Li et al. (2026) Subseasonal Forecasting of Snow Cover and Cold Compound Extremes: Insights From MPAS‐A Over Midlatitude East Asia

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

Identification

• Journal: Journal of Geophysical Research Atmospheres
• Year: 2026
• Date: 2026-04-11
• Authors: Wei Li, Wenxin Ruan, Weidong Guo
• DOI: 10.1029/2025jd045631

Research Groups

Not explicitly mentioned in the abstract.

Short Summary

This study evaluates the subseasonal forecast skill of snow cover and cold compound extremes in midlatitude East Asia using MPAS-A, finding detectable skill up to three pentads, but highlighting that biases from underestimated snowfall and the choice of snow cover fraction scheme significantly impact forecast accuracy.

Objective

• To evaluate the subseasonal forecast performance of snow cover and cold compound extremes in midlatitude East Asia using the Model for Prediction Across Scales–Atmosphere (MPAS‐A), specifically investigating the role of snow-atmosphere interactions and the impact of model parameterizations.

Study Configuration

• Spatial Scale: Regional (midlatitude East Asia)
• Temporal Scale: Subseasonal (forecasts up to 10 days, detectable skill up to 15 days, limited reliability beyond 20 days)

Methodology and Data

• Models used: Model for Prediction Across Scales–Atmosphere (MPAS‐A), Noah‐MP land surface scheme, Noah land surface scheme.
• Data sources: Not explicitly mentioned in the abstract for evaluation or initialization, but forecasts are generated by MPAS-A.

Main Results

• Rapid snow cover expansion and abrupt decreases in surface air temperature occur regionally at the onset of snow cover and cold compound extremes.
• MPAS-A can forecast these extreme variations in snow cover fraction and temperature up to two pentads (10 days) in advance.
• Forecast skill declines but remains detectable at three pentads (15 days).
• Forecasts beyond four pentads (20 days) exhibit limited reliability.
• Biases in MPAS-A snow cover fraction predictions primarily originate from an underestimation of snowfall.
• These snowfall-related biases propagate into surface air temperature forecasts.
• The forecast performance of MPAS-A is sensitive to the snow cover fraction scheme employed.
• MPAS-A utilizing the Noah-MP land surface scheme produces more snow cover and colder temperatures compared to using the Noah scheme, due to differences in their snow cover fraction formulations.

Contributions

• Highlights the critical role of snow cover in subseasonal forecasts of compound extremes.
• Demonstrates that improving snowfall representation and snow cover fraction parameterization can significantly enhance subseasonal forecasting models.
• Provides an evaluation of MPAS-A's subseasonal forecast performance for snow cover and cold compound extremes in midlatitude East Asia, with a focus on snow-atmosphere interactions and sensitivity to land surface schemes.

Funding

Not explicitly mentioned in the abstract.

Citation

@article{Li2026Subseasonal,
  author = {Li, Wei and Ruan, Wenxin and Guo, Weidong},
  title = {Subseasonal Forecasting of Snow Cover and Cold Compound Extremes: Insights From MPAS‐A Over Midlatitude East Asia},
  journal = {Journal of Geophysical Research Atmospheres},
  year = {2026},
  doi = {10.1029/2025jd045631},
  url = {https://doi.org/10.1029/2025jd045631}
}