Validation and correction of sea surface salinity retrieval from SMAP

Sisi Qin; Hui Wang; Jiang Zhu; Liying Wan; Yu Zhang; Haoyun Wang

doi:10.1007/s13131-020-1533-0

Volume 39 Issue 3

Apr. 2020

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Article Navigation > Acta Oceanologica Sinica > 2020 > 39(3): 148-158

Sisi Qin, Hui Wang, Jiang Zhu, Liying Wan, Yu Zhang, Haoyun Wang. Validation and correction of sea surface salinity retrieval from SMAP[J]. Acta Oceanologica Sinica, 2020, 39(3): 148-158. doi: 10.1007/s13131-020-1533-0

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Sisi Qin, Hui Wang, Jiang Zhu, Liying Wan, Yu Zhang, Haoyun Wang. Validation and correction of sea surface salinity retrieval from SMAP[J]. Acta Oceanologica Sinica, 2020, 39(3): 148-158. doi: 10.1007/s13131-020-1533-0

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Validation and correction of sea surface salinity retrieval from SMAP

doi: 10.1007/s13131-020-1533-0

Sisi Qin^{1, 2},
Hui Wang³,
Jiang Zhu^{4, 5},
Liying Wan^{3
,
,},
Yu Zhang³,
Haoyun Wang^{3, 5}

1.
National Meteorological Center, Beijing 100081, China
2.
Numerical Weather Prediction Center of China Meteorological Administration, Beijing 100081, China
3.
Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing 100081, China
4.
International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
5.
University of the Chinese Academy of Sciences, Beijing 100049, China

Funds: The National Key Research and Development Program of China under contract Nos 2016YFC1401409 and 2016YFC1401704; the National Natural Science Foundation of China under contract Nos 41506031 and 41606029.

More Information

Corresponding author: E-mail: liying.wan@nmefc.cn
Received Date: 2018-10-18
Accepted Date: 2018-12-12

Available Online: 2020-04-21

Publish Date: 2020-03-25

Abstract

Abstract

In this study, sea surface salinity (SSS) Level 3 (L3) daily product derived from soil moisture active passive (SMAP) during the year 2016, was validated and compared with SSS daily products derived from soil Moisture and ocean salinity (SMOS) and in-situ measurements. Generally, the root mean square error (RMSE) of the daily SSS products is larger along the coastal areas and at high latitudes and is smaller in the tropical regions and open oceans. Comparisons between the two types of daily satellite SSS product revealed that the RMSE was higher in the daily SMOS product than in the SMAP, whereas the bias of the daily SMOS was observed to be less than that of the SMAP when compared with Argo floats data. In addition, the latitude-dependent bias and RMSE of the SMAP SSS were found to be primarily influenced by the precipitation and the sea surface temperature (SST). Then, a regression analysis method which has adopted the precipitation and SST data was used to correct the larger bias of the daily SMAP product. It was confirmed that the corrected daily SMAP product could be used for assimilation in high-resolution forecast models, due to the fact that it was demonstrated to be unbiased and much closer to the in-situ measurements than the original uncorrected SMAP product.
- sea surface salinity (SSS),
- soil moisture active passive (SMAP),
- soil moisture and ocean salinity (SMOS),
- validation,
- correction

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References(30)

