Acta Oceanologica Sinica

, Volume 35, Issue 3, pp 54–62 | Cite as

Assessment and adjustment of sea surface salinity products from Aquarius in the southeast Indian Ocean based on in situ measurement and MyOcean modeled data

  • Shenzhen Xia
  • Changqing Ke
  • Xiaobing Zhou
  • Jie Zhang
Article
  • 39 Downloads

Abstract

The in situ sea surface salinity (SSS) measurements from a scientific cruise to the western zone of the southeast Indian Ocean covering 30°–60°S, 80°–120°E are used to assess the SSS retrieved from Aquarius (Aquarius SSS). Wind speed and sea surface temperature (SST) affect the SSS estimates based on passive microwave radiation within the mid- to low-latitude southeast Indian Ocean. The relationships among the in situ, Aquarius SSS and wind-SST corrections are used to adjust the Aquarius SSS. The adjusted Aquarius SSS are compared with the SSS data from MyOcean model. Results show that: (1) Before adjustment: compared with MyOcean SSS, the Aquarius SSS in most of the sea areas is higher; but lower in the low-temperature sea areas located at the south of 55°S and west of 98°E. The Aquarius SSS is generally higher by 0.42 on average for the southeast Indian Ocean. (2) After adjustment: the adjustment greatly counteracts the impact of high wind speeds and improves the overall accuracy of the retrieved salinity (the mean absolute error of the Zonal mean is improved by 0.06, and the mean error is - 0.05 compared with MyOcean SSS). Near the latitude 42°S, the adjusted SSS is well consistent with the MyOcean and the difference is approximately 0.004.

