Wu et al. (2026) Hail Event Detection Using Power Spectrum Characteristics of Coherent Doppler Lidar: A Case Study in Hefei

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

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-04-02
• Authors: Kenan Wu, Yang Sun, Jiadong Hu, Tianwen Wei, Xiaodan Hu, M. Wang, H. L. Xia
• DOI: 10.3390/rs18071072

Research Groups

Not explicitly stated in the provided text.

Short Summary

This study employed a compact all-fiber coherent Doppler lidar (CDL) at 1.5 µm wavelength, combined with reanalysis and satellite data, to detect and characterize a hail event, identifying distinctive power spectrum characteristics of hail and verifying CDL's potential for high-spatiotemporal-resolution short-term hail forecasting.

Objective

• To detect and characterize a hail event using an all-fiber coherent Doppler lidar (CDL) and identify distinctive power spectrum characteristics of hail for short-term forecasting.

Study Configuration

• Spatial Scale: Localized severe convective weather events (hail); high-spatiotemporal-resolution data support.
• Temporal Scale: Sudden onset events; short-term forecasting.

Methodology and Data

• Models used: Not explicitly stated as a numerical model for simulation or prediction. The study primarily uses observational data and analysis of lidar signals.
• Data sources: Compact all-fiber coherent Doppler lidar (CDL) operating at 1.5 µm wavelength, ERA5 reanalysis data, Parsivel2 disdrometer data, cloud-type products from Fengyun satellite.

Main Results

• A compact all-fiber coherent Doppler lidar (CDL) successfully detected a hail event.
• The CDL's high-precision spectrum measurement capability enabled effective separation of multi-component power spectra from precipitation particles.
• Distinctive power spectrum characteristics of hail were identified by comparing particle velocity, spectrum width, and skewness across light rain, hail, and heavy rain.
• The study verified that CDL can provide high-spatiotemporal-resolution data support for the short-term forecasting of hail events.

Contributions

• Demonstrated the capability of a compact all-fiber coherent Doppler lidar (CDL) for detecting and characterizing hail events with high spatiotemporal resolution.
• Identified specific power spectrum characteristics (particle velocity, spectrum width, and skewness) that distinguish hail from other precipitation types using CDL data.
• Verified the potential of CDL as a valuable tool for short-term hail forecasting.

Funding

Not explicitly stated in the provided text.

Citation

@article{Wu2026Hail,
  author = {Wu, Kenan and Sun, Yang and Hu, Jiadong and Wei, Tianwen and Hu, Xiaodan and Wang, M. and Xia, H. L.},
  title = {Hail Event Detection Using Power Spectrum Characteristics of Coherent Doppler Lidar: A Case Study in Hefei},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18071072},
  url = {https://doi.org/10.3390/rs18071072}
}