Communication

PhD thesis: Image de-noising techniques to improve the observability of oceanic fine-scale dynamics by the swot mission

 

 

 

 

 

Esporles, September 28, 2020. Laura Gómez-Navarro has defended her doctoral thesis supervised by Emmanuel Cosme from L'Institut des Géosciences de l'Environnement (IGE, Grenoble), Ananda Pascual from IMEDEA (CSIC-UIB), and Julien Le Sommer from IGE. The event took place on September 29 in Grenoble and partially hold via Zoom.

 

 

Sea Surface Height (SSH) observations describing scales in the range 10 - 100 km are crucial to better understand energy transfers across scales in the opn ocean and to quantify vertical exchanges of heat and biogeochemical tracers.

 

 

The Surface Water Ocean Topography (SWOT) mission is a new wide-swath altimetric satellite which is planned to be launched in 2022. SWOT will provide information on SSH at a kilometric resolution, but uncertainties due to various sources of errors will challenge our capacity to extract the physical signal of structures below a few tens of kilometers. Filtering SWOT noise and errors is a key step towards an optimal interpretation of the data.

 


The aim of this study is to explore image de-noising techniques to assess the capabilities of the future SWOT data to resolve the oceanic fine scales. Pseudo-SWOT data are generated with the SWOT simulator for Ocean Science, which uses as input the SSH outputs from high-resolution Ocean General Circulation Models (OGCMs). Several de-noising techniques are tested, to find the one that renders the most accurate SSH and its derivatives fields while preserving the magnitude and shape of the oceanic features present. The techniques are evaluated based on the root mean square error, spectra and other diagnostics.

 

 

Image: Artistic image of the SWOT satellite (https://swot.jpl.nasa.gov/) (Credits: NASA)

 

 


 

Date and time: tuesday, september 29, 01:40 PM Paris

Place: Zoom Meeting:

Join: https://univ-grenoble-alpes-fr.zoom.us/j/96509789592?pwd=MFRUd3dVQVZNc1czRjZhMzNGU0Uvdz09

Meeting ID: 965 0978 9592

Passcode: 1FgJvE

 


Source: IMEDEA (UIB-CSIC)