IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2024)

Correction of the SMAP Sea Surface Brightness Temperature and Retrieval of Sea Surface Salinity Incorporating CYGNSS Observables

  • Zheng Li,
  • Fei Guo,
  • Zhiyu Zhang,
  • Xiaohong Zhang

DOI
https://doi.org/10.1109/JSTARS.2023.3348880
Journal volume & issue
Vol. 17
pp. 3226 – 3235

Abstract

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The correction of sea surface brightness temperature is crucial for improving the accuracy of sea surface salinity (SSS) retrieval by L-band microwave radiometer. However, the traditional method of correcting brightness temperature using only wind speed and significant wave height (SWH) is inadequate, as sea surface roughness is affected by multiple factors. The Global Navigation Satellite System Reflectometer (GNSS-R) observables, which directly respond to sea surface roughness, have been preliminarily validated in ground-based experiments for their potential to correct sea surface brightness temperature. Compared with ground-based GNSS-R, spaceborne GNSS-R has a wider coverage and can better support the brightness temperature correction of spaceborne L-band microwave radiometers. This article has preliminarily verified the correlation between cyclone GNSS (CYGNSS) observables and brightness temperature variations, and found that the incidence angle of the observable needs to be taken into account when retrieving SSS jointly with soil moisture active and passive (SMAP) and CYGNSS. A multilayer perceptron (MLP) model was established to assess the SSS retrieval performance of SMAP combined with different parameters. The results show that the retrieval performance based on the MLP model is better than that based on the geophysical model function model. Compared with joint wind speed and SWH, joint CYGNSS observables performs better in retrieving SSS. The root mean square error of retrieval salinity decreased from 0.58 to 0.46 psu, and the correlation coefficient (R) increased from 0.83 to 0.90. This provides reference for future joint retrieval of SSS using L-band microwave radiometers and spaceborne GNSS-R.

Keywords