Keywords

Aquarius sea surface salinity (SSS) in situ SSS MyOcean comparison analysis southeast Indian Ocean 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bahurel P, Adragna F, Bell M J, et al. 2010. Ocean Monitoring and Forecasting Core Services: The European MyOcean Example. In: Hall J, Harrison D E, Stammer, D, Eds. Proceedings of OCEANOBS’09 Sustained Ocean Observations and Information for Society. Venice, Italy: ESA Publication WPP-306, 2–11Google Scholar
  2. Banks C J, Gommenginger C P, Srokosz M A, et al. 2012. Validating SMOS ocean surface salinity in the Atlantic with Argo and operational ocean model data. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1688–1702CrossRefGoogle Scholar
  3. Boutin J, Martin N, Yin Xiaobin, et al. 2012. First assessment of SMOS data over open ocean: Part II Sea surface salinity. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1662–1675CrossRefGoogle Scholar
  4. Camps A, Font J, Vall-llossera M, et al. 2004. The WISE 2000 and 2001 field experiments in support of the SMOS Mission: Sea surface L-Band brightness temperature observations and their application to sea surface salinity retrieval. IEEE Transactions on Geoscience and Remote Sensing, 42(4): 804–823CrossRefGoogle Scholar
  5. Chen Jian, Zhang Ren, Wang Huizan, et al. 2014. An analysis on the error structure and mechanism of soil moisture and ocean salinity remotely sensed sea surface salinity products. Acta Oceanologica Sinica, 33(1): 48–55CrossRefGoogle Scholar
  6. Cheng Y, Andersen O B, Knudsen P. 2012. First evaluation of MyOcean altimetric data in the Arctic Ocean. Ocean Science Discussions, 9(1): 291–314CrossRefGoogle Scholar
  7. Ebuchi N, Abe H. 2012. Evaluation of sea surface salinity observed by Aquarius. In: 2012IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Munich: IEEE, 5767–5769CrossRefGoogle Scholar
  8. Feng Shizuo, Li Fengqi, Li Shaoqing. 1999. An Introduction to Marine Science (in Chinese). Beijing: The Higher Education Press, 83–108Google Scholar
  9. Font J, Lagerloef G, Le Vine D, et al. 2003. The determination of surface salinity with SMOS-recent results and main issues. In: Proceedings of 2003 IEEE International Geoscience and Remote Sensing Symposium (IGARSS'03). Toulouse, France: IEEE, 7–9Google Scholar
  10. Glejin J, Kumar V S, Nair T M B. 2013. Monsoon and cyclone induced wave climate over the near shore waters off Puduchery, south western Bay of Bengal. Ocean Engineering, 72: 277–286CrossRefGoogle Scholar
  11. Guinehut S, Dhomps A L, Larnicol G, et al. 2012. High resolution 3-D temperature and salinity fields derived from in situ and satellite observations. Ocean Science, 8(5): 845–857CrossRefGoogle Scholar
  12. Kerr Y H, Waldteufel P, Wigneron J P, et al. 2001. Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission. IEEE Transactions on Geoscience and Remote Sensing, 39(8): 1729–1735CrossRefGoogle Scholar
  13. Kerr Y H, Waldteufel P, Wigneron J P, et al. 2010. The SMOS Mission: New tool for monitoring key elements of the global water cycle. Proceedings of the IEEE, 98(5): 666–68CrossRefGoogle Scholar
  14. Lagerloef G. 2012. Satellite mission monitors ocean surface salinity. Eos, Transacations American Geophysical Union, 93(25): 233–234CrossRefGoogle Scholar
  15. Lagerloef G, Colomb F R, Le Vine D, et al. 2008. The Aquarius/SAC-D Mission: Designed to meet the salinity remote-sensing challenge. Oceanography, 21(1): 68–81CrossRefGoogle Scholar
  16. Lerner R M, Hollinger J P. 1977. Analysis of 1.4 GHz radiometric measurements from Skylab. Remote Sensing of Environment, 6(4): 251–269CrossRefGoogle Scholar
  17. Le Vine D M, Lagerloef G S E, Colomb F R, et al. 2007. Aquarius: An instrument to monitor sea surface salinity from space. IEEE Transactions on Geoscience and Remote Sensing, 45(7): 2040–2050CrossRefGoogle Scholar
  18. Le Vine D M, Lagerloef G S E, Torrusio S E. 2010. Aquarius and remote sensing of sea surface salinity from space. Proceedings of the IEEE, 98(5): 688–703CrossRefGoogle Scholar
  19. Le Vine D M. 2011. Aquarius Instrument and Salinity Retrieval. h t t p: / / a q u a r i u s. u m a i n e. e d u / c g i / d o c u m e n t s. h t m [03–Jun–2011]Google Scholar
  20. Liang Yuqing, Liu Jinfang, Zhang Xian, et al. 2003. Temporal and spatial characteristics of South Indian Ocean wind field. Marine Forecasts (in Chinese), 20(1): 25–31Google Scholar
  21. Lu Zhaoshi, Shi Jiuxin, Jiao Yutian, et al. 2006. Experimental study of microwave remote sensing of sea surface salinity. Ocean Technology (in Chinese), 25(3): 70–75, 89Google Scholar
