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Validation of Satellite SMAP Sea Surface Salinity using Ieodo Ocean Research Station Data

이어도 해양과학기지 자료를 활용한 SMAP 인공위성 염분 검증

  • Park, Jae-Jin (Department of Science Education, Seoul National University) ;
  • Park, Kyung-Ae (Department of Earth Science Education/Research Institute of Oceanography, Seoul National University) ;
  • Kim, Hee-Young (Department of Science Education, Seoul National University) ;
  • Lee, Eunil (Ocean Research Division, Korea Hydrographic and Oceanographic Agency) ;
  • Byun, Do-Seong (Ocean Research Division, Korea Hydrographic and Oceanographic Agency) ;
  • Jeong, Kwang-Yeong (Ocean Research Division, Korea Hydrographic and Oceanographic Agency)
  • 박재진 (서울대학교 과학교육과) ;
  • 박경애 (서울대학교 지구과학교육과/해양연구소) ;
  • 김희영 (서울대학교 과학교육과) ;
  • 이은일 (국립해양조사원 해양과학조사연구실) ;
  • 변도성 (국립해양조사원 해양과학조사연구실) ;
  • 정광영 (국립해양조사원 해양과학조사연구실)
  • Received : 2020.10.13
  • Accepted : 2020.10.19
  • Published : 2020.10.31

Abstract

Salinity is not only an important variable that determines the density of the ocean but also one of the main parameters representing the global water cycle. Ocean salinity observations have been mainly conducted using ships, Argo floats, and buoys. Since the first satellite salinity was launched in 2009, it is also possible to observe sea surface salinity in the global ocean using satellite salinity data. However, the satellite salinity data contain various errors, it is necessary to validate its accuracy before applying it as research data. In this study, the salinity accuracy between the Soil Moisture Active Passive (SMAP) satellite salinity data and the in-situ salinity data provided by the Ieodo ocean research station was evaluated, and the error characteristics were analyzed from April 2015 to August 2020. As a result, a total of 314 match-up points were produced, and the root mean square error (RMSE) and mean bias of salinity were 1.79 and 0.91 psu, respectively. Overall, the satellite salinity was overestimated compare to the in-situ salinity. Satellite salinity is dependent on various marine environmental factors such as season, sea surface temperature (SST), and wind speed. In summer, the difference between the satellite salinity and the in-situ salinity was less than 0.18 psu. This means that the accuracy of satellite salinity increases at high SST rather than at low SST. This accuracy was affected by the sensitivity of the sensor. Likewise, the error was reduced at wind speeds greater than 5 m s-1. This study suggests that satellite-derived salinity data should be used in coastal areas for limited use by checking if they are suitable for specific research purposes.

염분은 해양의 밀도를 결정하는 중요한 변수이자 전지구 물의 순환을 나타내는 주요 인자 중 하나이다. 해상염분 관측은 선박을 이용한 현장조사, Argo 플로트, 부이를 통한 조사가 주로 수행되어 왔다. 2009년 염분관측 인공위성이 발사한 이래로, 위성 염분자료를 이용하여 전 지구 해역에서 표층 염분 관측이 가능해졌다. 그러나 위성 염분자료는 다양한 오차를 포함하기 때문에 연구 자료로 활용하기에 앞서 정확도 검증과정이 필요하다. 따라서 본 연구에서는 2015년 4월부터 2020년 8월까지 Soil Moisture Active Passive (SMAP) 위성 염분자료와 이어도 해양과학기지에서 제공하는 실측 염분자료 간의 정확도 및 오차특성을 비교 분석하였다. 총 314개의 일치점을 생산하였으며, 염분의 평균제 곱근오차 및 평균편차는 각각 1.79, 0.91 psu로 제시되었다. 전반적으로 위성 염분이 실측 염분보다 과대추정 되는 것으로 나타났다. 위성 염분의 오차는 계절, 표층 수온, 풍속과 같은 다양한 해양 환경적 요인에 의존성을 보였다. 여름철 위성 염분과 실측 염분의 차이는 0.18 psu 이하로 저수온보다는 고수온에서 위성 염분의 정확도가 증가하였다. 이는 센서의 민감도에 따른 결과였다. 마찬가지로 5m s-1 이상 풍속 조건에서 오차가 줄어들었다. 본 연구결과는 연안에서 위성 염분자료를 활용할 경우에는 특정한 연구 목적에 적합한지 확인하여 제한적으로 사용하여야 함을 제시한다.

