Seasonal variations of the geostrophic ocean surface circulation inferred from the combination of altimetry and GOCE data

Isabel Vigo (Universidad de Alicante, Spain)

CoAuthors

Jose M. Sanchez-Reales (Universidad de Alicante, Spain); Mario Trottini (Universidad de Alicante, Spain)

Event: 2014 Ocean Surface Topography Science Team Meeting

Session: The Geoid, Mean Sea Surfaces and Mean Dynamic Topography

Presentation type: Type Poster

The most recent advances in the geoid determination, provided by the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) mission, together with the continuous monitoring of the sea surface height by the altimeters on board of satellites have made possible to retrieve ocean surface currents directly through remote sensing. A reliable estimation of the ocean Dynamic Topography (DT) that, in turn, requires reliable measurements of the Absolute Sea Level (ASL) height and an independent geoid are the key to the determination of the Surface Geostrophic Currents (SGC). Nowadays it is possible to combine 20 years altimetry data with a GOCE geoid model to obtain a mean DT with an unprecedented precision and accuracy. In addition, the improved accuracy in satellite altimetry data allows us to determine ASL maps at weekly resolution. Weekly ASL maps are used to extend previous research on the mean circulation to study the ocean circulation variability.
In this work, we calculate and map the annual mean velocity, the seasonal variation about the mean, the annual and semiannual harmonics, and a surface circulation climatology inferred solely from satellite data. We combine weekly estimations of the ASL provided as a merged solution of high resolution altimetry data available with an independent solution (time-wise method) of the geoid provided by the third release of GOCE data. The result is a 52 weeks data set of surface current vectors, gridded at one fourth degree longitude and latitude resolution resolving spatial scales as short as 140 km. For presentation, this data set is averaged monthly and the results presented as monthly climatology are compared with a climatology based on in-situ observations from drifter data.
 
Isabel Vigo
Universidad de Alicante
Spain
vigo@ua.es