Sensitivity of glacier elevation analysis and numerical modeling to CryoSat-2 SIRAL retracking techniques

Trantow, T.; Herzfeld, U. C.; Helm, Veit; Nilsson, Johan

doi:10.1016/j.cageo.2020.104610

Cited by 5 publications

(7 citation statements)

References 67 publications

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“…More specifically, the Summer 2016 ice‐surface data is attained from a CryoSat‐2 processing (retracking) technique that combines swath‐processing with the Threshold First Maximum Retracking Algorithm (TFMRA) (Helm et al., 2014). Swath‐processing provides over 150 times more height estimates than traditional retracking methods, and provides the best DEM available for numerical modeling (Trantow et al., 2020). The TFMRA‐swath data is based on the Baseline‐C version of the CryoSat‐2 L1B data (Bouffard, 2015), as this was the latest data version at the time of analysis.…”

Section: Data and Observationsmentioning

confidence: 99%

“…Furthermore, the influence of CryoSat‐2 data processing techniques on elevation analysis and numerical modeling results is covered in Trantow et al. (2020).…”

Section: Data and Observationsmentioning

confidence: 99%

“…This data processing pipeline is laid out fully in Trantow and Herzfeld (2016), while Herzfeld et al (1993) introduces the method of Advanced Kriging which builds upon the Ordinary Kriging method to better interpolate elevations on a glacier surface, particularly one that is highly-crevassed. Furthermore, the influence of CryoSat-2 data processing techniques on elevation analysis and numerical modeling results is covered in Trantow et al (2020).…”

Section: Surface and Bedrock Digital Elevation Maps (Dems)mentioning

confidence: 99%

“…Figure 7a shows modeled quiescent elevation change by differencing the initial surface elevation with the surface elevation after 20 years of evolution. The initial ice surface is taken as the glacier surface after 50 time steps of free evolution in order to reduce any elevation‐change signals arising from errors in the input surface DEM (Trantow et al., 2020).…”

Section: The Quiescent Phasementioning

confidence: 99%

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Evolution of a Surge Cycle of the Bering‐Bagley Glacier System From Observations and Numerical Modeling

Trantow,

Herzfeld

2024

JGR Earth Surface

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The Bering‐Bagley Glacier System (BBGS), Alaska, Earth's largest temperate surging glacier, surged in 2008–2013. We use numerical modeling and satellite observations to investigate how surging in a large and complex glacier system differs from surging in smaller glaciers for which our current understanding of the surge phenomenon is based. With numerical simulations of a long quiescent phase and a short surge phase in the BBGS, we show that surging is more spatiotemporally complex in larger glaciers with multiple reservoir areas forming during quiescence which interact in a cascading manner when ice accelerates during the surge phase. For each phase, we analyze the simulated elevation‐change and ice‐velocity pattern, infer information on the evolving basal drainage system through hydropotential analysis, and supplement these findings with observational data such as CryoSat‐2 digital elevation maps. During the quiescent simulation, water drainage paths become increasingly lateral and hydropotential wells form indicating an expanding storage capacity of subglacial water. These results are attributed to local bedrock topography characterized by large subglacial ridges that dam the down‐glacier flow of ice and water. In the surge simulation, we model surge evolution through Bering Glacier's trunk by imposing a basal friction representation that mimics a propagating surge wave. As the surge progresses, drainage efficiency further degrades in the active surging‐zone from its already inefficient, end‐of‐quiescence state. Results from this study improve our knowledge of surging in large and complex systems which generalizes to glacial accelerations observed in outlet glaciers of Greenland, thus reducing uncertainty in modeling sea‐level rise.

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Section: Data and Observationsmentioning

confidence: 99%

“…Furthermore, the influence of CryoSat‐2 data processing techniques on elevation analysis and numerical modeling results is covered in Trantow et al. (2020).…”

Section: Data and Observationsmentioning

confidence: 99%

Section: Surface and Bedrock Digital Elevation Maps (Dems)mentioning

confidence: 99%

Section: The Quiescent Phasementioning

confidence: 99%

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Evolution of a Surge Cycle of the Bering‐Bagley Glacier System From Observations and Numerical Modeling

Trantow,

Herzfeld

2024

JGR Earth Surface

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“…Heights derived from non-official processing chain [9,10] also provides potential in ice-sheet application. The old versions of the CS2 LRM/SIN product (BB [4,11] or BC [12]) were assessed completely in previous third-party studies. The up-to-date version of the CS2 BD LRM product was limitedly assessed by a third-party study, which was conducted based on singlesource traverse GNSS data over the flat interior of AIS.…”

