Data use cases

Ice caps applications | 2

2.3 Ice caps applications: Altimetry for observing polar ice caps Altimetry is one of the most powerful tools for monitoring ice sheets. The cryosphere plays an important role in moderating the global climate. Rapid changes are occurring on ice caps margins that can significantly contribute to sea level rise. Altimeter data is a powerful tool for measuring both the dynamics and mass balance of ice sheets. Moreover, altimeters also provide other parameters such as backscatter coefficient and waveform shape that give information on surface roughness and snow pack characteristics.

Data used

By giving a good overview of polar regions (-82.5°S / 82.5°N), Envisat mission is well adapted and able to accurately map 80% of Antarctica and almost all the Greenland. Envisat altimeter (RA-2) data are supplied on DVD-Roms and by FTP and can be obtained from EOHelp.
This dataset has another advantage. The Envisat GDR directly offers the opportunity to use other algorithms that are better suited for non-ocean surfaces. One of them is optimized for ice surfaces, the so-called ICE-2 retracker.
The RA-2 altimeter on Envisat platform is a dual-frequency radar operating at Ku-band (13.575 GHz) and at S-band (3.2 GHz). This dual-frequency can be used for better quantify wave penetration in snowpack and improve the knowledge of the ice sheets surface topography evolution.

Methodology

Two parameters were used to map ice sheets: the radar altimetric backscatter coefficient which corresponds to the waveform integration and gives information on surface characteristics; the leading edge width which is related to the penetration into the medium and the surface roughness.

Temporal extraction

We use data spanning the period of Summer 2005 (Envisat cycle 040).

Data editing

In the "Datasets" tab, we have selected both cycles 034 and 040 in two different datasets and named them: Dataset_cy034 and Dataset_cy040.
In the "Operations" tab, we have created a first operation for the backscatter coefficient for each Dataset_cycle. Select longitude for "X", latitude for "Y". For the "Data expression", use the difference between the two bands S-Ku: hz18_s_ice2_bscat - hz18_ku_ice2_bscat. The following selection criteria limits the backscatter coefficient boundaries to exclude the most erroneous data and applies an ocean mask: ((altim_landocean_flag > 0) && (is_bounded(0, hz18_s_ice2_bscat, 45))) && (is_bounded(0, hz18_ku_ice2_bscat, 45)). This first operation is duplicated to be applied on the second cycle but be careful to select the corresponding dataset.
In order to give you several examples, we choose to represent two different geographic resolutions for each cycle : 1/3° for cycle034 and 1° for cycle040. This is done by clicking on "Set Resolution/Filter AND selecting the "step" in X resolution and Y resolution.

The second operation is applied to the difference S-Ku band on the leading edge width: select longitude for "X", latitude for "Y". For the "Data expression", use: hz18_s_ice2_edge_width - hz18_ku_ice2_edge_width. A selection criteria masks the data over the oceans and tends to eliminated most of the bad data: ((altim_landocean_flag > 0) && (is_bounded(0, hz18_ku_ice2_edge_width, 7.7))) && (is_bounded(0, hz18_s_ice2_edge_width, 7.7)).

In the "Views" tab, select each operation to be plotted and "execute" it.