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SAR mode altimetry observations of internal solitary waves in the tropical ocean: a method of detection

Santos-Ferreira, Adriana M.; Silva, Jose C. B. da; Srokosz, Meric. 2018 SAR mode altimetry observations of internal solitary waves in the tropical ocean: a method of detection. In: 2018 Doppler Oceanography from Space (DOfS), Brest, France, 10-12 Oct. 2018. IEEE, 1-7.

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Abstract/Summary

It is demonstrated that the synthetic aperture radar altimeter (SRAL) on board the Sentine1-3A can detect short-period internal solitary waves (ISWs) with scales of the order of a kilometre. A variety of signatures owing to the surface manifestations of the ISWs are apparent in the SRAL Leve1-2 products over the ocean. These signatures are identified in several geophysical parameters, such as radar back scatter (sigmaO) and sea level anomaly (SLA). Radar backscatter is the primary parameter in which ISWs can be identified owing to the measurable sea surface roughness perturbations in the along-track direction resulting from the sharpened SRAL footprint. The SRAL footprint is sufficiently small to capture radar power fluctuations over successive wave crests and troughs, which produce rough and slick surface patterns arrayed in parallel bands with scales of a few kilometres along-track. Furthermore, it was possible to calculate the mean square slope (mss) for the dual-band (Ku and C bands) altimeter of Sentine1-3, which made the ISW signatures unambiguously identified because of the large mss variations in exact synergy with OLCI (Ocean Land Colour Imager) images. Hence, the detection method is validated in cloud-free sunglint OLCI images. It is shown that both sigmaO and SLA yield realistic estimates for routine observation of ISWs with the SRAL. The detection method that is used relies on the parameter mss which is calculated from sigmaO. This is a significant improvement from previous observations recently reported for conventional pulse-limited altimeters (Jason- 2). A Matlab code is developed to be used in any deep ocean region. Wavelets were applied for a first analysis of the mss variations because ISWs can be readily identified in high frequencies signals. Other geophysical parameters such as SLA are used to exclude phenomena that are unlikely to be ISWs.

Item Type: Publication - Conference Item (Paper)
Digital Object Identifier (DOI): https://doi.org/10.1109/DOfS.2018.8587277
Date made live: 15 Apr 2019 12:55 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/522841

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