Section: Introductionmentioning

confidence: 99%

Assessment of CryoSat-2 Baseline-D Height Product by GNSS and ICESat-2 in Lambert-Amery System, East Antarctica

Hai

Cheng

Xie

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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CryoSat-2 repeatedly collects dense radar altimetry footprints covering high latitudes of the polar ice sheets for over 10 years. The Baseline-D height product of CryoSat-2 was recently upgraded and released in 2019. Based on the internal or locally external evaluation of CryoSat-2 Baseline-D ice heights, we extended the validation both heterogeneously and spatially to accomplish a comprehensive assessment. Firstly, reliable ice surface GNSS point solutions along the 36th Chinese National Antarctic Research Expedition traverse functioned as a height reference for comparison with the CryoSat-2 SAR synthetic aperture radar interferometric mode (SIN) data. Secondly, the Land Ice Along-Track Height product over Lambert-Amery System (LAS) from ICESat-2, was also applied to validate CryoSat-2 SIN and Low-Resolution Mode (LRM) data. As the results indicate, the SIN height accuracy is evaluated to be -1.68 m ± 2.35 m (slope < 0.65°) along the traverse and -0.96 ± 1.95 m (slope < 0.95° & roughness < 3 m) over the margin of LAS. The LRM height accuracy is evaluated to be -0.13 ± 0.46 m (slope < 0.1° & roughness < 1 m) over the interior of LAS. The standard deviation (SD) of the height differences degrades linearly against the limited growth of the terrain slope/roughness at the confidence level of 99%. It is worth noting that the spatially heterogeneous pattern of height differences is correlated with surface topography variations. This study should imply the potential to improve the estimation of mass balance and its uncertainty of polar ice sheets based on radar altimetry data.

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Reconciled estimation of Antarctic ice sheet mass balance and contribution to global sea level change from 1996 to 2021

Li,

Hai

et al. 2024

Sci. China Earth Sci.

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The Antarctic Ice Sheet (AIS) has been losing ice mass and contributing to global sea level rise (GSLR). Given its mass that is enough to cause ∼58 m of GSLR, accurate estimation of mass balance trend is critical for AIS mass loss monitoring and sea level rise forecasting. Here, we present an improved approach to reconciled solutions of mass balance in AIS and its regions from multiple contributing solutions using the input-out, altimetric, and gravimetric methods. In comparison to previous methods, such as IMBIE 2018, this approach utilizes an adaptive data aggregation window to handle the heterogeneity of the contributing solutions, including the number of solutions, temporal distributions, uncertainties, and estimation techniques. We improved the regression-based method by using a two-step procedure that establishes ensembled solutions within each method (input-output, altimetry, or gravimetry) and then estimates the method-independent reconciled solutions. For the first time, 16 contributing solutions from 8 Chinese institutions are used to estimate the reconciled mass balance of AIS and its regions from 1996 to 2021. Our results show that AIS has lost a total ice mass of ∼3213±253 Gt during the period, an equivalent of ∼8.9±0.7 mm of GSLR. There is a sustained mass loss acceleration since 2006, from 88.1±3.6 Gt yr−1 during 1996–2005 to 130.7±8.4 Gt yr−1 during 2006–2013 and further to 157.0±9.0 Gt yr−1 during 2014–2021. The mass loss signal in the West Antarctica and Antarctic Peninsula is dominant and clearly presented in the reconciled estimation and contributing solutions, regardless of estimation methods used and fluctuation of surface mass balance. Uncertainty and challenges remain in mass balance estimation in East Antarctica. This reconciled estimation approach can be extended and applied for improved mass balance estimation in the Greenland Ice Sheet and mountain glacier regions.

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Sensitivity of glacier elevation analysis and numerical modeling to CryoSat-2 SIRAL retracking techniques

Cited by 5 publications

References 67 publications

Evolution of a Surge Cycle of the Bering‐Bagley Glacier System From Observations and Numerical Modeling

Evolution of a Surge Cycle of the Bering‐Bagley Glacier System From Observations and Numerical Modeling

Assessment of CryoSat-2 Baseline-D Height Product by GNSS and ICESat-2 in Lambert-Amery System, East Antarctica

Reconciled estimation of Antarctic ice sheet mass balance and contribution to global sea level change from 1996 to 2021

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