Analysis of convective cell evolution with split and merge events using a graph-based methodology

Abstract. Convective storms are associated with several hazards, including heavy rainfall, hail, and lightning, which pose severe risks to society. While the nowcasting (i.e., short-term forecasting from 5 min to 6 h) of storm locations has been extensively studied, nowcasting storm development remains a challenge. Nowcasting rapid, non-linear convective storm evolution requires finding connections between observations and storm evolution and representing them in the nowcasting model. Convective cell identification and tracking algorithms are commonly used for nowcasting and analysis of convective storms. This analysis is complicated by the splits and merges that occur in the cell tracks, either due to the physical processes or data quality issues. Consequently, the splits and merges are often excluded from the analysis. Here, we present a methodology for analyzing cell development around time of interest that explicitly includes the splits and merges in the analysis. The time of interest can be the time when the nowcast is created or the occurrence of some fingerprint of meteorological processes, for example, Zdr columns. We represent the cell tracks as directed graphs where we select event nodes to represent the times of interest. For each event node, a subgraph of related cells from both the past and future of the event node is selected. We propose rules for selecting the subgraphs with the aim of retaining the available information in the subgraph at each time step. Once selected, the cell features in the subgraphs are aggregated into time series for analysis. We demonstrate the methodology through case studies of convective storms with Zdr column features signalling updrafts and apply it to analyze split and merge events using three years of warm-season (MJJAS) operational radar data from the Swiss national weather radar network, with a focus on the total rainfall amount produced by the cells. Splits and merges occur in 7.2 % of all identified cells, and are more frequent in cells with larger vertically integrated liquid (17.9 %) or containing Zdr columns (11.7 %). Typically, cell mergers are associated with growth in total rainfall and cell area, and cell splits are associated with decrease in total rainfall.

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Journal
Atmospheric measurement techniques
Published
2026-03-16
DOI
https://doi.org/10.5194/amt-19-1853-2026
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00

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article

Analysis of convective cell evolution with split and merge events using a graph-based methodology

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Atmospheric measurement techniques
Meteorological Phenomena and Simulations
article

Analysis of convective cell evolution with split and merge events using a graph-based methodology

Jenna Ritvanen, Dmitri Moisseev, Martin Aregger, Seppo Pulkkinen, Alessandro Hering, Urs Germann
article en

Abstract

Abstract. Convective storms are associated with several hazards, including heavy rainfall, hail, and lightning, which pose severe risks to society. While the nowcasting (i.e., short-term forecasting from 5 min to 6 h) of storm locations has been extensively studied, nowcasting storm development remains a challenge. Nowcasting rapid, non-linear convective storm evolution requires finding connections between observations and storm evolution and representing them in the nowcasting model. Convective cell identification and tracking algorithms are commonly used for nowcasting and analysis of convective storms. This analysis is complicated by the splits and merges that occur in the cell tracks, either due to the physical processes or data quality issues. Consequently, the splits and merges are often excluded from the analysis. Here, we present a methodology for analyzing cell development around time of interest that explicitly includes the splits and merges in the analysis. The time of interest can be the time when the nowcast is created or the occurrence of some fingerprint of meteorological processes, for example, Zdr columns. We represent the cell tracks as directed graphs where we select event nodes to represent the times of interest. For each event node, a subgraph of related cells from both the past and future of the event node is selected. We propose rules for selecting the subgraphs with the aim of retaining the available information in the subgraph at each time step. Once selected, the cell features in the subgraphs are aggregated into time series for analysis. We demonstrate the methodology through case studies of convective storms with Zdr column features signalling updrafts and apply it to analyze split and merge events using three years of warm-season (MJJAS) operational radar data from the Swiss national weather radar network, with a focus on the total rainfall amount produced by the cells. Splits and merges occur in 7.2 % of all identified cells, and are more frequent in cells with larger vertically integrated liquid (17.9 %) or containing Zdr columns (11.7 %). Typically, cell mergers are associated with growth in total rainfall and cell area, and cell splits are associated with decrease in total rainfall.

Atmospheric measurement techniquesVol. 19(5)
University of Bern (CH), Finnish Meteorological Institute (FI), Federal Office of Meteorology and Climatology MeteoSwiss (CH), University of Helsinki (FI)
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Väisälän Rahasto
Climate action
Openalex Percentile: Top 13%
Meteorological Phenomena and Simulations
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