Reconstructing Glacier Dynamics in Complex Terrain with ICESat-2 and Gaussian Process Interpolation
- 1Friedrich-Alexander-Universität Erlangen-Nürnberg (Erlangen, Germany)
Abstract
We apply Gaussian Process Regression (GPR) to ICESat-2 along-track height change data to generate spatially continuous glacier height change fields across two glaciated regions with complex topography and dynamic behaviour: Larsen-B (Antarctic Peninsula) and central Southern Svalbard. For Larsen-B, GPR-derived average height change rates from 2021–2024 are −0.61 ± 0.02 m a ⁻¹ , corresponding to a volume loss of 4.55 ± 0.17 km ³ a ⁻¹ , similar to independent estimates from TanDEM-X. In Svalbard, we observe widespread average thinning (−1.62 ± 0.03 m a ⁻¹ ) and detect clear signals of surging glaciers. GPR's multi-dimensional, uncertainty-aware framework enables accurate interpolation across data gaps and supports the detection of localized dynamic events, such as surges. Sensitivity tests show that interpolation errors increase with gap size, slope, and extrapolation distance. Our findings demonstrate that GPR is well-suited for enhancing the spatial and temporal resolution of altimetry-based glacier monitoring, enabling improved estimates of height and volume change while reconstructing spatially localized phenomena such as surge activity and other transient glacier dynamics.
Versions
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BibTeX
@article{seehaus2026reconstructing,
title = {{Reconstructing Glacier Dynamics in Complex Terrain with ICESat-2 and Gaussian Process Interpolation}},
author = {Thorsten Seehaus and Alex S. Gardner and Johan Nilsson},
journal = {The Cryosphere},
year = {2026},
month = oct,
doi = {10.5194/tc-20-6107-2026},
url = {https://doi.org/10.5194/tc-20-6107-2026},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Reconstructing Glacier Dynamics in Complex Terrain with ICESat-2 and Gaussian Process Interpolation
AU - Thorsten Seehaus
AU - Alex S. Gardner
AU - Johan Nilsson
PY - 2026
DA - 2026/10/26
JO - The Cryosphere
DO - 10.5194/tc-20-6107-2026
UR - https://doi.org/10.5194/tc-20-6107-2026
AB - We apply Gaussian Process Regression (GPR) to ICESat-2 along-track height change data to generate spatially continuous glacier height change fields across two glaciated regions with complex topography and dynamic behaviour: Larsen-B (Antarctic Peninsula) and central Southern Svalbard. For Larsen-B, GPR-derived average height change rates from 2021–2024 are −0.61 ± 0.02 m a ⁻¹ , corresponding to a volume loss of 4.55 ± 0.17 km ³ a ⁻¹ , similar to independent estimates from TanDEM-X. In Svalbard, we observe widespread average thinning (−1.62 ± 0.03 m a ⁻¹ ) and detect clear signals of surging glaciers. GPR's multi-dimensional, uncertainty-aware framework enables accurate interpolation across data gaps and supports the detection of localized dynamic events, such as surges. Sensitivity tests show that interpolation errors increase with gap size, slope, and extrapolation distance. Our findings demonstrate that GPR is well-suited for enhancing the spatial and temporal resolution of altimetry-based glacier monitoring, enabling improved estimates of height and volume change while reconstructing spatially localized phenomena such as surge activity and other transient glacier dynamics.
SN - 1994-0424
ER -