Abstract
In sea surface salinity (SSS) retrieval using L-band passive radiometry, radiometer-independent ocean wind speed is needed as auxiliary data. Wind speed data from scatterometer and weather models are commonly used as auxiliary data in satellite SSS missions. This papers overarching goal is to explore the feasibility of incorporating the Cyclone Global Navigation Satellite System (CyGNSS) data into the SSS retrieval algorithm of the Soil Moisture Active and Passive (SMAP) mission over tropical and subtropical oceans. As a proof-of-concept study, empirical geophysical model functions (GMF) in the retrieval algorithm are developed using the statistics of collocated SMAP, CyGNSS, and referenced buoys measurements. The SSS accuracy of CyGNSS-incorporated salinity retrieval is investigated against the SMAP SSS data product. Comparisons show that the proposed CyGNSS-incorporated retrieval algorithm improves the SSS accuracy by 0.1~0.2 psu at low wind speed (< 2 m/s). To some extent, it proves that Spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) could be a new and helpful data source to understand wind-induced emissivity over a smooth ocean. The dependencies of emissivity on different geophysical parameters (i.e., sea surface temperature, significant wave height, and precipitation) are analyzed, and the spatial and seasonal variabilities of SSS errors are shown and linked to these geophysical parameters. The findings of this research provide valuable insights for future development and operation of the radiometer-based SSS retrieval algorithm using wind speed data from spaceborne GNSS-R.
Highlights
O CEAN salinity is a crucial variable in density-driven ocean circulation
The wind speed data of the Cyclone Global Navigation Satellite System (CyGNSS) are incorporated into the sea surface salinity (SSS) retrieval algorithm of the Soil Moisture Active Passive (SMAP) mission over the tropical and subtropical ocean
geophysical model functions (GMF) are developed using the collocated statistics of SMAP, CyGNSS, and Array for Real-Time Geostrophic Oceanography (ARGO) ground truth
Summary
O CEAN salinity is a crucial variable in density-driven ocean circulation. Knowledge of ocean salinity is crucial for understanding the climate variability [1], water cycle [2,3,4], airsea interactions [5, 6], and ocean biogeochemistry [7]. Radiometry presents its maximum sensitivity to SSS in terms of the L-band brightness temperature ( TB ) [10], the accurate measurement of TB at 1.4 GHz is significant in SSS retrieval Missions, such as Soil Moisture and Ocean Salinity (SMOS) [11], Aquarius [12], Soil Moisture Active Passive (SMAP) [13], and FSSCat [14], use the radiometer to observe L-band TB with high radiation accuracy. Wind speed (WS) data independent of L-band radiometer measurements is essential in SSS retrieval. We incorporate the CyGNSS WS into the SSS retrieval algorithm of the SMAP mission over the tropical and subtropical ocean. The findings of this study provide valuable insights for future development and operation of the radiometer-based SSS retrieval algorithm using wind speed data from spaceborne GNSS-R.
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