Recent studies show that the Ice, Clouds, and Land Elevation Satellite-2 (ICESat-2) can achieve decimeter-level accuracy over forested and mountainous sites in the western United States, as well as over the glaciers of Alaska. However, there has yet to be an assessment on ICESat-2 snow depths over the boreal forests and tundra of Alaska, both of which are significant reservoirs of snow during the winter season. We present two case studies of retrieving snow depth using ICESat-2 over Alaska. We focus on two field sites used by the NASA SnowEx 2022/2023 campaigns: Farmer’s Loop/Creamer’s Field near Fairbanks, AK (forest) and Upper Kuparuk/Toolik on the Arctic North Slope (tundra). When validated against airborne lidar flown by the University of Alaska, Fairbanks (UAF), we find median biases of -6.3 to +2.1 cm among three ICESat-2 data products in the tundra region. Biases over the the boreal forest are somewhat higher at 7.5-13 cm. Utilizing the open source tool SlideRule, we observe little change in results when filtering by the ICESat-2 signal photon confidence scheme or by the vegetation filter. However, uncertainties in snow depth decrease with coarser Sliderule-derived snow depths. The number of signal photons (i.e., signal strength) has an influence on retrievals, with a large number of photons per ICESat-2 return providing more accurate snow depths. The initial results are promising, and we expect to expand this effort to other ICESat-2 overpasses over the SnowEx field sites.

Between 2012 and 2018 we mapped near-peak seasonal snow depths across two swaths covering 126 km in Northern Alaska using aerial structure-from-motion photogrammetry and lidar surveys. The surveys were validated by over a hundred thousand ground-based depth measurements. Using a quantitative method for identifying drift areas, we conducted a snowdrift census that showed on average 18% of the study area is covered by snowdrifts each winter, with 40% of the snow-water-equivalent contained in the drifts. Within the census we identified six types of drifts, some of which fill each winter, others which do not. The seasonal drift evolution was distinctly different in the two swaths, a result largely explained by physiographic differences. Using four metrics from the field of image quality analysis, we tested the year-to-year fidelity of these drift patterns, finding overall high year-to-year similarity (>70%), but with higher similarity values for filling drifts, and higher similarity in one swath vs. the other, again a function of the physiography. These high drift fidelity values are best explained by climatically convergent cumulative wind-blown snow fluxes interacting with drift traps to produce the same drifts year after year despite considerable differences in winter weather. However, due to the existence of filling vs. non-filling drifts, and a predicted increasing frequency of rain-on-snow events in the Arctic, future snowdrift patterns and drift evolution in the Arctic are likely to diverge from those of today.