Cristea et al. (2026) Sensitivity of Spatial Snowmelt Simulations to Radiative Forcing and Model Top Layer Thickness

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

Identification

• Journal: Water Resources Research
• Year: 2026
• Date: 2026-08-01
• Authors: Nicoleta C. Cristea, Jessica D. Lundquist
• DOI: 10.1029/2025wr042968

Research Groups

• University of California, Department of Hydrology and Water Resources
• University of California, Department of Atmospheric Science

Short Summary

This study investigates the importance of energy balance considerations in snow modeling by examining the impact of model parameters on simulated snowmelt initiation and rate. The results highlight the significance of incorporating multiple validation data sources, including snow surface temperature.

Objective

• Investigate how decisions regarding model parameters interact with energy budget considerations to effectively simulate snowmelt

Study Configuration

• Spatial Scale: Upper Tuolumne River watershed in California, USA (approximately 1,000 km²)
• Temporal Scale: Daily time step for a period of one year during the winter season

Methodology and Data

• Models used: Two-layer Distributed Hydrology Soil Vegetation Model (DHSVM)
• Data sources: Observations from snow surface temperature sensors, incoming longwave radiation measurements, albedo data, and streamflow records

Main Results

• The model top layer thickness has a significant impact on diurnal variations in snow surface temperature, snowpack energy distribution, and the timing of snowmelt.
• Lower albedo enhances melting rates more strongly in thinner upper layers.
• Biases in incoming longwave radiation can either amplify or mitigate these effects.

Contributions

This study highlights the importance of considering energy balance aspects in snow modeling and demonstrates the significance of incorporating multiple validation data sources, including snow surface temperature. The findings provide insights into the complex interactions between model parameters, forcing data, and snowmelt simulations.

Funding

• This research was funded by the National Science Foundation (NSF) under grant number 1724947.
• Additional support was provided by the University of California's Water Resources Center.

Citation

@article{Cristea2026Sensitivity,
  author = {Cristea, Nicoleta C. and Lundquist, Jessica D.},
  title = {Sensitivity of Spatial Snowmelt Simulations to Radiative Forcing and Model Top Layer Thickness},
  journal = {Water Resources Research},
  year = {2026},
  doi = {10.1029/2025wr042968},
  url = {https://doi.org/10.1029/2025wr042968}
}