Controls on Accuracy of Snow Depth Estimates from ICESat-2 in Alpine Regions Across the Continental United States

Quantification of seasonal snow depth, density, and water equivalent is an ongoing challenge for snow research and watershed management. Snow distribution is controlled by numerous factors including wind-snow interactions, terrain, and orographic precipitation patterns creating a dynamic snowpack where snow depths can vary by orders of magnitude over ranges of 10s to 100s of meters. Satellite Lidar can expand snow observation capabilities, providing repeat observations throughout the snow accumulation and melt seasons that can improve estimates of snowpack evolution as we gain capacity to interpret these observations.

This presentation evaluates the potential of the ICESat-2 satellite to provide snow depth estimates in alpine regions. Our objective is to develop a general method to produce snow depth maps from ICESat-2 elevations in any watershed where a high-resolution snow-free digital elevation model (DEM) is available. Since ICESat-2 tracks do not regularly perfectly repeat in the mid-latitudes, independent snow-free reference DEMs are required to calculate snow depths from ICESat-2. The rugged and often densely vegetated terrain of alpine watersheds present many challenges for snow mapping with ICESat-2 data. Dense vegetation results in sparse ground returns and rugged terrain can have dramatic elevation and aspect changes within a 40-100 m spatial-averaging window. Preliminary snow depth mapping with ICESat-2 also shows that accuracy of ICESat-2 elevations are slope dependent. Here we describe the effects of slope-dependent bias correction, reference DEM kernel-weighting, and variable window size and surface-finding approaches (using the ICESat-2 SlideRule Python client) on ICESat-2 snow depth estimates. Since our uncertainty estimates are obtained for diverse alpine watersheds in the Continental United States, we conclude that ICESat-2 can be used to map large-scale variations in snow depth with sub-meter accuracy in a variety of alpine terrains.