Understanding biases in ICESat-2 data due to subsurface scattering using Airborne Topographic Mapper waveform data

Abstract. The process of laser light reflecting from surfaces made of scattering materials that do not strongly absorb at the wavelength of the laser can involve reflections from hundreds or thousands of individual grains, which can introduce delays in the time between light entering and leaving the surface. These time of flight biases depend on the grain size and density of the medium, and so can result in spatially and temporally varying surface height biases estimated from NASA’s ICESat-2 (Ice Cloud, and land Elevation Satellite-2) mission. In this study, we investigate these biases using a model of subsurface scattering, altimetry measurements form NASA’s ATM (Airborne Topographic Mapping system), and grain-size estimates based on optical imagery of the ice sheet. We demonstrate that distortions in the shapes of waveforms measured using ATM are related to the optical grain size of the surface estimated using optical reflectance measurements, and argue that they can be used to estimate an effective grain radius for the surface. Using this effective grain radius as a proxy for the severity of subsurface scattering, we use our model with grain-size estimates from optical imagery to simulate corrections for biases in ICESat-2 data due to subsurface scattering, and demonstrate that on the basis of large-scale averages, the corrections calculated based on the optical imagery match the biases in the data. This work demonstrates that waveform-based altimetry data has the potential to measure the optical properties of granular surfaces, and that corrections based on optical grain-size estimates have the potential to correct for subsurface-scattering biases in ICESat-2 data.