Retrieval of remotely sensed sea surface salinity using MODIS data in the Chinese Bohai Sea

ABSTRACT

Salinity dominates seawater density and directly affects physical and biochemical processes. Having a reliable retrieval model is essential to providing frequent and accurate sea surface salinity (SSS) data for marine research. Remote-sensing techniques provide alternatives for SSS data retrieval with its advantages of wide area surveys and real-time monitoring. In the present study, inverse relationship between SSS and coloured dissolved organic matter (CDOM) concentration in the Chinese Bohai Sea was verified. Thus, four simple band ratios of the original remote-sensing reflectance (R_rs) used to retrieve the CDOM concentration were compared and tested during SSS retrieval. R_rs (531)/R_rs (551) performed best among the four given band ratios. The model employed here can be applied to derive SSS with a root mean square error (RMSE) of 0.26 practical salinity units (psu) (R² = 0.76). A calibration model was verified using a discrete dataset of the measured SSS and was tested further during mapping of SSS in the Chinese Bohai Sea during 2010–2014. The yielded spatial patterns of SSS were satisfactory and an inverse relationship between SSS and the Yellow River discharge was confirmed.

Acknowledgement

This work was jointly supported by the Key Research Program of the Chinese Academy of Sciences under grants NSFC41371483, KZZD-EW-14 and Key Laboratory of Coastal Environmental Processes and Ecological Remediation, YICCAS Grant No.: 2016KFJJ03. We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was jointly supported by the Key Research Program of the Chinese Academy of Sciences under grants NSFC41371483, KZZD-EW-14 and Key Laboratory of Coastal Environmental Processes and Ecological Remediation, YICCAS grant number: 2016KFJJ03.