Experimental assessment of different mineral dust on snow properties and melt dynamics under cold laboratory conditions

Understanding the role of mineral dust deposition on snow-covered surfaces is essential for improving predictions of snowmelt timing and magnitude in mountain and polar regions. This is particularly relevant given the global diversity of dust sources, such as North Africa and Central Asia, or regional sources related to human activities. While the radiative forcing of light-absorbing impurities is increasingly well documented, there is still limited understanding of how distinct mineral dust types and their associated mineralogical and geochemical compositions differently affect snowpack energy balance and melt processes. This knowledge gap persists because many models still assume a globally uniform mineralogical composition, leading to substantial uncertainties.

In this study, we present a series of controlled experiments conducted in the SubZero cold laboratories at Montana State University, using mini-lysimeters filled with snow artificially doped with varying and environmentally realistic concentrations of mineral dust samples originating from four distinct source regions (North Africa, Iceland, North America and the Middle East) under controlled environmental conditions in the cold chamber.

Our results suggest that Fe content is a key driver of the variability observed in snow darkening and melt enhancement. Dust-emitting sediments from the studied regions display distinct mineralogical compositions, with Fe contents varying 3.0 wt% in U.S. desert samples, 3.6 wt% in Moroccan dust, 5.5 wt% in mixed African dust sources, and substantially higher levels in Icelandic surface sediments, reaching up to 9.5 wt%.

Across experiments, the results show clear reductions in snow albedo, changes in specific surface area (SSA), and increases in liquid water content (LWC) and meltwater production for different dust types samples and concentrations.

The first author has an FPI predoctoral grant in the frame of MARGISNOW project (PID2021-124220OB-100) funded by the Spanish Ministry of Science and Innovation. This research received support from SNOWDUST (AEI, TED2021-130114B-I00), POSAHPI-2 (PID2022-143146OB-I00) and FRAGMENT (ERC-2017-COG, Grant agreement ID: 773051).