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Lightning Danger Indexing in the Changing Climate Cover

Lightning Danger Indexing in the Changing Climate

Quaestiones Geographicae
Volume 44 (2025): Issue 3 (September 2025)
By: Rafał Iwański and  Agnieszka Wypych  
Open Access
|Aug 2025

Figures & Tables

Fig. 1.

The broad PERUN sensor’s layout in Poland (red dots) and neighbouring country sensors that contribute to the PERUN detections analysed in this paper (white dots). Please note that this map does not present all the changes in the locations of the receiving stations within the country during the network’s history.
The broad PERUN sensor’s layout in Poland (red dots) and neighbouring country sensors that contribute to the PERUN detections analysed in this paper (white dots). Please note that this map does not present all the changes in the locations of the receiving stations within the country during the network’s history.

Fig. 2.

The monthly total CG Heat Maps with Convex Hull Function centroids during 2002–2023. Based on CG lightning stroke data derived from the PERUN lightning detection and localisation network and compatible sensors located in the neighbouring countries.
The monthly total CG Heat Maps with Convex Hull Function centroids during 2002–2023. Based on CG lightning stroke data derived from the PERUN lightning detection and localisation network and compatible sensors located in the neighbouring countries.

Fig. 3.

The monthly total CG lightning stroke density spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on CG lightning stroke data derived from the PERUN lighting detection and localisation network and compatible sensors located in the neighbouring countries.
The monthly total CG lightning stroke density spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on CG lightning stroke data derived from the PERUN lighting detection and localisation network and compatible sensors located in the neighbouring countries.

Fig. 4.

A – The monthly total CG+ intensity spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on CG lightning stroke data derived from the PERUN lightning detection and localisation network, and compatible sensors located in the neighbouring countries. B – The monthly total CG-intensity spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on CG lightning stroke data derived from the PERUN lightning detection and localisation network, and compatible sensors located in the neighbouring countries.
A – The monthly total CG+ intensity spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on CG lightning stroke data derived from the PERUN lightning detection and localisation network, and compatible sensors located in the neighbouring countries. B – The monthly total CG-intensity spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on CG lightning stroke data derived from the PERUN lightning detection and localisation network, and compatible sensors located in the neighbouring countries.

Fig. 5.

A – The monthly total CG+ 9th decile spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on lightning stroke data derived from the PERUN lighting detection and localisation network and compatible sensors located in the neighbouring countries. B – The monthly total CG– 9th decile spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on lightning stroke data derived from the PERUN lighting detection and localisation network and compatible sensors located in the neighbouring countries.
A – The monthly total CG+ 9th decile spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on lightning stroke data derived from the PERUN lighting detection and localisation network and compatible sensors located in the neighbouring countries. B – The monthly total CG– 9th decile spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on lightning stroke data derived from the PERUN lighting detection and localisation network and compatible sensors located in the neighbouring countries.

Fig. 6.

The monthly total CG LDI spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on lightning stroke data derived from the PERUN lighting detection and localisation network and compatible sensors located in the neighbouring countries.
The monthly total CG LDI spatial variability in km2. Computed for 0.2° × 0.2° grid cells during 2002–2023. Based on lightning stroke data derived from the PERUN lighting detection and localisation network and compatible sensors located in the neighbouring countries.

Fig. 7.

The mutual relation between 2002 and 2023 CG lightning stroke density (left panel – both lightning stroke polarities]) and LDI (right panel) of the same period.
The mutual relation between 2002 and 2023 CG lightning stroke density (left panel – both lightning stroke polarities]) and LDI (right panel) of the same period.

Fig. 8.

Annual sums of lightning strokes acc. to types for Poland in the 2002–2023 period.
Annual sums of lightning strokes acc. to types for Poland in the 2002–2023 period.

Linear regression equation (y = ax + b) and determination coefficient (R2) calculated for both CG lightning stroke polarities throughout all analysed periods_

MonthLightning stroke polarisation
CG+CG–
y = ax + bR2y = ax + bR2
Januaryy = 13.879x + 3.660.6181y = –11.31x – 64.4670.2391
Februaryy = 14.863x + 13.610.3034y = –10.373x – 30.1070.2824
Marchy = 11.839x + 147.990.4005y = –6.4458x – 164.470.1545
Aprily = 22.99x + 148.220.4399y = –7.3853x – 226.650.4459
Mayy = 12.473x + 233.570.6575y = –5.1407x – 270.090.2713
Juney = 15.614x + 2160.5637y = –8.3806x – 247.830.3875
Julyy = 13.932x + 221.910.6835y = –12.032x – 227.910.6370
Augusty = 10.588x + 241.130.5576y = –6.3636x – 259.840.4303
Septembery = 13.974x + 206.040.6347y = –7.6922x – 238.830.6388
Octobery = 7.1687x + 210.760.3345y = –4.3605x – 245.870.1555
Novembery = 9.7656x + 94.1670.3599y = –16.427x – 49.2580.5741
Decembery = 13.813x + 31.5650.5812y = –12.436x – 67.1130.3457
DOI: https://doi.org/10.14746/quageo-2025-0029 | Journal eISSN: 2081-6383 | Journal ISSN: 2082-2103
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Language: English
Page range: 95 - 109
Submitted on: Oct 3, 2025
|
Published on: Aug 7, 2025
Published by: Adam Mickiewicz University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
lightning,
thunderstorm,
severe weather risk,
climate change,
Poland
Related subjects:
Geosciences,
Geography

© 2025 Rafał Iwański, Agnieszka Wypych, published by Adam Mickiewicz University
This work is licensed under the Creative Commons Attribution 4.0 License.

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