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The Detection and Tracking of Ocean Surface Roughness Supression by Ocean Pollutans Via Surfactants
Summary
Researchers investigated how ocean pollutants and surfactants suppress ocean surface roughness and demonstrated that GNSS-R satellites can detect these anomalies as apparent errors in wind speed estimation. By combining GNSS-R data with hyperspectral imagery and other satellite products, the study shows it is possible to distinguish between different pollutant types and generate individual pollutant maps.
GNSS-R satellites can be used to track ocean surface wind speed and roughness via their direct measurement of radar cross section. However, if an agent were to change ocean surface roughness without changing the wind speed there would be an error in the estimated wind speed. This study posits that some of these errors are caused by ocean pollutants and related surfactants. Surfactants are soaps and oils that decrease local ocean surface tension, and therefore suppress the wind driven roughening of the surface. This paper demonstrates how GNSS-R satellites with the aid of hyperspectral imagers and other satellite products can discern the difference between various ocean pollutants. The decomposition of different roughness suppression agents allows for individual pollutant maps to be generated, which will aid our understanding of ocean microplastic distributions, as there is currently no other reliable and effective method for their detection and tracking.