Study of the Penetration Bias of ENVISAT Altimeter Observations over Antarctica in Comparison to ICESat Observations

Michel, Aurélie; Flament, Thomas; Rémy, Frédérique

doi:10.3390/rs6109412

Cited by 17 publications

(12 citation statements)

References 38 publications

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“…Wingham et al (1998), Davis and Ferguson (2004), McMillan et al (2014) and Zwally et al (2015) apply a linear regression using the backscattered power. Flament and Rémy (2012), Michel et al (2014) and Simonsen and Sørensen (2017) use two additional waveform shape parameters, obtained from functional fit retrackers. Nilsson et al (2016) showed that a low threshold retracker mitigates the need for a complex waveform shape correction.…”

Section: Repeat-track Parameter Fitmentioning

confidence: 99%

“…Rignot (2006) showed that the flow velocity of these glaciers, which are www.the-cryosphere.net/13/427/2019/ The Cryosphere, 13, 427-449, 2019 grounded well below sea level, was above the balance velocity for many years. Miles et al (2018) analyzed satellite images since 1973 and found that the flow velocity of Cook Ice Shelf glaciers has significantly accelerated since then. In contrast, the western sector of the EAIS (Coats Land, Dronning Maud Land and Enderby Land; basins J"-B) shows thickening over the last 25 years at rates of up to a decimeter per year.…”

Section: Surface Elevation Changesmentioning

confidence: 99%

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Four decades of Antarctic surface elevation changes from multi-mission satellite altimetry

et al. 2019

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We developed a multi-mission satellite altimetry analysis over the Antarctic Ice Sheet which comprises Seasat, Geosat, ERS-1, ERS-2, Envisat, ICESat and CryoSat-2. After a consistent reprocessing and a stepwise calibration of the inter-mission offsets, we obtained monthly grids of multi-mission surface elevation change (SEC) with respect to the reference epoch 09/2010 (in the format of month/year) from 1978 to 2017. A validation with independent elevation changes from in situ and airborne observations as well as a comparison with a firn model proves that the different missions and observation modes have been successfully combined to a seamless multi-mission time series. For coastal East Antarctica, even Seasat and Geosat provide reliable information and, hence, allow for the analysis of four decades of elevation changes. The spatial and temporal resolution of our result allows for the identification of when and where significant changes in elevation occurred. These time series add detailed information to the evolution of surface elevation in such key regions as Pine Island Glacier, Totten Glacier, Dronning Maud Land or Lake Vostok. After applying a density mask, we calculated time series of mass changes and found that the Antarctic Ice Sheet north of 81.5 • S was losing mass at an average rate of −85 ± 16 Gt yr −1 between 1992 and 2017, which accelerated to −137 ± 25 Gt yr −1 after 2010.

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Section: Repeat-track Parameter Fitmentioning

confidence: 99%

Section: Surface Elevation Changesmentioning

confidence: 99%

Four decades of Antarctic surface elevation changes from multi-mission satellite altimetry

et al. 2019

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“…However, altimetric observations are affected by several errors: error due to atmospheric or ionospheric propagations, slope error and error due to the radar wave penetration into the cold and dry snow (Ridley and Partington, 1988). The first two errors are usually corrected with good accuracy (Remy et al, 2012;Nilsson et al, 2016), while the last one is the most critical and the most challenging problem to tackle (Remy et al, 2012) as it results in an overestimation of the observed distance between the satellite and the target, leading to a negative bias in the surface elevation estimation. The magnitude of the penetration error on the estimated surface elevation is between a few tens of centimeters and few meters (Remy and Parouty, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…The magnitude of the penetration error on the estimated surface elevation is between a few tens of centimeters and few meters (Remy and Parouty, 2009). For instance, Michel et al (2014) have found a surface elevation difference of −0.5 m between ENVIronment SATellite (EN-VISAT) and ICESat crossover points over Antarctica. Authors relate this negative bias to the difference in the penetration depth between the radar altimeter wave that penetrates within the snowpack and the laser altimeter beam that does not penetrate within the snowpack.…”

Section: Introductionmentioning

confidence: 99%

Seasonal variations of the backscattering coefficient measured by radar altimeters over the Antarctic Ice Sheet

