Uncertainty of ICESat-2 ATL06- and ATL08-derived snow depths for glacierized and vegetated mountain regions

Seasonal snow melt dominates the hydrologic budget across a large portion of globe. Snow accumulation and vary over broad range spatial scales, preventing accurate extrapolation sparse in situ observations to watershed scales. The lidar onboard Ice, Cloud, land Elevation, Satellite (ICESat-2) was designed for precise mapping ice sheets sea ice, here we assess feasibility depth-mapping using ICESat-2 data more complex rugged mountain landscapes. We explore utility ATL08 Land Vegetation Height ATL06 Ice differencing from reference elevation datasets two end member study sites. analyze ∼3 years Reynolds Creek Experimental Watershed Idaho's Owyhee Mountains Wolverine Glacier southcentral Alaska's Kenai Mountains. Our analysis reveals decimeter-scale uncertainties derived depth glacier mass balance at scale. Both accuracy precision decrease as slope increases: magnitudes median absolute deviation errors (MAD) ∼0.2 m slopes <5° >1 >20°. For glacierized regions, failure account intra- inter-annual evolution surface elevations can strongly bias elevations, resulting under-estimation gradient with elevation. Based on these results, conclude that are best suited characterization watershed-scale gradients relatively shallow thick snowpacks. In residual-derived transects provide valuable scale constraints terrain parameter- model-derived estimates melt.