Aquarius semi-theoretical model of sea surface salinity retrieval for foam-covered surface. Issue 11 (2nd June 2020)

• Record Type: Journal Article
• Authors: Liu, Shu-Bo; Wei, En-Bo; Li, Yi-Nan; Dang, Hong-Xing; Li, Hao
• Is Part Of: International journal of remote sensing. Volume 41:Issue 11(2020)
• Page Start: 4293
• Page End: 4311
• Publication Date: 2020-06-02
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2020.1714783
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: For high wind speeds (7–22 m s −1 ), a semi-theoretical model for retrieving sea surface salinity (SSS) is derived from the version V3.0 of Aquarius data. In the model, the sea surface brightness temperature is the sum of the brightness temperatures of foam-covered sea surface and rough sea surface, which is weighted by the foam coverage. The emissivity of foam layer is dealt with the effective permittivity of foam composites and the wave approach theory, where the air volume fraction and thickness of the foam layer are optimized with Aquarius data. Due to the influence of foam coverage, the foam contribution to the sea surface emissivity is smaller than that of the rough sea surface, only about 20% at 22 m s −1 . Furthermore, the model is applied to retrieve Aquarius SSS for the wind speeds larger than 7 m s −1 . The inverse accuracy is assessed by comparison with ARGO monthly gridded salinity products. The average root mean square error (RMSE) between the retrieved SSS and Argo SSS are about 0.20 and 0.30 psu for the latitude within 40° S–40° N and 70° S–70 N, respectively. The model improves the retrieval accuracy of SSS for high wind speeds.