Development of a Storm-Tracking Algorithm for the Analysis of Radar Rainfall Patterns in Athens, Greece

This research work focuses on the development and application of a storm-tracking algorithm for identifying and tracking storm cells. The algorithm first identifies storm cells on the basis of reflectivity thresholds and then matches the cells in the tracking procedure on the basis of their geometrical characteristics and the distance within the weather radar image. A sensitivity analysis was performed to evaluate the preferable thresholds for each case and test the algorithm’s ability to perform in different time step resolutions. Following this, we applied the algorithm to 54 rainfall events recorded by the National Technical University X-Band weather radar, the rainscanner system, from 2018 to 2023 in the Attica region of Greece. Testing of the algorithm demonstrated its efficiency in tracking storm cells over various time intervals and reflecting changes such as merging or dissipation. The results reveal the predominant southwest-to-east storm directions in 40% of cases examined, followed by northwest-to-east and south-to-north patterns. Additionally, stratiform storms showed slower north-to-west trajectories, while convective storms exhibited faster west-to-east movement. These findings provide valuable insights into storm behavior in Athens and highlight the algorithm’s potential for integration into nowcasting systems, particularly for flood early warning systems.

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Publication Details

Journal
Water
Published
2024-10-12
DOI
https://doi.org/10.3390/w16202905
Citations
4
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
1.13
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article

Development of a Storm-Tracking Algorithm for the Analysis of Radar Rainfall Patterns in Athens, Greece

Apollon Bournas, Evangelos Baltas
4 citations
Water
Flood Risk Assessment and Management
1.13
article

Development of a Storm-Tracking Algorithm for the Analysis of Radar Rainfall Patterns in Athens, Greece

Apollon Bournas, Evangelos Baltas
article en
4 citations

Abstract

This research work focuses on the development and application of a storm-tracking algorithm for identifying and tracking storm cells. The algorithm first identifies storm cells on the basis of reflectivity thresholds and then matches the cells in the tracking procedure on the basis of their geometrical characteristics and the distance within the weather radar image. A sensitivity analysis was performed to evaluate the preferable thresholds for each case and test the algorithm’s ability to perform in different time step resolutions. Following this, we applied the algorithm to 54 rainfall events recorded by the National Technical University X-Band weather radar, the rainscanner system, from 2018 to 2023 in the Attica region of Greece. Testing of the algorithm demonstrated its efficiency in tracking storm cells over various time intervals and reflecting changes such as merging or dissipation. The results reveal the predominant southwest-to-east storm directions in 40% of cases examined, followed by northwest-to-east and south-to-north patterns. Additionally, stratiform storms showed slower north-to-west trajectories, while convective storms exhibited faster west-to-east movement. These findings provide valuable insights into storm behavior in Athens and highlight the algorithm’s potential for integration into nowcasting systems, particularly for flood early warning systems.

WaterVol. 16(20)
National Technical University of Athens (GR)
Climate action
Openalex Percentile: Top 23%
Flood Risk Assessment and Management
1.13
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