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Improving the altimeter-derived surface currents using Sea Surface Temperature (SST) data: A sensitivity study to SST products

Articolo
Data di Pubblicazione:
2020
Abstract:
Measurements of ocean surface topography collected by satellite altimeters provide geostrophic estimates of the sea surface currents at relatively low resolution. The effective spatial and temporal resolution of these velocity estimates can be improved by optimally combining altimeter data with sequences of high resolution interpolated (Level 4) Sea Surface Temperature (SST) data, improving upon present-day values of approximately 100 km and 15 days at mid-latitudes. However, the combined altimeter/SST currents accuracy depends on the area and input SST data considered. Here, we present a comparative study based on three satellite-derived daily SST products: the Remote Sensing Systems (REMSS, 1/10° resolution), the UK Met Office OSTIA (1/20° resolution), and the Multiscale Ultra-High resolution SST (1/100° resolution). The accuracy of the marine currents computed with our synergistic approach is assessed by comparisons with in-situ estimated currents derived from a global network of drifting buoys. Using REMSS SST, the meridional currents improve up to more than 20% compared to simple altimeter estimates. The maximum global improvements for the zonal currents are obtained using OSTIA SST, and reach 6%. Using the OSTIA SST also results in slight improvements (?1.3%) in the zonal flow estimated in the Southern Ocean (45°S to 70°S). The homogeneity of the input SST effective spatial resolution is identified as a crucial requirement for an accurate surface current reconstruction. In our analyses, this condition was best satisfied by the lower resolution SST products considered.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
sea surface temperature; ocean currents; altimetry; earth observations synergy
Elenco autori:
BUONGIORNO NARDELLI, Bruno; Ciani, Daniele; Santoleri, Rosalia
Autori di Ateneo:
BUONGIORNO NARDELLI BRUNO
CIANI DANIELE
SANTOLERI ROSALIA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/409368
Pubblicato in:
REMOTE SENSING (BASEL)
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