The optical grain size of snow controls albedo, playing a key role in Earth's energy balance. This parameter varies substantially in time and space; thus, accurate estimates are vital. Reflectance measurements can be used to map grain size, although results differ considerably, depending on the algorithm and model used during retrieval. We perform a novel laboratory comparison to determine the optimal model, shape parameters, and retrieval algorithm for accurately estimating grain size.

Snow avalanches pose substantial risks to communities and public safety in Colorado. We studied tree growth patterns impacted by avalanches from 1698 to 2020 alongside meteorological data. We found variations in avalanche frequency revealing a decline in regional avalanche activity and shifts in the causes of these types of large and widespread avalanche events. This knowledge can enhance avalanche safety measures and infrastructure design.

To release a slab avalanche, a crack in a weak snow layer beneath a cohesive slab has to propagate. Information on that is essential for assessing avalanche risk. In the field, information can be gathered with the propagation saw test (PST). However, there are different standards on how to cut the PST. In this study, we experimentally investigate the effect of these different column geometries and provide models to correct for imprecise field test geometry effects on the critical cut length.

Accurate knowledge of firn grain size is crucial for many ice sheet research applications. Unfortunately, collecting detailed measurements of firn grain size is difficult. We demonstrate that scanning firn cores with a near-infrared imager can quickly produce high-resolution maps of both grain size and ice layer distributions. We map grain size and ice layer stratigraphy in 14 firn cores from Greenland and document changes to grain size and ice layer content from the extreme melt summer of 2012.

The amount of water within a snowpack is important information for predicting snowmelt and wet-snow avalanches. From within a controlled laboratory, the optimal method for measuring liquid water content (LWC) at the snow surface or along a snow pit profile using near-infrared imagery was determined. As snow samples melted, multiple models to represent wet-snow reflectance were assessed against a more established LWC instrument. The best model represents snow as separate spheres of ice and water.