EO Sign In Authentication (Open)

1. Go to the Dissemination Service
2. Find the product you want using the search options
3. Register or log in to EO Sign In
4. Download (via HTTPS or FTPS)

The dissemination service provides data generated within the ESA FDR4ALT project.

The data is collection based and allows data browsing and download via treeview, filename or advanced catalogue search.

Data download is available via HTTPS, including bulk download functionality. ESA internal users can use their ESAAD account to access the HTTPS Dissemination Service.

Access to ftps://hm-lbr-ds.eo.esa.int is available via common FTP clients using “implicit FTP over TLS” and your own EO Sign In credentials. For internal ESA users the ESAAD account cannot be used for FTP access.

New users can register an account on EO Sign In. For further information about the EO Sign In Service you can visit TellUs.

Should you need support to access the data, please contact EOHelp.

World Wide

This is the Ocean and Coastal Topography Thematic Data Product (TDP) V1 resulting from the ESA FDR4ALT project and containing improved sea surface height anomaly data records both at 1 Hz and 20 Hz resolution to address climate and/or coastal areas studies. The collection covers data for the ERS-1, ERS-2 and Envisat missions. Note that a dedicated processing to coastal zones has been applied for coastal distances below 200 km.

Compared to existing datasets, the Ocean and Coastal Topography TDP demonstrates notable improvements in several aspects:

• Up-to-date orbit and geophysical corrections applied
• Adaptive retracker for Envisat

The FDR4ALT products are available in NetCDF format. Free standard tools for reading NetCDF data can be used.
Information for expert altimetry users is also available in a dedicated NetCDF group within the products.

Please consult the FDR4ALT Product User Guide before using the data.

The FDR4ALT datasets represent the new reference data for the ERS/Envisat altimetry missions, superseding any previous mission data. Users are strongly encouraged to make use of these datasets for optimal results.