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Turbulent Snow Transport and Accumulation: New Reduced-Order Models and Diagnostics

Turbulent Snow Transport and Accumulation: New Reduced-Order Models and Diagnostics

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

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Authors

Nikolas Olson Aksamit, Alex P. Encinas-Bartos, Holt Hancock, Alexander Prokop

Abstract

Understanding and modeling snow particle dynamics in the atmosphere remains a significant challenge for atmospheric scientists, hydrologists, and glaciologists. Temporally and spatially varying rates of snow transport, deposition, and erosion are driven by atmospheric turbulence and further complicated by inertial particle dynamics. Even with perfectly resolved wind fields, accurately predicting the fate of mobile snow particles in wind relies on semi-empirical assumptions embedded in diffeo-integro equations that contain numerical instabilities. The present research couples a modern approach to snow particle drag with model order reduction tools from nonlinear dynamical systems. Coupled with novel accumulation diagnostics, we provide a simplified framework of snow transport with well-defined simplification errors and rigorous physical meaning.

DOI

https://doi.org/10.31223/X54B1G

Subjects

Atmospheric Sciences, Dynamical Systems, Fluid Dynamics, Glaciology, Hydrology, Meteorology, Non-linear Dynamics

Keywords

Snow Preferential Deposition, Particle Transport, Blowing Snow, suspension, snow, Preferential deposition, particle transport, blowing snow, suspension

Dates

Published: 2025-05-15 05:13

Last Updated: 2025-05-15 05:13

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
All data publicly available or generated with open source software