Abstract's details

Satellite altimetry data validation in San Matias Gulf, Argentina

Loreley Selene Lago (Universidad de Buenos Aires, Argentina)


Laura Agustina Ruiz Etcheverry (Universidad de Buenos Aires, Argentina); Marcello Passaro (University of Southampton, UK); Martin Saraceno (Universidad de Buenos Aires, Argentina)

Event: 2015 Ocean Surface Topography Science Team Meeting

Session: Quantifying Errors and Uncertainties in Altimetry data

Presentation type: Type Poster

Contribution: not provided


The objective of this work is to evaluate satellite altimetry data and its corrections terms in a complex coastal environment. Satellite altimetry data are compared with data obtained from a bottom pressure recorder deployed during 22 months. The instrument is moored at 1 km from the coast in San Matias Gulf, Argentina, at only 38m from the nominal intersection of satellite tracks 52 (descending) and 189 (ascending) of Jason 2. Data obtained from the bottom pressure recorder are therefore ideal to test coastal satellite altimetry products. Correlation between the two datasets is 0.9 (95% CL) when no corrections are applied to the altimeter data, until a distance of 3 km to the coast for track 189, and 10 km for track 52. Results show that both sea bias and ionosphere corrections reduce the correlation between altimetry and in-situ data near the coast: a correlation value of 0.9 is found at a distance from the coast of 7 km (track 189) and 13 km (track 52). Tide correction also reduces the correlation between the two datasets along the tracks. Eight global models were considered, and the one with lower root sum square of the difference considering the first 11 amplitude and phase constants is FES2012 (0.84 cm). Finally two retracking algorithms were considered: a classic Brown model (MLE4) and a more recent developed method: ALES (Adaptive Leading Edge Subwaveform Retracker). Both ALES and MLE4 show similar correlation with in-situ data when applied to satellite altimetry data for distances larger than 10km from the coast, obtaining a correlation factor of 0.9 (95% CL). ALES has the ability to recover more data close to the coast, especially for the ascending track 189 (the one that has a transition from ocean to land), up to 3km from the coast. We conclude that satellite data from Jason 2 can adequately represent the sea level variability as close as 3 km from the coast depending on the relative motion of the satellite to the coast and the corrections used.

Poster show times:

Room Start Date End Date
Grand Ballroom Foyer Thu, Oct 22 2015,11:00 Thu, Oct 22 2015,18:00
Loreley Selene Lago
Universidad de Buenos Aires