2018

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Abstract. Spaceborne radar altimeters are a valuable tool for observing the Antarctic Ice Sheet. The radar wave interaction with the snow provides information on both the surface and the subsurface of the snowpack due to its dependence on the snow properties. However, the penetration of the radar wave within the snowpack also induces a negative bias on the estimated surface elevation. Empirical corrections of this space- and time-varying bias are usually based on the backscattering coefficient variability. We investigate the spatial and seasonal variations of the backscattering coefficient at the S (3.2 GHz ∼ 9.4 cm), Ku (13.6 GHz ∼ 2.3 cm) and Ka (37 GHz ∼ 0.8 cm) bands. We identified that the backscattering coefficient at Ku band reaches a maximum in winter in part of the continent (Region 1) and in the summer in the remaining (Region 2), while the evolution at other frequencies is relatively uniform over the whole continent. To explain this contrasting behavior between frequencies and between regions, we studied the sensitivity of the backscattering coefficient at three frequencies to several parameters (surface snow density, snow temperature and snow grain size) using an electromagnetic model. The results show that the seasonal cycle of the backscattering coefficient at Ka frequency is dominated by the volume echo and is mainly driven by snow temperature evolution everywhere. In contrast, at S band, the cycle is dominated by the surface echo. At Ku band, the seasonal cycle is dominated by the volume echo in Region 1 and by the surface echo in Region 2. This investigation provides new information on the seasonal dynamics of the Antarctic Ice Sheet surface and provides new clues to build more accurate corrections of the radar altimeter surface elevation signal in the future.

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“…Since 1991, Greenland and Antarctica to 81.5°south had been covered continuously by the European Space Agency (ESA) radar altimeters on the European Remote Sensing Satellites (Fé mé nias, P. et al, 1993;Anita C. Brenner et al, 2007; Auré lie Michel et al, 2014). The ENVISAT was launched in 2002 by the ESA to link up with ERS-1 and ERS-2.…”

Section: Introductionmentioning

confidence: 99%

Precision and Deviation Comparison Between Icesat and Envisat in Typical Ice Gaining and Losing Regions of Antarctica

Chen

Xie

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VIII, WG VIII/6 KEY WORDS: ICESat, Envisat , precision , deviation, Antarctica ABSTRACT:This paper analyzes the precision and deviation of elevations acquired from Envisat and The Ice, Cloud and Land Elevation Satellite (ICESat) over typical ice gaining and losing regions, i.e. Lambert-Amery System (LAS) in east Antarctica, and Amundsen Sea Sector (ASS) in west Antarctica, during the same period from 2003 to 2008. We used GLA12 dataset of ICESat and Level 2 data of Envisat. Data preprocessing includes data filtering, projection transformation and track classification. Meanwhile, the slope correction is applied to Envisat data and saturation correction for ICESat data. Then the crossover analysis was used to obtain the crossing points of the ICESat tracks, Envisat tracks and ICESat-Envisat tracks separately. The two tracks we chose for cross-over analysis should be in the same campaign for ICESat (within 33 days) or the same cycle for Envisat (within 35 days).The standard deviation of a set of elevation residuals at time-coincident crossovers is calculated as the precision of each satellite while the mean value is calculated as the deviation of ICESat-Envisat. Generally, the ICESat laser altimeter gets a better precision than the Envisat radar altimeter. For Amundsen Sea Sector, the ICESat precision is found to vary from 8.9 cm to 17 cm and the Envisat precision varies from 0.81 m to 1.57 m. For LAS area, the ICESat precision is found to vary from 6.7 cm to 14.3 cm and the Envisat precision varies from 0.46 m to 0.81 m. Comparison result between Envisat and ICESat elevations shows a mean difference of 0.43 ±7.14 m for Amundsen Sea Sector and 0.53 ± 1.23m over LAS.

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Study of the Penetration Bias of ENVISAT Altimeter Observations over Antarctica in Comparison to ICESat Observations

Cited by 17 publications

References 38 publications

Four decades of Antarctic surface elevation changes from multi-mission satellite altimetry

Four decades of Antarctic surface elevation changes from multi-mission satellite altimetry

Seasonal variations of the backscattering coefficient measured by radar altimeters over the Antarctic Ice Sheet

Precision and Deviation Comparison Between Icesat and Envisat in Typical Ice Gaining and Losing Regions of Antarctica

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