SMOS Near-Surface Salinity Stratification Under Rainy Conditions

Abstract

The European Space Agency’s soil moisture ocean salinity (SMOS) satellite was launched in 2009 to measure land soil moisture and sea surface salinity (SSS). It carries an L-band microwave imaging radiometer that measures brightness temperatures that are used to produce global ocean salinity (OS) maps every three days. Similar maps are obtained with NASA’s L-band push-broom radiometer Aquarius (AQ) on board of the AQ/SAC-D satellite that was launched in 2011. In previous studies, the Central Florida Remote Sensing Laboratory (CFRSL) has analyzed AQ SSS retrievals during rain and has developed a model to predict the effect of precipitation on the SSS measurements. This rain impact model (RIM) estimates the transient near-surface salinity stratification based upon the corresponding rain accumulation over the previous 24 h to the satellite observation. In this paper, the RIM methodology has been adapted to the SMOS geometry, presenting comparisons with its SSS measurements; also, spatial correlations are performed between SMOS salinity images with those predicted by RIM for different wind speed ranges. Therefore, the main objective of this research is to better understand the processes of near-surface salinity stratification, which impact the interpretation of satellite-based SSS measurements to measure the ocean bulk salinity (5–10-m depth). The results presented in this paper show an excellent performance of RIM when applied to SMOS SSS data. Also, the SSS comparisons show that significant rain events are rapidly diluted for wind speeds of $\sim 12 \text{ m}/\text{s}$ and above.