Regional Assessments of Surface Ice Elevations from Swath-Processed CryoSat-2 SARIn Data

Abstract

The Arctic responds rapidly to climate change, and the melting of land ice is a major contributor to the observed present-day sea-level rise. The coastal regions of these ice-covered areas are showing the most dramatic changes in the form of widespread thinning. Therefore, it is vital to improve the monitoring of these areas to help us better understand their contribution to present-day sea levels. In this study, we derive ice-surface elevations from the swath processing of CryoSat-2 SARIn data, and evaluate the results in several Arctic regions. In contrast to the conventional retracking of radar data, swath processing greatly enhances spatial coverage as it uses the majority of information in the radar waveform to create a swath of elevation measurements. However, detailed validation procedures for swath-processed data are important to assess the performance of the method. Therefore, a range of validation activities were carried out to evaluate the performance of the swath processor in four different regions in the Arctic. We assessed accuracy by investigating both intramission crossover elevation differences, and comparisons to independent elevation data. The validation data consisted of both air- and spaceborne laser altimetry, and airborne X-band radar data. There were varying elevation biases between CryoSat-2 and the validation datasets. The best agreement was found for CryoSat-2 and ICESat-2 over the Helheim region in June 2019. To test the stability of the swath processor, we applied two different coherence thresholds. The number of data points was increased by approximately 25% when decreasing the coherence threshold in the processor from 0.8 to 0.6. However, depending on the region, this came with the cost of an increase of 33–65% in standard deviation of the intramission differences. Our study highlights the importance of selecting an appropriate coherence threshold for the swath processor. Coherence threshold should be chosen on a case-specific basis depending on the need for enhanced spatial coverage or accuracy.

Systematic Errors Observed in CryoSat-2 Elevation Swaths on Mountain Glaciers and Their Implications

“…Finally, we discuss our findings in light of performance analysis and uncertainty treatment in earlier research. In line with our findings, Andersen et al [24] report standard deviations from 6 to 17 m for CryoSat-2 swath elevations compared to air-and spaceborne laser altimetry, and airborne X-band radar altimetry data. Previous studies, which investigated surface elevation change rates, usually did not consider the uncertainties of CryoSat-2 swath data directly.…”

Lake Ice Thickness Retrieval Method with ICESat-2-Assisted CyroSat-2 Echo Peak Selection

“…The primary payload for altimetry carried by a satellite is SAR Interferometric Radar Altimeter (SIRAL). This radar altimeter has three measurement modes: low-resolution mode (LRM), synthetic aperture radar (SAR), and state-of-the-art dual-channel synthetic aperture interferometric radar (SARIn) [21]. Within the GBL region, CryoSat-2 operates in SARIn mode, in which the processor avoids the effects of terrain relief in the along-track direction with a footprint size of approximately 0.5 km 2 .…”

“…The track of the ICESat-2 data used in this study is shown in Figure 1 CryoSat-2 is a radar altimetry satellite launched by the ESA in Apri primary payload for altimetry carried by a satellite is SAR Interferometric R (SIRAL). This radar altimeter has three measurement modes: low-resolutio synthetic aperture radar (SAR), and state-of-the-art dual-channel syntheti ferometric radar (SARIn) [21]. Within the GBL region, CryoSat-2 operates in which the processor avoids the effects of terrain relief in the along-trac a footprint size of approximately 0.5 km 2 .…”

Improved monitoring of subglacial lake activity in Greenland

“…Evans and Smith (1970) were the first to detect a subglacial lake under the AIS by RES. RES can penetrate the ice sheet and map the bedrock topography, where a strong, flat reflection indicates the presence of basal water (Bingham and Siegert, 2007;Tulaczyk and Foley, 2020). RES has been used to detect and map numerous subglacial lakes under the ice sheets (Wright and Siegert, 2012;Siegert et al, 2016;Bowling et al, 2019).…”