Statistical Model of Subsurface Scattering Bias in Icesat‐2's ATL06 Product

Authors

• Thilini Bamunu Arachchige, University of North Dakota
• Kelly E. Gleason, Portland State UniversityFollow
• Jonathan C. Ryan, Duke University
• Markus Allgaier, Department of Physics and Astrophysics University of North Dakota Grand Forks ND USA

Sponsor

We thank Anthony J. Martino and Almut M. Pingel of NASA for providing ATLAS linear impulse response functions, and Benjamin Smith at the Applied Physics Laboratory for providing ideal ATLAS photon count numbers. This work was supported by NASA award No 80NSSC25K7743.

Published In

Earth and Space Science

Document Type

Article

Publication Date

8-26-2026

Subjects

Subsurface scattering -- Monte Carlo Radiative Transfer (MCRT)

Abstract

ICESat‐2 uses visible laser pulses and photon‐counting detectors to range the Earth's surface, providing precision altimetry for measuring ice sheet elevation change. However, since water ice is transparent to visible light, the photon returns recorded by ICESat‐2's ATLAS instrument may originate from subsurface scattering inside the snow or glacier ice volume, making the surface appear lower than it is. Here, we develop a Monte Carlo Radiative Transfer model to characterize the potential bias caused by subsurface scattering in snow and ice. Our model allows us to study the subsurface scattering bias in relation to photon number, scattering coefficient, and slope angle. We find centimeter‐scale bias caused by subsurface scattering that is statistically significant for strong returns on firn and weak returns on bare glacier ice at low slope angles, and for strong returns on glacier ice at moderate slope angles. We find that the bias is amplified by slope angle, but can be accounted for with the existing correction employed in the ATL06 product. Most of the Greenland Ice Sheet is affected, but the bias is not expected to manifest in elevation change products and derived mass balance, as it would cancel out. We conclude that the modeled subsurface scattering signature in the ICESat‐2 data offers future opportunities for investigating scattering coefficients of glacier ice.

Rights

Copyright (c) 2026 The Authors

This work is licensed under a Creative Commons Attribution 4.0 International License.

Locate the Document

https://doi.org/10.1029/2026EA005083

DOI

10.1029/2026EA005083

Persistent Identifier

https://archives.pdx.edu/ds/psu/45092

Citation Details

Bamunu Arachchige, T., Gleason, K. E., Ryan, J. C., & Allgaier, M. (2026). Statistical Model of Subsurface Scattering Bias in ICESat‐2’s ATL06 Product. Earth and Space Science, 13(8). Portico. https://doi.org/10.1029/2026ea005083