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Impact of rain-induced sea surface roughness variations on salinity retrieval from the Aquarius/SAC-D satellite

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Abstract

Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher, which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and TRMM 3B42 matchup dataset indicate that the retrieved sea surface salinity (SSS) is underestimated by the present Aquarius algorithm compared to numerical model outputs, especially in cases of a high rain rate. For example, the bias between satellite-observed SSS and numerical model SSS is approximately 2 when the rain rate is 25 mm/h. The bias can be eliminated by accounting for rain-induced roughness, which is usually modeled by rain-generated ring-wave spectrum. The rain spectrum will be input into the Small Slope Approximation (SSA) model for the simulation of sea surface emissivity influenced by rain. The comparison with theoretical model indicated that the empirical model of rain spectrumis more suitable to be used in the simulation. Further, the coefficients of the rain spectrum are modified by fitting the simulations with the observations of the 2–year Aquarius and TRMM matchup dataset. The calculations confirm that the sea surface emissivity increases with the wind speed and rain rate. The increase induced by the rain rate is rapid in the case of low rain rate and low wind speed. Finally, a modified model of sea surface emissivity including the rain spectrum is proposed and validated by using the matchup dataset in May 2014. Compared with observations, the bias of the rain-induced sea surface emissivity simulated by the modified modelis approximately 1e–4, and the RMSE is slightly larger than 1e–3. With using more matchup data, thebias between model retrieved sea surface salinities and observationsmay be further corrected, and the RMSE may be reduced to less than 1 in the cases of low rain rate and low wind speed.

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References

  • Bliven L F, Sobieski P W, Craeye C. 1997. Rain generated ring-waves: measurements and modelling for remote sensing. IntJRemote Sens, 18(1): 221–228

    Google Scholar 

  • Boutin J, Martin N, Reverdin G, et al. 2013. Sea surface freshening inferred from SMOS and ARGO salinity: impact of rain. Ocean Sci, 9(1): 183–192

    Article  Google Scholar 

  • Boutin J, Martin N, Reverdin G, et al. 2014. Sea surface salinity under rain cells: SMOS satellite and in situ drifters observations. Journal of Geophysical Research: Oceans, 119(8): 5533–5545

    Google Scholar 

  • Boutin J, Martin N, Yin Xiaobin, et al. 2012. First assessment of SMOS data over open ocean: Part II-Sea surface salinity. IEEE Trans- Geosci Remote Sens, 50(5): 1662–1675

    Article  Google Scholar 

  • Chassignet E P, Hurlburt H E, Metzger E J, et al. 2009. US GODAE: global ocean prediction with the HYbrid coordinate ocean model (HYCOM). Oceanography, 22(2): 64–75

    Article  Google Scholar 

  • Contreras R F, Plant W J. 2006. Surface effect of rain on microwave backscatter from the ocean: Measurements and modeling. Journal of Geophysical Research: Oceans (1978–2012), 111(C8): C08019

    Article  Google Scholar 

  • Craeye C, Sobieski P W, Bliven L F. 1997. Scattering by artificial wind and rain roughened water surfaces at oblique incidences. IntJRemote Sens, 18(10): 2241–2246

    Google Scholar 

  • Durden S L, Vesecky J F. 1985. A physical radar cross-section model for a wind-driven sea with swell. IEEE JOceanic Eng, 10(4): 445–451

    Article  Google Scholar 

  • Felton C S, Subrahmanyam B, Murty V S N, et al. 2014. Estimation of the barrier layer thickness in the Indian Ocean using Aquarius Salinity. Journal of Geophysical Research: Oceans, 119(7): 4200–4213

    Google Scholar 

  • Font J, Camps A, Borges A, et al. 2010. SMOS: The challenging sea surface salinity measurement from space. Proc IEEE, 98(5): 649–665

    Article  Google Scholar 

  • Johnson J T, Zhang Min. 1999. Theoretical study of the small slope approximation for ocean polarimetric thermal emission. IEEE Trans Geosci Remote Sens, 37(5): 2305–2316

