Mondal et al. (2026) Assessing the Potential of Total Lightning for Nowcasting Ground Rainfall in Summer Thunderstorms Using Automatic Density-Dependent Tracking

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

Identification

• Journal: Atmosphere
• Year: 2026
• Date: 2026-03-31
• Authors: Debrupa Mondal, Yasuhide Hobara, Hiroshi Kikuchi, Jeff Lapierre
• DOI: 10.3390/atmos17040364

Research Groups

Not explicitly mentioned in the provided text.

Short Summary

This study integrates total lightning data and high-resolution radar precipitation data using an automatic storm cell tracking method to improve the prediction accuracy of torrential rainfall, building on prior findings of a strong correlation and time lag between lightning and ground rainfall.

Objective

• To improve the prediction accuracy of torrential rainfall by integrating total lightning data and heavy precipitation data using an automatic method for identifying and tracking convective storm cells.

Study Configuration

• Spatial Scale: Convective storm cells, tracked areas within Japan.
• Temporal Scale: 5-minute intervals for lightning pulse frequency analysis; ~10-minute time lag for prediction.

Methodology and Data

• Models used: An adapted algorithm for identifying and tracking convective storm cells (based on Shimizu and Uyeda's approach); Cross-correlation analyses.
• Data sources: High-resolution 2D weather radar composite precipitation data (XRAIN, MLIT, Japan); Total lightning data (Japanese Total Lightning Network - JTLN).

Main Results

• The study discusses the results of correlation matrix analysis for identifying the movement of storm cells and their utilization towards spatiotemporal nowcasting of extreme rainfall.

Contributions

• Improves the prediction accuracy of torrential rainfall through the integration of total lightning data and heavy precipitation data.
• Advances spatiotemporal nowcasting capabilities for extreme rainfall events by leveraging lightning-precipitation relationships.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Mondal2026Assessing,
  author = {Mondal, Debrupa and Hobara, Yasuhide and Kikuchi, Hiroshi and Lapierre, Jeff},
  title = {Assessing the Potential of Total Lightning for Nowcasting Ground Rainfall in Summer Thunderstorms Using Automatic Density-Dependent Tracking},
  journal = {Atmosphere},
  year = {2026},
  doi = {10.3390/atmos17040364},
  url = {https://doi.org/10.3390/atmos17040364}
}