Here are some asked question about altimetry, its applications and the Broadview Radar Altimetry Toolbox.

For any question about specific data, please contact the data distribution centre.

Applications

Sea state influence the measurement of the satellite-sea surface range because the altimeter is sensitive to
sea surface elements perpendicular to the target line. These elements are more frequently in the wave trough than
in the crest, so the mean height of these elements doesn’t match the geometric mean height of all sea
surface elements that make the mean sea level (electromagnetic bias). In this way, the altimetric-measured mean
is shifted toward wave trough, and moreover if waves are high.
Dynamic topography (or absolute sea surface height) is the sea surface height with respect to geoid. It can
be computed as the sum of sea level anomalies (i.e. the variable part of sea surface height) and a mean
dynamic topography.

Absolute Dynamic Topography = Sea Level Anomalies + Mean Dynamic Topography = Sea Surface Height – geoid

 

Altimetry

You can find an explanation of how altimetry works, in the Altimetry Tutorial section of this website.
Sea state influence the measurement of the satellite-sea surface range because the altimeter is sensitive to
sea surface elements perpendicular to the target line. These elements are more frequently in the wave trough than
in the crest, so the mean height of these elements doesn’t match the geometric mean height of all sea
surface elements that make the mean sea level (electromagnetic bias). In this way, the altimetric-measured mean
is shifted toward wave trough, and moreover if waves are high.
Using Topex/Poseidon or Jason-1 data near Antarctica is not easy, because of coasts and sea-ice. Moreover,
Their orbit passes between 66°S and 66°N (ERS-1 and 2 between 82°S and 82°N). However, ERS-1 & 2 and
Envisat give data up to 82°S.
The brightness temperature of a surface is equal to the product of the emissivity of this surface by its
physical temperature. The radiation measured by the radiometer depends on the ocean surface emissivity,
its physical temperature and water vapour and cloud absorption in the atmosphere. If you want to know precisely
the atmospheric water vapour contents, you have to subtract surface and cloud contribution from the signal
received by the radiometer. That’s why several frequencies (3) are used, each one being more sensitive than
the other to one of these contributions. By combining measurements done at each frequencies, you can extract
the water vapour signal.

 

Toolbox

Version 2 and over include an “export” button in the Operations tab. It will enable you to dump your chosen fields
in an txt file.
For now, derivatives functions have not be implemented in the toolbox
Altimetry satellites repeat their ground track very precisely, but NOT exactly (to within 1 km, typically). So, from
one cycle to the other, the location in longitude and/or latitude of a measure varies. If you really want to
average those, you have to round the latitude (or longitude) field in X (use the rnd(field,nb of digit) function).
More broadly, whenever you want to compare two along-track data in a Y=F(X) Operation, rounding the field used
as X down to the number of significant digits (e.g. “rnd(lat,4)”) may be interesting: Double Real formats may lead
to slightly different values when the computer process them (you will have e.g. 6.54820000001 or 6.54819999999
for the same number (6.5482), which is enough to consider the locations as different)
The question is different with maps, since the processing is automatically binning the data using the
defined resolution.