    Article  Google Scholar 

  • Kerr Y H, Waldteufel P, Wigneron J-P, et al. 2010. The SMOS mission: New tool for monitoring key elements ofthe global water cycle. Proc IEEE, 98(5): 666–687

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Le Vine D M, Lagerloef G S E, Torrusio S E. 2010. Aquarius and remote sensing of sea surface salinity from space. Proc IEEE, 98(5): 688–703

    Article  Google Scholar 

  • Ma Wentao, Yang Xiaofeng, Liu Guihong, et al. 2014. An Improved Model for L-Band Brightness Temperature Estimation Over Foam-Covered Seas Under Low and Moderate Winds. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(9): 3784–3793

    Article  Google Scholar 

  • Meissner T, Wentz F J. 2004. The complex dielectric constant of pure and sea water from microwave satellite observations. IEEE Trans Geosci Remote Sens, 42(9): 1836–1849

    Article  Google Scholar 

  • Qu Tangdong, Song Y T, Maes C. 2014. Sea surface salinity and barrier layer variability in the equatorial Pacific as seen from Aquarius and Argo. Journal of Geophysical Research: Oceans, 119(1): 15–29

    Google Scholar 

  • Reynolds R W, Smith T M, Liu Chunying, et al. 2007. Daily high-resolution-blended analyses for sea surface temperature. Journal of Climate, 20(22): 5473–5496

    Article  Google Scholar 

  • Sobieski P, Craeye C, Bliven L F. 2009. A relationship between rain radar reflectivity and height elevation variance of ringwaves due to the impact of rain on the sea surface. Radio Science, 44(3): CiteID RS3005

    Google Scholar 

  • Tang Wenqing, Yueh S, Fore A, et al. 2013. The rain effect on Aquarius' L-band sea surface brightness temperature and radar backscatter. Remote Sens Environ, 137: 147–157

    Article  Google Scholar 

  • Tang Wenqing, Yueh S H, Fore A G, et al. 2014. Uncertainty of Aquarius sea surface salinity retrieved under rainy conditions and its implication on the water cycle study. Journal of Geophysical Research: Oceans, 119(8): 4821–4839

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Wentz F J. 2005. The effect of clouds and rain on Aquarius salinity retrieval. Remote Sensing System Technical Memorandum, 3031805

  • Wentz F J, Le Vine David M. 2013. Aquarius Salinity Retrieval Algorithm. Algorithm Theoretical Basis Document

  • Yin Xiaobin, Boutin J, Martin N, et al. 2012a. Optimization of L-band sea surface emissivity models deduced from SMOS data. IEEE Trans Geosci Remote Sens, 50(5): 1414–1426

    Article  Google Scholar 

  • Yin Xiaobin, Boutin J, Spurgeon P. 2012b. First assessment of SMOS data over open ocean: Part I—Pacific Ocean. IEEE Trans Geosci Remote Sens, 50(5): 1648–1661

    Article  Google Scholar 

  • Yueh S H, Dinardo S J, Fore A G, et al. 2010. Passive and active L-band microwave observations and modeling of ocean surface winds. IEEE Trans Geosci Remote Sens, 48(8): 3087–3100

    Article  Google Scholar 

  • Yueh S H, Tang Wenqing, Fore A G, et al. 2013. L-band passive and active microwave geophysical model functions of ocean surface winds and applications to Aquarius retrieval. IEEE Trans Geosci Remote Sens, 51(9): 4619–4632

    Article  Google Scholar 

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Correspondence to Xiaofeng Yang.

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Foundation item: The National Natural Science Foundation of China under contract No. 41371355.

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Ma, W., Yang, X., Yu, Y. et al. Impact of rain-induced sea surface roughness variations on salinity retrieval from the Aquarius/SAC-D satellite. Acta Oceanol. Sin. 34, 89–96 (2015). https://doi.org/10.1007/s13131-015-0660-5

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  • DOI: https://doi.org/10.1007/s13131-015-0660-5

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