Item: TOWARDS REAL-TIME FRACTIONATION OF MIXED-PHASE PRECIPITATION
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Title: TOWARDS REAL-TIME FRACTIONATION OF MIXED-PHASE PRECIPITATION
Proceedings: Proceedings, International Snow Science Workshop, Whistler, BC, Canada, 2026
Authors:
- Eric R. Pardyjak [ University of Utah, Department of Mechanical Engineering, Salt Lake City, UT, USA ]
- Dhiraj K. Singh [ University of Utah, Department of Mechanical Engineering, Salt Lake City, UT, USA ]
- Daniel Webster [ University of Utah, Department of Mechanical Engineering, Salt Lake City, UT, USA ]
- Benjamin H. Silberman [ University of Utah, Department of Mechanical Engineering, Salt Lake City, UT, USA ]
- Timothy Garrett [ University of Utah, Department of Atmospheric Sciences, Salt Lake City, UT, USA ]
- Travis Morrison [ University of Utah, Department of Mechanical Engineering, Salt Lake City, UT, USA ] [ Utah Avalanche Center, Salt Lake City, UT, USA ]
Date: 2026-09-28
Abstract: Near-surface precipitation can occur as liquid, solid, or mixed-phase hydrometeors. In many winter storms, individual particles are not purely rain or snow, but instead contain both liquid and ice, as in sleet, freezing rain, or partially melted snow. These complex particles remain poorly constrained in observations, which limits progress in numerical weather prediction and in understanding hazardous winter weather. Mixed-phase precipitation is especially important because it significantly affects surface icing, visibility, and road traction, creating major risks for transportation and infrastructure. From a snowpack perspective, the water content of precipitation can lead to the injection of both heat and liquid mass into the snowpack resulting in snow grain metamorphism and potentially modification of the seasonal release of snow-melt water, flooding, weakening of a snowpack, and generation of various melt-freeze crusts that lead to avalanche instabilities. Various methods currently exist for quantifying the amount of water going into a snowpack including optical disdrometers, imaging disdrometers, micro rain radars, and integrated satellite products, each of which has advantages and disadvantages. Crowdsourcing has also provided important qualitative knowledge of the spatial variability of phase that is particularly useful for validation studies. Here, we present a new first-principles-based experimental methodology based on the Differential Emissivity Imaging Disdrometer or DEID, a thermal-imaging hot-plate device, that has previously been used to measure snow water equivalent (SWE), snow density, and other integrated snowpack properties. Because the DEID can analyze hydrometeors on a particle-by-particle basis, it can be used to identify very short-lived mixed-phase events that may normally be overlooked. We present cold-room lab results to verify that the methodology works and to quantify its ability to fractionate liquid and ice phases. We then present preliminary results of phase-fractionation from field observations collected in Utah at the Alta-Collins snow-study plot and Red Butte Canyon during the 2020–2021 winter season and more recently at the Atwater snow-study plot during the 2025-2026 winter season. We analyze storms with a range of near-freezing mean air temperatures representing different conditions.
Object ID: ISSW2026_FS4.4.pdf
DOI: https://doi.org/10.15788/1790098458
Language of Article: English
Presenter(s): Eric Pardyjak
Keywords: Mixed-phase precipitation, DEID, Avalanche forecasting, Rain-on-snow events.
Page Number(s): 1596 - 1602
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