Liu et al. (2025) Impact of Aerosols on Weather Forecasts in China During Winter 2016–2017

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

Identification

• Journal: Journal of Advances in Modeling Earth Systems
• Year: 2025
• Date: 2025-12-01
• Authors: Chong Liu, Yue Peng, Junting Zhong, Qiying Chen, Jiong Chen, Hong Wang, Zhanshan Ma, Kun Liu, Xueshun Shen, Xiaoye Zhang
• DOI: 10.1029/2024ms004696

Research Groups

• China Meteorological Administration (CMA)
• Research groups associated with the development and operation of the Global/Regional Assimilation and PrEdiction System (GRAPES_Meso5.1) and the Chinese Unified Atmospheric Chemistry Environment (CUACE) model.

Short Summary

This study developed and applied CMA's first chemistry-weather integrated model (GRAPES_Meso5.1/CUACE CW V1.0) to investigate aerosol impacts on weather forecasts during the 2016–2017 winter season across China, finding that incorporating aerosol feedbacks significantly improves temperature and precipitation forecast accuracy, particularly in polluted regions.

Objective

• To examine the impacts of aerosols on weather forecasts during the 2016–2017 winter season across China using a newly developed chemistry-weather integrated model (GRAPES_Meso5.1/CUACE CW V1.0) that incorporates aerosol-cloud-radiation interactions.

Study Configuration

• Spatial Scale: China (national scale), with specific focus on the Beijing-Tianjin-Hebei (JJJ) region and Pearl River Delta regions.
• Temporal Scale: 2016–2017 winter season, with analysis of 72-hour weather forecasts.

Methodology and Data

• Models used: GRAPESMeso5.1 (Global/Regional Assimilation and PrEdiction System), CUACE (Chinese Unified Atmospheric Chemistry Environment) model. The integrated model is GRAPESMeso5.1/CUACE CW V1.0.
• Data sources: Not explicitly detailed in the abstract, but implied by an operational Global/Regional Assimilation and PrEdiction System, which typically assimilates various meteorological observations.

Main Results

• Incorporating aerosol feedbacks improved forecasts of temperature and precipitation.
• 72-hour temperature forecast errors were reduced by up to 30% over the Beijing-Tianjin-Hebei (JJJ) region.
• High cloud cover increased in the JJJ and Pearl River Delta regions.
• Cumulative precipitation forecast errors were reduced by an average of 7.9–8.7 mm across China.
• Aerosols meaningfully influence convective and radiative processes relevant to short-term weather prediction.

Contributions

• Development and implementation of CMA's first version of a chemistry-weather integrated model (GRAPES_Meso5.1/CUACE CW V1.0) incorporating aerosol-cloud-radiation interactions.
• Demonstration of the potential benefits of integrating prognostic aerosol processes into numerical weather prediction systems.
• Provision of evidence for improved forecast accuracy, especially under high-pollution conditions, by considering aerosol feedbacks.

Funding

• Not mentioned in the abstract.

Citation

@article{Liu2025Impact,
  author = {Liu, Chong and Peng, Yue and Zhong, Junting and Chen, Qiying and Chen, Jiong and Wang, Hong and Ma, Zhanshan and Liu, Kun and Shen, Xueshun and Zhang, Xiaoye},
  title = {Impact of Aerosols on Weather Forecasts in China During Winter 2016–2017},
  journal = {Journal of Advances in Modeling Earth Systems},
  year = {2025},
  doi = {10.1029/2024ms004696},
  url = {https://doi.org/10.1029/2024ms004696}
}