysis Sea Surface Temperature Data at the Seas Adjacent to the Korean Peninsula)

  • 백유현;문일주
    • Ocean and Polar Research
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    • 제41권4호
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    • pp.213-232
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    • 2019
  • This study evaluates the accuracy of four satellite-composite (OSTIA, AVHRR, G1SST, FNMONC-S) and three model-reanalysis (HYCOM, JCOPE2, FNMOC-M) daily sea surface temperature (SST) data around the Korean Peninsula (KP) using ocean buoy data from 2011-2016. The results reveal that OSTIA has the lowest root mean square error (RMSE; 0.68℃) and FNMOC-S/M has the highest correction coefficients (r = 0.993) compared with observations, while G1SST, JCOPE2, and AVHRR have relatively larger RMSEs and smaller correlations. The large RMSEs were found in the western coastal regions of the KP where water depth is shallow and tides are strong, such as Chilbaldo and Deokjeokdo, while low RMSEs were found in the East Sea and open oceans where water depth is relatively deep such as Donghae, Ulleungdo, and Marado. We found that the main sources of the large RMSEs, sometimes reaching up to 5℃, in SST data around the KP, can be attributed to rapid SST changes during events of strong tidal mixing, upwelling, and typhoon-induced mixing. The errors in the background SST fields which are used in data assimilations and satellite composites and the missing in-situ observations are also potential sources of large SST errors. These results suggest that both satellite and reanalysis SST data, which are believed to be true observation-based data, sometimes, can have significant inherent errors in specific regions around the KP and thus the use of such SST products should proceed with caution particularly when the aforementioned events occur.

Sensitivity analysis of satellite-retrieved SST using IR data from COMS/MI

  • Park, Eun-Bin;Han, Kyung-Soo;Ryu, Jae-Hyun;Lee, Chang-Suk
    • 대한원격탐사학회지
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    • 제29권6호
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    • pp.589-593
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    • 2013
  • Sea Surface Temperature (SST) is the temperature close to the ocean's surface and affects the Earth's atmosphere as an important parameter for the climate circulation and change. The SST from satellite still has biases from the error in specifying retrieval coefficients from either forward modeling or instrumental biases. So in this paper, we performed sensitivity analysis using input parameter of the SST to notice that the SST is most affected among the input parameter. We used Infrared (IR) data from the Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager (MI) from April 2011 to March 2012. We also used the Global Space-based Inter-Calibration System (GSICS) correction to quality of the IR data from COMS. SST was calculated by substituting the input parameters; IR data with or without the GSICS correction. The results of this sensitivity analysis, the SST was sensitive from -0.0403 to 0.2743 K when the IR data were changed by the GSICS corrections.

다종 위성 자료를 활용한 해수면온도(SST) 합성기법 개발 연구 (Study on Merging Method of SSTs Using Multi-satellite Data)

  • 오은경;양찬수
    • 해양환경안전학회지
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    • 제17권3호
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    • pp.197-202
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    • 2011
  • 본 연구는 다종 위성 자료를 활용한 해수면온도 합성 기법에 대한 연구이다. 현재 많은 연구자들이 사용하고 있는 NGSST 알고리듬은 위성에 따른 정확도를 고려하지 않고 시 공간 상관도만을 계산하여 해당 픽셀의 값을 추정한다. 본 연구에서는 위성 센서별로 가지고 있는 정확도를 추가로 고려한 해수면온도 합성기법을 제안하고 기존 알고리듬과의 비교를 수행하였다. 합성장을 산출하는데 사용된 센서는 적외 센서인 MODIS, AVHRR 그리고 마이크로파 센서인 AMSR-E를 사용하였고, 2011년 4월 4일을 기준으로 5 km의 공간해상도를 갖는 일일 해수면 온도 합성장을 비교하였다. 부이와의 비교 결과, 기존 방법(NGSST Method)과 제안 방법(New Method)에 의한 표준편차는 각각 $0.15^{\circ}C$$0.12^{\circ}C$이었다. 또한 기존 방법보다 제안 방법에 의한 해수면온도 값은 연안을 제외한 대부분의 해역에서 다소 높게 산출이 되었다. 현 단계에서 정량적인 평가는 어렵지만, 본 연구를 통하여 해수면온도 합성기법에 대한 연구 방향이 제시되었다고 판단된다.

SEASONAL VARIATION OF THE OCEANIC WATER INTRUSIONS INTO KAGOSHIMA BAY DERIVED FROM THE SATELLITE SST AND CHL-A IMAGES

  • Hosotani, Kazunori
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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    • pp.61-64
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    • 2008
  • Seasonal distribution of the oceanic water intrusion was investigated using satellite SST (sea surface temperature) and chl-a (chlorophyll-a) images taken by the MODIS Aqua sensor. The warm water mass emanating periodically from the meandering Kuroshio Current brings the oceanic water intrusion, known as the 'Kyucho' phenomenon, into Kagoshima bay during the winter. Satellite SST images and buoy robot data show that this warm water intrusion has the characteristics of a semigeostrophic gravity current influenced by the Coriolis effect. However, it is difficult to find the oceanic water intrusion during the summer season considering that it is accompanied by thermal stratification, and SST shows almost the same temperature between the inner side of the bay and the ocean. In this research, the satellite chl-a images taken by MODIS Aqua were employed instead of SST images to reveal the oceanic water intrusion in each season. The enclosed bay has the tendency to undergo eutrophication caused by organic materials from land and differences in chl-a concentration of the bay water and the oceanic water. As a result, distribution of low concentration chl-a with oceanic water intrusion in summer season shows almost the same pattern in winter season. On the other hand, in spring season, both SST and chl-a images are available to differentiate the oceanic water intrusion. Therefore, applying the suitable satellite sensor images for each season is effective in the monitoring of oceanic water intrusion. Moreover, in this area, SST and chl-a distribution reveal not only the oceanic water intrusion into Kagoshima bay but also the intrusion at Fukiage seashore facing East China Sea.

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