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.

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.

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.

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.

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.

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.

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.

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.