Sediment dynamics is the primary driver of the evolution of the coastal geomorphology and of the underwater shelf clinoforms. In this paper, we focus on mesoscale and sub-mesoscale processes, such as coastal currents and river plumes, and how they shape the sediment dynamics at regional or basin spatial scales. A new methodology is developed that combines observational data with numerical modelling: the aim is to pair satellite measurements of suspended sediment with velocity fields from numerical oceanographic models, to obtain an estimation of the sediment flux. A numerical divergence of this flux is then computed. The divergence field thus obtained shows how the aforementioned mesoscale processes distribute the sediments. The approach was applied and discussed on the Adriatic Sea, for the winter of 2012, using data provided by the ESA Coastcolour project and the output of a run of the MIT General Circulation Model.

Benincasa, M., Falcini, F., Adduce, C., Sannino, G., Santoleri, R. (2019). Synergy of satellite remote sensing and numerical ocean modelling for coastal geomorphology diagnosis. REMOTE SENSING, 11(22), 2636 [10.3390/rs11222636].

Synergy of satellite remote sensing and numerical ocean modelling for coastal geomorphology diagnosis

Benincasa M.
;
Adduce C.;
2019-01-01

Abstract

Sediment dynamics is the primary driver of the evolution of the coastal geomorphology and of the underwater shelf clinoforms. In this paper, we focus on mesoscale and sub-mesoscale processes, such as coastal currents and river plumes, and how they shape the sediment dynamics at regional or basin spatial scales. A new methodology is developed that combines observational data with numerical modelling: the aim is to pair satellite measurements of suspended sediment with velocity fields from numerical oceanographic models, to obtain an estimation of the sediment flux. A numerical divergence of this flux is then computed. The divergence field thus obtained shows how the aforementioned mesoscale processes distribute the sediments. The approach was applied and discussed on the Adriatic Sea, for the winter of 2012, using data provided by the ESA Coastcolour project and the output of a run of the MIT General Circulation Model.
2019
Benincasa, M., Falcini, F., Adduce, C., Sannino, G., Santoleri, R. (2019). Synergy of satellite remote sensing and numerical ocean modelling for coastal geomorphology diagnosis. REMOTE SENSING, 11(22), 2636 [10.3390/rs11222636].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/364256
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