Shu et al. (2026) Direct EnKF assimilation of FY-3G dual-frequency PMR reflectivity for heavy rainfall forecasting: frequency-dependent impacts of Ka- and Ku-band observations

Identification

• Journal: Atmospheric Research
• Year: 2026
• Date: 2026-09-22
• Authors: Aiqing Shu, Peng Zhang, Feifei Shen, Yubao Chen, Jinzhong Min
• DOI: 10.1016/j.atmosres.2026.109356

Research Groups

• Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)
• Joint International Research Laboratory of Climate and Environment Change (ILCEC)
• Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology
• Meteorological Observation Centre, China Meteorological Administration
• CMA Research Centre on Meteorological Observation Engineering Technology
• State Key Laboratory of Environment Characteristics and Effects for Near-space
• China Meteorological Administration Tornado Key Laboratory
• East China Phased Array Weather Radar Application Joint Laboratory

Short Summary

This study investigates the direct assimilation of FY-3G PMR reflectivity using the Gridpoint Statistical Interpolation (GSI)-based Ensemble Kalman Filter (EnKF) system for heavy rainfall forecasting, revealing clear frequency-dependent impacts of Ka- and Ku-band observations.

Objective

• Investigate the potential of FY-3G PMR observations for improving convective-scale numerical weather prediction (NWP) through direct ensemble-based data assimilation (DA).

Study Configuration

• Spatial Scale: Regional scale over Hunan and Beijing, China.
• Temporal Scale: Hourly to daily time scales.

Methodology and Data

• Models used: Gridpoint Statistical Interpolation (GSI)-based Ensemble Kalman Filter (EnKF) system, WRF Single-Moment 6-class (WSM6) microphysics scheme.
• Data sources: FY-3G dual-frequency PMR reflectivity, ground-based S-band radar data.

Main Results

• Ka-band assimilation preferentially refines upper-tropospheric ice-phase structures, while Ku-band assimilation enables the EnKF to more effectively reconstruct mid-to-lower-tropospheric hydro­ meteors.
• Diagnostics of particle size distributions (PSDs) within the WSM6 microphysics scheme illustrate how frequency-dependent hydrometeor mass adjustments are represented in particle-size space.

Contributions

• This study demonstrates the value of FY-3G Ku-band observations for heavy-rainfall forecasting and suggests that optimized dual-frequency assimilation strategies may need to be developed.

Funding

• This research was supported by the Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD).

Citation

@article{Shu2026Direct,
  author = {Shu, Aiqing and Zhang, Peng and Shen, Feifei and Chen, Yubao and Min, Jinzhong},
  title = {Direct EnKF assimilation of FY-3G dual-frequency PMR reflectivity for heavy rainfall forecasting: frequency-dependent impacts of Ka- and Ku-band observations},
  journal = {Atmospheric Research},
  year = {2026},
  doi = {10.1016/j.atmosres.2026.109356},
  url = {https://doi.org/10.1016/j.atmosres.2026.109356}
}