ICESat-2 coastal and nearshore bathymetry product algorithm development

NASA’s ICESat-2 satellite launched in 2018, carrying a single instrument, the Advanced Topographic Laser Altimeter System (ATLAS). The level 1 science objectives of the mission focus primarily on cryospheric science, with specific interest in changes in our polar ice sheets, glaciers and sea ice. However, in addition to planned observations and data products for polar, land, vegetation, ocean and atmospheric surface measurements, ATLAS’s photon-counting, green-wavelength design was found to enable an impressive bathymetric measurement capability. Although most of the ICESat-2 along-track data products were developed during pre-launch studies, at that time there was not a dedicated effort placed on a generating one for bathymetry. This product’s absence requires the scientific community to develop independent, individual algorithms for bathymetric signal extraction, tailored to local or regional studies but perhaps not applicable at larger scales. Over the last few years the ICESat-2 Project Science Office has sought to address the need for coastal and nearshore bathymetry through the development of a Level 3a, along-track data product for global shallow-water bathymetry (ATL24). The ATL24 workflow embraces several independent signal extraction algorithms in a machine learning ensemble to provide robust signal extraction of the seafloor and sea surface heights despite extreme variability in environmental conditions and water quality. The ATL24 workflow also includes correction strategies for the index of refraction and uncertainty estimates. This paper explains the approach to the algorithms, the implementation of the data product, and an assessment of the accuracy to evaluate its usefulness for high-priority science and application use cases.