Xia et al. (2026) Biased Aerosol Wet Deposition CAM5 Simulations: A Result of Misrepresented Convective-Stratiform Precipitation Partitioning When Benchmarked Against SPCAM

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-01-02
• Authors: Wenwen Xia, Yujun He, Bin Wang
• DOI: 10.3390/rs18010151

Research Groups

Community Atmosphere Model (CAM) development community (e.g., National Center for Atmospheric Research)

Short Summary

This study evaluates the conventional CAM5 model against the benchmark Super-parameterized Community Atmosphere Model (SPCAM) for simulating precipitation and aerosol wet deposition. It reveals that CAM5 significantly misrepresents convective-stratiform rainfall partitioning, leading to systematic biases in aerosol wet removal, particularly in tropical regions.

Objective

• To evaluate the performance of the conventional CAM5 model in simulating precipitation and aerosol wet deposition, using the Super-parameterized Community Atmosphere Model (SPCAM) as a benchmark, with a focus on the impact of convective-stratiform precipitation partitioning.

Study Configuration

• Spatial Scale: Global, with a focus on tropical regions.
• Temporal Scale: Climate-scale simulations, assessing long-term processes of precipitation and aerosol wet deposition.

Methodology and Data

• Models used: Super-parameterized Community Atmosphere Model (SPCAM), conventional Community Atmosphere Model version 5 (CAM5).
• Data sources: Satellite observations (for comparison of convective precipitation contribution); SPCAM simulations (used as a high-fidelity benchmark).

Main Results

• CAM5 overestimates the frequency of light convective rainfall (1.16 x 10⁻⁸ to 2.31 x 10⁻⁷ m s⁻¹) by up to 50% and underestimates heavy convective precipitation compared to SPCAM.
• Convective precipitation contributes over 90% to total rainfall in tropical CAM5 simulations, significantly exceeding satellite observations.
• CAM5 overestimates aerosol wet removal by convective precipitation (74.2% vs. 47.6% in SPCAM) and by light rain (84.0% vs. 65.5% in SPCAM), while underestimating removal by large-scale precipitation.
• These biases result in systematic errors in wet deposition fluxes across aerosol types and sizes in CAM5, particularly in tropical regions, distorting aerosol lifetime and distribution.

Contributions

• This study provides a quantitative evaluation of the conventional CAM5 model's performance in simulating precipitation and aerosol wet deposition using the high-fidelity SPCAM as a benchmark.
• It specifically identifies and quantifies the significant biases arising from the misrepresentation of convective-stratiform rainfall partitioning in CAM5, demonstrating its critical impact on aerosol wet removal, lifetime, and distribution in global climate models.
• It highlights the essential need for improving convective parameterizations in conventional global climate models for credible aerosol-climate projections.

Funding

Not specified in the provided text.

Citation

@article{Xia2026Biased,
  author = {Xia, Wenwen and He, Yujun and Wang, Bin},
  title = {Biased Aerosol Wet Deposition CAM5 Simulations: A Result of Misrepresented Convective-Stratiform Precipitation Partitioning When Benchmarked Against SPCAM},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18010151},
  url = {https://doi.org/10.3390/rs18010151}
}