Temporal Dependencies Between Total Lightning and Rainfall in Multicellular Systems: A Predictive Approach for Torrential Rain During Summer Thunderstorms in Japan

Abstract Recently, detailed spatio‐temporal analysis utilizing X‐band multi‐parameter radar‐derived 3D volume scan and total lightning data in Japan, have revealed the peak in‐cloud (IC) lightning occurs 5–10 min prior to maximum ground rainfall in individual thunderstorm cells during heavy rainfall events. This temporal relation holds the potential for improving real‐time monitoring and nowcasting of torrential rain causing natural disaster such as flash floods. However, cell interactions such as merging and splitting of the cells are often observed in multicellular thunderstorms, which cause abrupt fluctuation in the total lightning rate and make it difficult to track the storm evolution. To address this, we propose an area‐correction method based on the lightning activity (in terms of cell area ratio before and after merging/splitting) of individual cell. Preliminary observation results of two multicellular thunderstorm events with heavy rainfall (∼100 mm/hr) that exhibited cell merging and splitting during their life cycle are demonstrated. The area‐correction resulted in a reasonable and corresponding trend in the temporal behavior of IC lightning rate and ground precipitation volume, with the peak IC rate preceding the peak ground PV by 5–10 min. We also demonstrate a promising approach for short‐term prediction of ground rainfall with high accuracy (correlation coefficient between observed and predicted PV was 0.84–0.94), by means of a moving linear regression model, using recent IC observations. These results highlight the potential of total lightning for short‐term rainfall prediction in both isolated and multicellular thunderstorms.

Authors

Institutions

Publication Details

Journal
Radio Science
Published
2026-02-01
DOI
https://doi.org/10.1029/2025rs008380
Primary Topic
Lightning and Electromagnetic Phenomena
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Temporal Dependencies Between Total Lightning and Rainfall in Multicellular Systems: A Predictive Approach for Torrential Rain During Summer Thunderstorms in Japan

Osamu Kameya, Y. Hobara, Kuniyuki Motojima, Daisuke Okano et al.
Radio Science
Lightning and Electromagnetic Phenomena
article

Temporal Dependencies Between Total Lightning and Rainfall in Multicellular Systems: A Predictive Approach for Torrential Rain During Summer Thunderstorms in Japan

Osamu Kameya, Y. Hobara, Kuniyuki Motojima, Daisuke Okano, Jeff Lapierre, Debrupa Mondal, P. Le Floch, N. Kawaguchi, H. Kikuchi, K. Shiokawa, T. Eguchi, T. Nakamura
article en

Abstract

Abstract Recently, detailed spatio‐temporal analysis utilizing X‐band multi‐parameter radar‐derived 3D volume scan and total lightning data in Japan, have revealed the peak in‐cloud (IC) lightning occurs 5–10 min prior to maximum ground rainfall in individual thunderstorm cells during heavy rainfall events. This temporal relation holds the potential for improving real‐time monitoring and nowcasting of torrential rain causing natural disaster such as flash floods. However, cell interactions such as merging and splitting of the cells are often observed in multicellular thunderstorms, which cause abrupt fluctuation in the total lightning rate and make it difficult to track the storm evolution. To address this, we propose an area‐correction method based on the lightning activity (in terms of cell area ratio before and after merging/splitting) of individual cell. Preliminary observation results of two multicellular thunderstorm events with heavy rainfall (∼100 mm/hr) that exhibited cell merging and splitting during their life cycle are demonstrated. The area‐correction resulted in a reasonable and corresponding trend in the temporal behavior of IC lightning rate and ground precipitation volume, with the peak IC rate preceding the peak ground PV by 5–10 min. We also demonstrate a promising approach for short‐term prediction of ground rainfall with high accuracy (correlation coefficient between observed and predicted PV was 0.84–0.94), by means of a moving linear regression model, using recent IC observations. These results highlight the potential of total lightning for short‐term rainfall prediction in both isolated and multicellular thunderstorms.

Radio ScienceVol. 61(2)
Yamaguchi University (JP), University of Kochi (JP), University of Electro-Communications (JP), Kiryu University (JP), Nagoya Industrial Science Research Institute (JP), Senseonics (United States) (US), National Astronomical Observatory of Japan (JP), Kyushu Tokai University (JP)
Openalex Percentile: Top 63%
Lightning and Electromagnetic Phenomena
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.