Keywords

References

  1. Abe, H., and Ebuchi, N., 2014, Evaluation of seasurface salinity observed by Aquarius. Journal of Geophysical Research: Oceans, 119(11), 8109-8121. https://doi.org/10.1002/2014jc010094
  2. Bao, S., Wang, H., Zhang, R., Yan, H., and Chen, J., 2019, Comparison of satellitederived sea surface salinity products from SMOS, Aquarius, and SMAP. Journal of Geophysical Research: Oceans, 124(3), 1932-1944. https://doi.org/10.1029/2019jc014937
  3. Barré, H. M., Duesmann, B., and Kerr, Y. H., 2008, SMOS: The mission and the system. IEEE Transactions on Geoscience and Remote Sensing, 46(3), 587-593. https://doi.org/10.1109/TGRS.2008.916264
  4. Beardsley, R. C., Limeburner, R., Yu, H., and Cannon, G. A., 1985, Discharge of the Changjiang (Yangtze river) into the East China Sea. Continental Shelf Research, 4(1-2), 57-76. https://doi.org/10.1016/0278-4343(85)90022-6
  5. Chang, P. H. and Isobe, A., 2003, A numerical study on the Changjiang diluted water in the Yellow and East China seas. Journal of Geophysical Research: Oceans, 108(C9) 3229. https://doi.org/10.1029/2000JC000712
  6. Choi, D. Y., Woo, H. J., Park, K., Byun, D. S., and Lee, E., 2018, Validation of sea surface wind speeds from satellite altimeters and relation to sea state bias-focus on wind measurements at Ieodo, Marado, Oeyeondo Stations. Journal of the Korean Earth Science Society, 39(2), 139-153. https://doi.org/10.5467/JKESS.2018.39.2.139
  7. Delcroix, T., and Murtugudde, R., 2002, Sea surface salinity changes in the East China Sea during 1997-2001: Influence of the Yangtze River. Journal of Geophysical Research: Oceans, 107(C12), SRF-9.
  8. Drucker, R., and Riser, S. C., 2014, Validation of Aquarius sea surface salinity with argo: Analysis of error due to depth of measurement and vertical salinity stratification. Journal of Geophysical Research: Oceans, 119(7), 4626-4637. https://doi.org/10.1002/2014jc010045
  9. Fournier, S., Lee, T., Tang, W., Steele, M., and Olmedo, E., 2019, Evaluation and intercomparison of SMOS, Aquarius, and SMAP sea surface salinity products in the Arctic Ocean. Remote Sensing, 11(24), 3043. https://doi.org/10.3390/rs11243043
  10. Grodsky, S. A., Reul, N., Bentamy, A., Vandemark, D., and Guimbard, S., 2019, Eastern Mediterranean salinification observed in satellite salinity from SMAP mission. Journal of Marine Systems, 198, 103190. https://doi.org/10.1016/j.jmarsys.2019.103190
  11. Helm, K. P., Bindoff, N. L., and Church, J. A., 2010, Changes in the global hydrologicalcycle inferred from ocean salinity. Geophysical Research Letters, 37(18), L18701. https://doi.org/10.1029/2010GL044222
  12. Hwang, K., and Jung, S., 2012, Decadal changes in fish assemblages in waters near the Ieodo ocean research station (East China Sea) in relation to climate change from 1984 to 2010. Ocean Science Journal, 47(2), 83-94. https://doi.org/10.1007/s12601-012-0009-3
  13. Kim, K., Rho, H. K., and Lee, S. H., 1991, Water masses and circulation around Cheju-do in summer. Journal of the Oceanological Society of Korea, 26, 262-277.
