Sea-ice contamination in the antenna field of view constitutes a large error source in retrieving sea-surface salinity (SSS) with the spaceborne Soil Moisture Active Passive (SMAP) L-band radiometer. This is a major obstacle in the current NASA/Remote Sensing Systems (RSS) SMAP SSS retrieval algorithm in regards to obtaining accurate SSS measurements in the polar oceans. Our analysis finds a strong correlation between 8-day averaged SMAP L-band brightness temperature (TB) bias and TB measurements from the Advanced Microwave Scanning Radiometer (AMSR2) in the C-through Ka-band frequency range for sea-ice contaminated ocean scenes. We show how this correlation can be employed to develop: (1) a discriminant analysis that is able to reliably flag the SMAP observations for sea-ice contamination and (2) subsequently remove the sea-ice contamination from the SMAP observations, which results in significantly more accurate SMAP SSS retrievals near the sea-ice edge. We provide a case study that evaluates the performance of the proposed sea-ice flagging and correction algorithm. Our method is also able to detect drifting icebergs, which go often undetected in many available standard sea-ice products and thus result in spurious SMAP SSS retrievals.
Keywords: AMSR2; SMAP; cold water; sea surface salinity; sea-ice.