Methaprayun et al. (2025) Enhancing the accuracy of weather radar heavy rainfall estimates in mountainous regions using combined radar quality indices

Identification

• Journal: Journal of Hydrology
• Year: 2025
• Date: 2025-07-17
• Authors: Monton Methaprayun, Thom Bogaard, Punpim Puttaraksa Mapiam
• DOI: 10.1016/j.jhydrol.2025.133907

Research Groups

• Department of Water Resources Engineering, Kasetsart University, Thailand
• Department of Water Management, Delft University of Technology, The Netherlands

Short Summary

The study introduces a novel relative radar quality index (QI) and an improved mean field bias adjustment technique to reduce rainfall estimation errors caused by beam blockage in the mountainous regions of Thailand.

Objective

• To enhance the accuracy of weather radar heavy rainfall estimates in mountainous terrain by mitigating the effects of beam blockage through combined quality indices and spatially variable bias adjustment.

Study Configuration

• Spatial Scale: Mountainous regions of Thailand, specifically the composite area covered by the Sattahip and Phimai radar stations.
• Temporal Scale: 2016–2022 (including 51 storm events, hourly data from August–October 2020, and three specific heavy storms from 2016, 2017, and 2020).

Methodology and Data

• Models used: Radar composite products, a novel relative radar quality index (QI) based on radar reflectivity fraction, and an improved mean field bias adjustment technique.
• Data sources: Single-polarization S-band radar data (Sattahip and Phimai stations) and automatic rain gauge networks.

Main Results

• The integration of combined multiple quality indices significantly improves the accuracy of radar rainfall estimates.
• The proposed mean field bias adjustment, which incorporates the spatial variability of bias factors associated with radar observation quality, outperforms conventional bias adjustment techniques, particularly during heavy rainfall events in beam-blocked mountainous basins.

Contributions

• Development of a novel relative radar quality index based on the radar reflectivity fraction to enhance composite radar products.
• Implementation of a bias adjustment method that accounts for the spatial quality of radar observations to mitigate terrain-induced errors (beam blockage).

Funding

• Not specified in the provided text.

Citation

@article{Methaprayun2025Enhancing,
  author = {Methaprayun, Monton and Bogaard, Thom and Mapiam, Punpim Puttaraksa},
  title = {Enhancing the accuracy of weather radar heavy rainfall estimates in mountainous regions using combined radar quality indices},
  journal = {Journal of Hydrology},
  year = {2025},
  doi = {10.1016/j.jhydrol.2025.133907},
  url = {https://doi.org/10.1016/j.jhydrol.2025.133907}
}