  14. Kim, S. B., Lee, J. H., de Matthaeis, P., Yueh, S., Hong, C. S., Lee, J. H., and Lagerloef, G., 2014, Sea surface salinity variability in the East China Sea observed by the Aquarius instrument. Journal of Geophysical Research: Oceans, 119(10), 7016-7028. https://doi.org/10.1002/2014jc009983
  15. Kim, S. S., Go, W. J., Jo, Y. J., Lee, P. Y., and Jeon, K. A., 1998, Low salinity anomaly and nutrient distribution at surface waters of the South Sea of Korea during 1996 summer. Journal of the Korean Society of Oceanography, 3, 165-169.
  16. Lagerloef, G., Colomb, F. R., Le Vine, D., Wentz, F., Yueh, S., Ruf, C., and Feldman, G., 2008, The Aquarius/SAC-D mission: Designed to meet the salinity remote-sensing challenge. Oceanography, 21(1), 68-81. https://doi.org/10.5670/oceanog.2008.68
  17. Lie, H.-J., Cho, C.-H., Lee, J.-H., and Lee, S., 2003, Structure and eastward extension of the Changjiang River plume in the East China Sea. Journal of Geophysical Research, 108(C3), 3077. https://doi.org/10.1029/2001JC001194
  18. Lie, H.-J., 1986, Summertime hydrographic features in the south eastern Hwanghae. Progress in Oceanography, 17, 229-242. https://doi.org/10.1016/0079-6611(86)90046-7
  19. Moon, I. J., Shim, J. S., Lee, D. Y., Lee, J. H., Min, I. K., and Lim, K. C., 2010, Typhoon researches using the Ieodo Ocean Research Station: Part I. Importance and present status of typhoon observation. Atmosphere, 20(3), 247-260.
  20. O'Carroll, A. G., Eyre, J. R., and Saunders, R. W., 2008, Three-way error analysis between AATSR, AMSR-E, and in situ sea surface temperature observations. Journal of Atmospheric and Oceanic Technology, 25(7), 1197-1207. https://doi.org/10.1175/2007JTECHO542.1
  21. Oh, H. M., and Ha, K. J., 2005, Analysis of marine meteorological characteristics at Ieodo ocean research station from 2003 to 2004. Atmosphere, 41(5), 671-680.
  22. Reul, N., Fournier, S., Boutin, J., Hernandez, O., Maes, C., Chapron, B., and Kerr, Y., 2014, Sea surface salinity observations from space with the SMOS satellite: A new means to monitor the marine branch of the water cycle. Surveys in Geophysics, 35(3), 681-722. https://doi.org/10.1007/s10712-013-9244-0
  23. Tang, W., Fore, A., Yueh, S., Lee, T., Hayashi, A., Sanchez-Franks, A., and Baranowski, D., 2017, Validating SMAP SSS with in situ measurements. Remote Sensing of Environment, 200, 326-340. https://doi.org/10.1016/j.rse.2017.08.021
  24. Wang W., 1988, Yangtze brackish water plume-circulation and diffusion. Progress in Oceanography, 21, 373-385. https://doi.org/10.1016/0079-6611(88)90015-8
  25. Woo, H. J., Park, K. A., Byun, D. S., Lee, J., and Lee, E., 2018, Characteristics of the differences between significant wave height at Ieodo Ocean Research Station and satellite altimeter-measured data over a decade (2004-2016). The Sea, 23(1), 1-19. https://doi.org/10.7850/jkso.2018.23.1.001
  26. Woo, H. J., Park, K. A., Choi, D. Y., Byun, D. S., Jeong, K. Y., and Lee, E. I., 2019, Comparison of multi-satellite sea surface temperatures and in-situ temperatures from Ieodo Ocean Research Station. Journal of the Korean Earth Science Society, 40(6), 613-623. https://doi.org/10.5467/JKESS.2019.40.6.613