Estimating differential penetration of green (532 nm) laser light over sea ice with NASA's Airborne Topographic Mapper: observations and models

• Published in: The Cryosphere
• Main Authors: Studinger, Michael, Smith, Benjamin E., Kurtz, Nathan, Petty, Alek, Sutterley, Tyler, Tilling, Rachel
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2024
• Subjects: article; Verlagsveröffentlichung; Airborne Topographic Mapper; Sea ice; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-18-2625-2024; https://noa.gwlb.de/receive/cop_mods_00073996; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00072129/tc-18-2625-2024.pdf; https://tc.copernicus.org/articles/18/2625/2024/tc-18-2625-2024.pdf

Differential penetration of green laser light into snow and ice has long been considered a possible cause of range and thus elevation bias in laser altimeters. Over snow, ice, and water, green photons can penetrate the surface and experience multiple scattering events in the subsurface volume before being scattered back to the surface and subsequently the instrument's detector, therefore biasing the range of the measurement. Newly formed sea ice adjacent to open-water leads provides an opportunity to identify differential penetration without the need for an absolute reference surface or dual-color lidar data. We use co-located, coincident high-resolution natural-color imagery and airborne lidar data to identify surface and ice types and evaluate elevation differences between those surfaces. The lidar data reveals that apparent elevations of thin ice and finger-rafted thin ice can be several tens of centimeters below the water surface of surrounding leads, but not over dry snow. These lower elevations coincide with broadening of the laser pulse, suggesting that subsurface volume scattering is causing the pulse broadening and elevation shift. To complement our analysis of pulse shapes and help interpret the physical mechanism behind the observed elevation biases, we match the waveform shapes with a model of scattering of light in snow and ice that predicts the shape of lidar waveforms reflecting from snow and ice surfaces based on the shape of the transmitted pulse, the surface roughness, and the optical scattering properties of the medium. We parameterize the scattering in our model based on the scattering length Lscat, the mean distance a photon travels between isotropic scattering events. The largest scattering lengths are found for thin ice that exhibits the largest negative elevation biases, where scattering lengths of several centimeters allow photons to build up considerable range biases over multiple scattering events, indicating that biased elevations exist in lower-level Airborne Topographic Mapper (ATM) ...