Xu et al. (2025) Assessing the clear-sky assimilation of FY-3D/HIRAS water vapor data and its impact on Typhoon forecasting

Identification

• Journal: Atmospheric Research
• Year: 2025
• Date: 2025-12-07
• Authors: Xiaoying Xu, Zhuoya Ni, Qifeng Lu, Ruixia Liu, Chunqiang Wu, Fu Wang, Xingtao Song
• DOI: 10.1016/j.atmosres.2025.108684

Research Groups

• Chinese Academy of Meteorological Sciences, Beijing 100081, China
• CMA Earth System Modeling and Prediction Centre (CEMC), China Meteorological Administration, Beijing 100081, China
• State Key Laboratory of Severe Weather (LaSW), China Meteorological Administration, Beijing 100081, China
• Nanjing University of Information Science and Technology, Nanjing 210044, China

Short Summary

This study assesses the clear-sky assimilation of Fengyun-3D (FY-3D) Hyperspectral Infrared Atmospheric Sounder (HIRAS) water vapor data into the China Meteorological Administration Global Forecasting System (CMA-GFS). The assimilation is shown to improve analysis fields and enhance short- to medium-range forecast accuracy for various meteorological parameters, including precipitation and typhoon tracks.

Objective

• To evaluate the impact of clear-sky assimilation of FY-3D/HIRAS water vapor data on the analysis fields and short- to medium-range forecasting capability of the CMA-GFS model, with a specific focus on typhoon forecasting.

Study Configuration

• Spatial Scale: Global (CMA-GFS) with regional focus on typhoon-affected areas (e.g., Typhoon Gaemi).
• Temporal Scale: Short- to medium-range forecasting (typically 1 to 10 days) based on batch cycling assimilation experiments.

Methodology and Data

• Models used: China Meteorological Administration Global Forecasting System (CMA-GFS) with its four-dimensional variational data assimilation system.
• Data sources: Fengyun-3D (FY-3D) Hyperspectral Infrared Atmospheric Sounder (HIRAS) water vapor data (20 selected channels in the mid-to-upper troposphere).

Main Results

• Assimilating FY-3D/HIRAS water vapor data improves the analysis fields of geopotential height, humidity, temperature, and wind.
• The assimilation enhances the short- to medium-range forecasting skills of the CMA-GFS model.
• Equitable Threat Score values indicate improvements in forecasts for light, moderate, and heavy rain categories, demonstrating enhanced precipitation forecast accuracy.
• A case study of Typhoon Gaemi (2024) shows that assimilating water vapor observations strengthens humidity and vertical motion in the mid-troposphere, leading to improved typhoon track forecasts.

Contributions

• Validates the application potential of FY-3D/HIRAS water vapor data for numerical weather prediction.
• Demonstrates the positive role of clear-sky assimilation of water vapor data in improving global numerical weather prediction and specific typhoon forecasting accuracy within the CMA-GFS framework.
• Provides evidence for the effectiveness of integrating new satellite hyperspectral data into operational forecasting systems.

Funding

• Not specified in the provided text.

Citation

@article{Xu2025Assessing,
  author = {Xu, Xiaoying and Ni, Zhuoya and Lu, Qifeng and Liu, Ruixia and Wu, Chunqiang and Wang, Fu and Song, Xingtao},
  title = {Assessing the clear-sky assimilation of FY-3D/HIRAS water vapor data and its impact on Typhoon forecasting},
  journal = {Atmospheric Research},
  year = {2025},
  doi = {10.1016/j.atmosres.2025.108684},
  url = {https://doi.org/10.1016/j.atmosres.2025.108684}
}