  22. Luis A J, Pandey P C. 2005. Characteristics of atmospheric divergence and convergence in the Indian Ocean inferred from scatterometer winds. Remote Sensing of Environment, 97(2): 231–237CrossRefGoogle Scholar
  23. Meissner T, Wentz F, Lagerloef G, et al. 2012. The Aquarius salinity retrieval algorithm. In: 2012 12th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment. Rome: IEEE, 1–3CrossRefGoogle Scholar
  24. Nardelli B B, Tronconi C, Pisano A, et al. 2013. High and Ultra-High resolution processing of satellite Sea Surface Temperature data over Southern European Seas in the framework of MyOcean project. Remote Sensing of Environment, 129: 1–16CrossRefGoogle Scholar
  25. Ratheesh S, Sharma R, Sikhakolli R, et al. 2014. Assessing sea surface salinity derived by Aquarius in the Indian Ocean. IEEE Geoscience and Remote Sensing Letters, 11(4): 719–722CrossRefGoogle Scholar
  26. Reagan J, Boyer T, Antonov J. 2013. Comparison analysis between Aquarius sea surface salinity and world ocean database in situ analyzed sea surface salinity.http://aquarius.umeoce.maine.edu/docs/aqsci2013_reagan.pdf [2013–11]Google Scholar
  27. Reagan J, Boyer T, Antonov J. 2014. Comparison analysis between Aquarius sea surface salinity and World Ocean Database in situ analyzed sea surface salinity. Journal of Geophysical Research: Oceans, 119(11): 8122–8140Google Scholar
  28. Reynolds R W, Rayner N A, Smith T M, et al. 2002. An improved in situ and satellite SST analysis for climate. Journal of Climate, 15(13): 1609–1625CrossRefGoogle Scholar
  29. Sabia R, Camps A, Talone M, et al. 2010. Determination of the sea surface salinity error budget in the Soil Moisture and Ocean Salinity Mission. IEEE Transactions on Geoscience and Remote Sensing, 48(4): 1684–1693CrossRefGoogle Scholar
  30. mitt R W. 2008. Salinity and the global water cycle. Oceanography, 21(1): 12–19CrossRefGoogle Scholar
  31. Sharma R, Agarwal N, Momin I M, et al. 2010. Simulated sea surface salinity variability in the Tropical Indian Ocean. Journal of Climate, 23(24): 6542–6554CrossRefGoogle Scholar
  32. Shi Jiuxin, Lu Zhaoshi, Li Shujiang, et al. 2006. Retrieval algorithm for seawater's salinity and temperature by L and S band microwave remote sensing. Chinese High Technology Letters (in Chinese), 16(11): 1181–1184Google Scholar
  33. Wang Xinxin, Yang Jianhong, Zhao Dongzhi, et al. 2013. SMOS satellite salinity data accuracy assessment in the China coastal areas. Haiyang Xuebao (in Chinese), 35(5): 169–176Google Scholar
  34. Wentz F J, Le Vine D. 2008. Algorithm theoretical basis document Aquarius level-2 radiometer algorithm: Revision 1. RSS Technical Report 012208, http://oceancolor.gsfc.nasa.gov/AQUARIUS/DOCS/Level2_salinity_atbd_rev1.pdfGoogle Scholar
  35. Xie Shangping, Annamalai H, Schott F A, et al. 2002. Structure and mechanisms of South Indian Ocean climate variability. Journal of Climate, 15(8): 864–878CrossRefGoogle Scholar
  36. Yin Xiaobin, Liu Yuguang, Zhang Hande, et al. 2005. Microwave remote sensing of sea surface salinity—A study on microwave radiation theory of calm sea surface. Chinese High Technology Letters (in Chinese), 15(8): 86–90Google Scholar
  37. Yin Xiaobin, Liu Yuguang, Zhang Hande. 2006. Removing the impact of wind direction on remote sensing of sea surface salinity. Chinese Science Bulletin, 51(11): 1368–1373CrossRefGoogle Scholar
  38. Yin Xiaobin, Liu Yuguang, Zhang Hande. 2006. Removing the impact of wind direction on remote sensing of sea surface salinity. Chinese Science Bulletin (in Chinese), 51(3): 349–354Google Scholar
  39. Yueh S H, West R, Wilson W J, et al. 2001. Error sources and feasibility for microwave remote sensing of ocean surface salinity. IEEE Transactions on Geoscience and Remote Sensing, 39(5): 1049–1060CrossRefGoogle Scholar
  40. Zhao Kai, Shi Jiuxin, Zhang Hande. 2008. High sensitivity airborne Lband microwave radiometer measurements of sea surface salinity. Journal of Remote Sensing (in Chinese), 12(2): 277–283Google Scholar

Copyright information

© The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Shenzhen Xia
    • 1
    • 2
    • 3
  • Changqing Ke
    • 1
    • 2
    • 3
  • Xiaobing Zhou
    • 4
  • Jie Zhang
    • 5
  1. 1.Jiangsu Provincial Key Laboratory of Geographic Information Science and TechnologyNanjing UniversityNanjingChina
  2. 2.Collaborative Innovation Center of South China Sea StudiesNanjingChina
  3. 3.Collaborative Innovation Center of Novel Software Technology and IndustrializationNanjingChina
  4. 4.Department of Geophysical EngineeringMontana Tech of the University of MontanaButteUSA
  5. 5.The First Institute of OceanographyState Oceanic AdministrationQingdaoChina

Personalised recommendations