Lundquist et al. (2026) Snow What? Strengths and Limitations of Different Snow Products in Western U.S. Mountains

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Water Resources Research
• Year: 2026
• Date: 2026-08-31
• Authors: Jessica D. Lundquist, Mimi Rose Abel, William Ryan Currier, Darren L. Jackson
• DOI: 10.1029/2026wr043728

Research Groups

Not specified in the provided text.

Short Summary

This study evaluates various snow water equivalent (SWE) products against aerial LiDAR observations in the western United States to identify the most accurate datasets for hydrological analysis.

Objective

• To compare existing SWE products with high-resolution aerial LiDAR data to determine which products best represent peak snow water storage and to identify the technical characteristics associated with higher accuracy.

Study Configuration

• Spatial Scale: Mountainous regions of the western United States (specifically Colorado, California, and Washington).
• Temporal Scale: Annual peak SWE, with a focus on the March–April window for 14 specific flight acquisitions.

Methodology and Data

• Models used: Western U.S. SWE Reanalysis (WUS-SR), SNODAS, University of Arizona products, ERA5-Land, and various energy balance models.
• Data sources: 26 aerial LiDAR acquisitions (ground truth) and various existing SWE reanalysis/model products.

Main Results

• WUS-SR: Demonstrated the highest accuracy for near-peak SWE with a bias of 1.6% and the best spatial distribution (lowest mean absolute error).
• SNODAS and University of Arizona products: Provided reasonable estimates with biases ranging between 7.8% and 10.2%.
• ERA5-Land: Showed a relatively small basin-scale bias (-17.5%) but poor spatial representation due to its coarse resolution.
• Accuracy Drivers: The most accurate products typically feature a resolution of 9 km or finer, utilize fractional snow-covered area or in situ SWE measurements, and employ well-calibrated precipitation and snowmelt frameworks.
• Model Deficiencies: Many energy balance models overestimated melt, likely due to excessive incoming radiation estimates.

Contributions

The study establishes critical guidelines for selecting SWE products, highlighting the necessity of high resolution and specific calibration factors, while validating WUS-SR as a superior product for reproducing peak SWE in the western US.

Funding

Not specified in the provided text.

Citation

@article{Lundquist2026Snow,
  author = {Lundquist, Jessica D. and Abel, Mimi Rose and Currier, William Ryan and Jackson, Darren L.},
  title = {Snow What? Strengths and Limitations of Different Snow Products in Western U.S. Mountains},
  journal = {Water Resources Research},
  year = {2026},
  doi = {10.1029/2026wr043728},
  url = {https://doi.org/10.1029/2026wr043728}
}