Tag: physics- based model

A University of Vermont- led team improved a physics- based snow model to better capture Northeast U.S. winter conditions, including midwinter thaws and runoff, which differ from those in the western U.S.

The October 28, 2026, article by Hannah Fischer (UVM Water Resources Institute) covers a study published in Water Resources Research.

Northeast mountain snowpacks, especially at intermediate elevations, are shaped by a milder, more humid climate. They feature frequent melt- freeze cycles, denser snow, and midwinter thaws, often leading to rain- on- snow events and flooding. Standard snow models, largely developed and tested for western conditions, often fail to represent these dynamics accurately near freezing temperatures.

Researchers from UVM, the U.S. Geological Survey (USGS), and the University of British Columbia applied and refined a physics- based model (drawing on approaches like SnowModel) focused on Mount Mansfield (Vermont’s highest peak) and the adjacent Ranch Brook watershed (a long- term hydrological monitoring site draining to the Winooski River and Lake Champlain).

Elevations ranged from about 200- 1,300 meters.

Key findings include:

• The snowpack is highly sensitive to temperature and precipitation changes, especially at middle elevations (700- 900 m). This band often aligns with the rain- snow line and near- freezing conditions; a shift of roughly +1.1°C can flip precipitation from snow to rain and accelerate melt.
• The improved model more accurately simulated observed snow water equivalent (SWE), snow depth, snowpack density, and snowmelt- derived runoff compared with prior approaches.
• This enables better analysis of how warmer, wetter winters may affect snowpack and hydrology, supporting improved flood forecasting and understanding of vulnerable systems.

Lead author Anna Grunes (UVM M.S. graduate in Civil and Environmental Engineering) noted the work advances understanding of highly vulnerable snowpacks amid rapid winter changes, with Vermont’s Green Mountains serving as a useful natural laboratory.

USGS research hydrologist (emeritus) Jamie Shanley highlighted its value for the region’s tourism- dependent snow season and broader hydrologic insights.

Additional co- authors included UVM faculty (Arne Bomblies, Donna Rizzo, Patrick Clemins, Beverley Wemple) and collaborators from USGS and elsewhere.

The project received support from the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) and the Cooperative Institute for Research to Operations in Hydrology (CIROH).

Application of a Physics-Based Snow Model to Assess Impacts of a Changing Climate on Snowpack and Snowmelt in the Northeastern United States

It is the study referenced in the University of Vermont press release (“UVM Researchers Explore the Northeast’s Vulnerable Snowpack” by Hannah Fischer, October 28, 2026).

Lead author is Anna Grunes (M.S. graduate, UVM Civil and Environmental Engineering), with co-authors from UVM, the U.S. Geological Survey (USGS), and the University of British Columbia.

The team adapted and evaluated a distributed physics- based snow model (SnowModel) for the Northeast U.S., specifically a domain centered on Mount Mansfield (Vermont’s highest peak) and the Ranch Brook watershed (long-term hydrological monitoring site on the eastern slope that drains to the Winooski River and Lake Champlain). Elevations span roughly 200- 1,300 m.⁠

Northeast snowpacks differ markedly from those in the western U.S.: milder, more humid conditions produce frequent melt– freeze cycles, denser snow, midwinter thaws, and rain- on- snow events.

Standard models often underperform near 0 °C. The improved configuration better reproduces observed snow water equivalent (SWE), snow depth, density, and melt- derived runoff.

Key technical improvements (drawn from the associated thesis and press summary)

• Precipitation- phase partitioning: Humidity- aware methods (e.g., wet- bulb temperature) outperformed simple air- temperature thresholds.
• Liquid- water percolation and retention: Gravity- dominated percolation schemes reduced model error most effectively.
• Calibration and validation used historical snow surveys plus a newer network of monitoring stations.

Snowpack response is highly elevation- dependent. Middle elevations (≈700- 900 m), near the typical rain– snow transition and freezing level, are especially sensitive.

A modest warming of about +1.1 °C can shift precipitation fully from snow to rain and accelerate melt.

Simulated warmer and wetter conditions increase midwinter melt and runoff pulses while producing an earlier, less pronounced spring freshet. In one example midwinter event, +3.3 °C produced a substantial surface- water- input spike (tens of mm) at mid- elevations where baseline melt was minimal.

The work improves representation of midwinter runoff and supports better flood analysis and forecasting under changing winters. It highlights the vulnerability of intermediate- elevation Northeast snowpacks that are critical for water resources, ecosystems, and winter recreation and tourism.

Funding included the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) and the Cooperative Institute for Research to Operations in Hydrology (CIROH).⁠

Full- text access may require institutional login, AGU membership, or purchase through the Wiley Online Library page.

Related open material includes Anna Grunes’s thesis (“Development and Evaluation of a Physics- Based Snow Model to Assess Spatiotemporal Snowpack Variability in Vermont”), which provides additional methodological detail and results that underpin the journal paper.

Journal: Water Resources Research

DOI: 10.1029/2026wr044222

First published: 28 October 2026

Provided: University of Vermont

Authors: Anna Grunes, Graham Sexstone, Arne Bomblies, John Hammond, Kate Hale, Donna M. Rizzo, Patrick J. Clemins, Beverley Wemple

Abstract

In the temperate, humid mountains of the northeastern United States (U.S.), seasonal snowmelt plays an important role in the annual water balance, and midwinter rain-on-snow events and spring snowmelt are common drivers of flooding. Frequent near-freezing winter temperatures make the region particularly susceptible to midwinter rain and ongoing climate warming. However, models used to evaluate seasonal snowpack evolution and inform snowmelt-derived streamflow forecasting remain limited in their ability to represent these conditions. Here, we evaluate northeastern U.S. snowpack under a changing climate using a distributed, physics-based snowpack model. SnowModel was applied to a domain in the state of Vermont, surrounding Mount Mansfield (1,340 m). Testing various model configurations showed that incorporating a wet-bulb temperature threshold (0.5°C) for precipitation phase partitioning and a gravity-driven liquid water percolation scheme most effectively reduced model error. These modifications reduced mean percent bias by 33 and 75 percentage points for snow depth and snow water equivalent (SWE), respectively. Using the improved model, we assessed the effects of climate-driven changes through a range of perturbations in temperature and precipitation. Middle elevations (700–900 m) were the most sensitive to these changes, exhibiting up to a 60% decrease in peak SWE with modest warming (+1.1°C). Incremental warming caused increased midwinter melt, including an event in which a +3.3°C temperature increase produced 40 mm of additional snowmelt (+700%) in 1 day at mid-elevations. These findings demonstrate the sensitivity of the northeastern U.S. snowpack to climate warming, and