References

[1]	Abe H, Ebuchi N. 2014. Evaluation of sea-surface salinity observed by Aquarius. Journal of Geophysical Research: Oceans, 119(11): 8109–8121. doi: 10.1002/2014JC010094
[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): 1688–1702. doi: 10.1109/TGRS.2011.2167340
[3]	Berrisford P, Dee D, Poli P, et al. 2011. The ERA-interim archive: Version 2.0. Nihon Seirigaku Zasshi Journal of the Physiological Society of Japan, 31(10): 1–40
[4]	Boutin J, Martin N, Yin X B, 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): 1662–1675. doi: 10.1109/TGRS.2012.2184546
[5]	Boutin J, Vergely J L, Marchand S, et al. 2018. New SMOS Sea Surface Salinity with reduced systematic errors and improved variability. Remote Sensing of Environment, 214: 115–134. doi: 10.1016/j.rse.2018.05.022
[6]	Drucker R, 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. doi: 10.1002/2014JC010045
[7]	Ebuchi N, Abe H. 2014. Evaluation of sea surface salinity observed by Aquarius and SMOS. In: Proceedings of 2013 IEEE International Geoscience and Remote Sensing Symposium. Melbourne: IEEE, 119: 8109–8121
[8]	Font J, Kerr Y H, Srokosz M A, et al. 2001. SMOS: a satellite mission to measure ocean surface salinity. In: Proceedings Volume 4167, Atmospheric Propagation, Adaptive Systems, and Laser Radar Technology for Remote Sensing. Barcelona: SPIE, 4167: 207–214
[9]	Garcia-Eidell C, Comiso J C, Dinnat E, et al. 2017. Satellite observed salinity distributions at high latitudes in the northern hemisphere: a comparison of four products. Journal of Geophysical Research: Oceans, 122(9): 7717–7736. doi: 10.1002/2017JC013184
[10]	Gould J, Roemmich D, Wijffels S, et al. 2004. Argo profiling floats bring new era of in situ ocean observations. Eos Transactions American Geophysical Union, 85(19): 185–191
[11]	Hackert E, Busalacchi A J, Ballabrera-Poy J. 2014. Impact of Aquarius sea surface salinity observations on coupled forecasts for the tropical Indo-Pacific Ocean. Journal of Geophysical Research: Oceans, 119(7): 4045–4067. doi: 10.1002/2013JC009697
[12]	Kolodziejczyk N, Reverdin G, Boutin J, et al. 2015. Observation of the surface horizontal thermohaline variability at mesoscale to submesoscale in the north-eastern subtropical Atlantic Ocean. Journal of Geophysical Research: Oceans, 120(4): 2588–2600. doi: 10.1002/2014JC010455
[13]	Lagerloef G S E. 2002. Introduction to the special section: The role of surface salinity on upper ocean dynamics, air-sea interaction and climate. Journal of Geophysical Research: Oceans, 107(C12): SRF 1-1–SRF 1-2. doi: 10.1029/2002JC001669
[14]	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): 68–81. doi: 10.5670/oceanog.2008.68
[15]	Lee T. 2016. Consistency of Aquarius sea surface salinity with Argo products on various spatial and temporal scales. Geophysical Research Letters, 43(8): 3857–3864. doi: 10.1002/2016GL068822
[16]	Lu Zhengting, Cheng Lijing, Zhu Jing, et al. 2016. The complementary role of SMOS sea surface salinity observations for estimating global ocean salinity state. Journal of Geophysical Research: Oceans, 121(6): 3672–3691. doi: 10.1002/2015JC011480
[17]	Martin M J. 2016. Suitability of satellite sea surface salinity data for use in assessing and correcting ocean forecasts. Remote Sensing of Environment, 180: 305–319. doi: 10.1016/j.rse.2016.02.004
[18]	McPhaden M J. 1995. The tropical atmosphere ocean array is completed. Bulletin of the American Meteorological Society, 76(5): 739–744. doi: 10.1175/1520-0477-76.5.739
[19]	McPhaden M J, Meyers G, Ando K, et al. 2009. RAMA: the research moored array for African-Asian-Australian monsoon analysis and prediction. Bulletin of the American Meteorological Society, 90(4): 459–480. doi: 10.1175/2008BAMS2608.1
[20]	Meissner T, Wentz F J. 2016. Remote Sensing Systems SMAP Ocean Surface Salinities [Level 2C, Level 3 Running 8-day, Level 3 Monthly], Version 2.0 validated release. Remote Sensing Systems, Santa Rosa, CA, USA. www.remss.com/missions/smap
[21]	Meissner T, Wentz F J, Le Vine D M. 2018. The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases. Remote Sensing, 10(7): 1121. doi: 10.3390/rs10071121
[22]	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): 719–722. doi: 10.1109/LGRS.2013.2277391
[23]	Reagan J, Boyer T, Antonov J, et al. 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): 8122–8140. doi: 10.1002/2014JC009961
[24]	Reul N, Tenerelli J, Chapron B, et al. 2007. Modeling sun glitter at L-band for sea surface salinity remote sensing with SMOS. IEEE Transactions on Geoscience and Remote Sensing, 45(7): 2073–2087. doi: 10.1109/TGRS.2006.890421
[25]	Servain J, Busalacchi A J, McPhaden M J, et al. 1998. A pilot research moored array in the tropical Atlantic (PIRATA). Bulletin of the American Meteorological Society, 79(10): 2019–2032. doi: 10.1175/1520-0477(1998)079<2019:APRMAI>2.0.CO;2
[26]	Tang Wenqing, Fore A, Yueh S, et al. 2017. Validating SMAP SSS with in situ measurements. Remote Sensing of Environment, 200: 326–340. doi: 10.1016/j.rse.2017.08.021
[27]	Tang Wenqing, Yueh S H, Fore A G, et al. 2014. Validation of Aquarius sea surface salinity with in situ measurements from Argo floats and moored buoys. Journal of Geophysical Research: Oceans, 119(9): 6171–6189. doi: 10.1002/2014JC010101
[28]	Terray L, Corre L, Cravatte S, et al. 2012. Near-surface salinity as nature’s rain gauge to detect human influence on the tropical water cycle. Journal of Climate, 25(3): 958–977. doi: 10.1175/JCLI-D-10-05025.1
[29]	Yueh S H, Chaubell J. 2012. Sea surface salinity and wind retrieval using combined passive and active L-band microwave observations. IEEE Transactions on Geoscience and Remote Sensing, 50(4): 1022–1032. doi: 10.1109/TGRS.2011.2165075
[30]	Yueh S, Tang Wenqing, Fore A, et al. 2014. Aquarius geophysical model function and combined active passive algorithm for ocean surface salinity and wind retrieval. Journal of Geophysical Research: Oceans, 119(8): 5360–5379. doi: 10.1002/2014JC009939