Bathymetry improvement and tidal modeling at regional scales

Mathilde Cancet (NOVELTIS, France)


Florence Toublanc (NOVELTIS, France); Gérald Dibarboure (CNES, France); Thierry Guinle (CNES, France)

Event: 2017 Ocean Surface Topography Science Team Meeting

Session: Tides, internal tides and high-frequency processes

Presentation type: Type Poster

Coastal processes (tidal currents, storm surges, waves) are highly dependent on bathymetry and directly impact offshore and coastal activities and studies. Many studies and applications lie on a growing modelling effort of the ocean and the limited accuracy of bathymetry, especially on the continental shelves, contributes to degrade numerical model performances despite significant use of in-situ and satellite measurements assimilation. In particular, the tidal models are very sensitive to the bathymetry accuracy on the shelves, where the ocean tides show the largest amplitudes and are strongly non-linear. This has a direct impact on the quality of the altimetry sea surface heights as the tide correction is one of the largest corrections on the shelves, ranging from several centimetres to several metres.
Various sources of bathymetry data exist but many regions remain not well known because of too sparse measurements, data access limitation or large temporal variability of the seabed dynamics. This paper presents a project very recently launched by CNES with the aim to improve the bathymetry on a number of continental shelves. The work is divided in several steps: 1/ an inventory of existing datasets and methods to derive the bathymetry on the shelves ; 2/ the integration of the collected datasets into a reference global bathymetry dataset ; 3/ the evaluation of this new bathymetry dataset through hydrodynamic modelling and the production of regional tidal models.
This poster will highlight the methodology that will be followed in the project and the first investigations that have been made.

Poster show times:

RoomStart DateEnd Date
Concerto Ballroom Thu, Oct 26 2017,14:00 Thu, Oct 26 2017,18:00
Mathilde Cancet