Wang et al. (2026) Projected Future Changes of Atmospheric Rivers by a High- and Low-resolution CESM

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

Identification

• Journal: Journal of Climate
• Year: 2026
• Date: 2026-03-06
• Authors: Shuyu Wang, Shenghui Zhou, Weiwei Ma, Xiaohui Ma, L N Wu
• DOI: 10.1175/jcli-d-25-0377.1

Research Groups

Community Earth System Model (CESM) development and research community (e.g., National Center for Atmospheric Research - NCAR).

Short Summary

This study evaluates atmospheric river (AR) simulations and projections using high-resolution (HR) and low-resolution (LR) Community Earth System Model (CESM), finding that LR CESM systematically underestimates AR frequency, intensity, and precipitation, particularly for extreme events, while HR CESM significantly improves historical simulations and provides more robust projections of increased extreme ARs under warming.

Objective

• To evaluate and compare atmospheric river (AR) simulations and projections using both high-resolution (HR) and low-resolution (LR) Community Earth System Model (CESM) globally across boreal winter and summer seasons.
• To quantify systematic biases in LR climate models regarding AR characteristics and their future projections under climate change.

Study Configuration

• Spatial Scale: Global scale, comparing low-resolution (~0.5° to 1° grid spacing) with high-resolution climate model configurations, resolving mesoscale ocean-atmosphere interactions.
• Temporal Scale: Boreal winter and summer seasons; historical simulations and future projections under warming climate scenarios.

Methodology and Data

• Models used: Community Earth System Model (CESM) – specifically, both high-resolution (HR) and low-resolution (LR) versions.
• Data sources: Model output from CESM simulations (historical and future climate projections).

Main Results

• LR CESM systematically underestimates AR frequency, intensity, integrated vapor transport (IVT), and precipitation by 20% to 40%.
• This underestimation in LR CESM is primarily due to underrepresentation of extreme ARs (Category 5) and overrepresentation of non-extreme events (Category 1-4).
• HR CESM demonstrates substantial improvements in simulating historical AR characteristics, particularly for extreme events.
• Both HR and LR CESM project more frequent and intense ARs with a poleward shift under warming.
• While relative increases are similar, LR CESM underestimates absolute values in projections due to weaker historical baselines.
• HR CESM projections feature approximately a 50% increment of extreme ARs and reduced non-extreme events.
• LR CESM projections show increases in both extreme and non-extreme events, continuing to underestimate the contribution of extreme ARs.
• Thermodynamic effects primarily drive AR intensification under warming, while dynamic processes modulate regional responses.
• Winter projections show more consistency between HR and LR CESM, whereas summer reveals larger divergence in dynamic responses and precipitation projections.

Contributions

• Provides the first global-scale, seasonal evaluation of AR simulations and projections comparing high-resolution and low-resolution versions of a major Earth System Model (CESM).
• Quantifies the systematic biases (20-40% underestimation) of low-resolution models in simulating AR frequency, intensity, and precipitation, especially for extreme events.
• Highlights the critical importance of resolving mesoscale ocean-atmosphere interactions in climate models for accurate simulation and projection of AR behavior under climate change.
• Differentiates the roles of thermodynamic and dynamic processes in AR intensification and regional responses under warming.

Funding

Not specified in the abstract.

Citation

@article{Wang2026Projected,
  author = {Wang, Shuyu and Zhou, Shenghui and Ma, Weiwei and Ma, Xiaohui and Wu, L N},
  title = {Projected Future Changes of Atmospheric Rivers by a High- and Low-resolution CESM},
  journal = {Journal of Climate},
  year = {2026},
  doi = {10.1175/jcli-d-25-0377.1},
  url = {https://doi.org/10.1175/jcli-d-25-0377.1}
}