Abolafia‐Rosenzweig et al. (2025) Snow Cover Plays a Non‐Dominant Role in WRF/Noah‐MP Simulated Surface Air Temperature Cold Biases Over the Western U.S.

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

Identification

• Journal: Journal of Geophysical Research Atmospheres
• Year: 2025
• Date: 2025-11-20
• Authors: Ronnie Abolafia‐Rosenzweig, Changhai Liu, Tzu‐Shun Lin, David M. Mocko, Karl Rittger, William Rudisill, Yifan Cheng, Michael Barlage, Ross T. Palomaki, Jerry Wegiel, Sujay V. Kumar
• DOI: 10.1029/2025jd044191

Research Groups

Information not available in the provided abstract.

Short Summary

This study evaluates whether snow cover errors are the primary cause of persistent 2-meter air temperature cold biases in WRF/Noah-MP simulations across the western U.S. during snow seasons, concluding that while snow cover errors contribute modestly, they are not the main driver.

Objective

• To evaluate whether snow cover errors are the primary driver for persistent 2-meter air temperature (T2) cold biases in coupled WRF/Noah-MP simulations across the western U.S. during snow seasons.

Study Configuration

• Spatial Scale: Western U.S. (WUS), mountainous regions, high-elevation areas.
• Temporal Scale: Snow seasons, mainly November–April.

Methodology and Data

• Models used: Coupled Weather Research and Forecasting (WRF) model with the Noah-MP land surface model. Simulations included baseline and those using recently enhanced snow compaction and ground snow cover fraction (SCF) parameterizations (ARnew). An additional experiment imposed unrealistically low ground SCF.
• Data sources: Analyses of simulated 2-meter air temperature (T2), ground snow cover fraction (SCF), snow water equivalent (SWE), and surface albedo from model outputs. Statistical and information theory analyses were applied.

Main Results

• Baseline simulations exhibited widespread cold biases in maximum daily T2 (T2 max) during November–April, with mean biases ranging from -1.05 °C to -1.32 °C, and up to -5.31 °C in higher elevation areas.
• Simulations using enhanced snow compaction and ground SCF parameterizations (ARnew) reduced cold biases across the WUS by an average of 17%–24%.
• Despite these reductions and underestimates of ground SCF and SWE in ARnew simulations, notable cold biases persisted, especially in high-elevation areas.
• Statistical and information theory analyses revealed very weak connections between T2 max biases and biases in ground SCF and SWE.
• An experiment imposing unrealistically low ground SCF (mean bias = -75%) still showed cold biases, particularly in high-elevation areas (mean bias for elevations > 2,000 m = -1.46 °C).
• These results indicate that snow cover errors contribute modestly to cold biases but are not their primary cause.

Contributions

• Systematically evaluates the role of snow cover errors as a primary driver for atmospheric model cold biases in mountainous snow regions.
• Provides quantitative evidence that snow cover errors are not the main cause of persistent T2 cold biases in WRF/Noah-MP, despite their modest contribution.
• Redirects future research efforts towards other potential factors for resolving cold biases, such as uncertainties in canopy radiative transfer, surface turbulence, and other atmospheric processes in complex terrain.

Funding

Information not available in the provided abstract.

Citation

@article{AbolafiaRosenzweig2025Snow,
  author = {Abolafia‐Rosenzweig, Ronnie and He, Cenlin and Liu, Changhai and Lin, Tzu‐Shun and Mocko, David M. and Rittger, Karl and Rudisill, William and Cheng, Yifan and Barlage, Michael and Palomaki, Ross T. and Wegiel, Jerry and Kumar, Sujay V.},
  title = {Snow Cover Plays a Non‐Dominant Role in WRF/Noah‐MP Simulated Surface Air Temperature Cold Biases Over the Western U.S.},
  journal = {Journal of Geophysical Research Atmospheres},
  year = {2025},
  doi = {10.1029/2025jd044191},
  url = {https://doi.org/10.1029/2025jd044191}
}