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Title: | Pre-monsoon lightning in Bangladesh: Separating most from least active days with thermodynamic and synoptic composites |
Authors: | Rafiuddin, M Akter, N Dewan, A Adnan, MSG Holle, RL |
Keywords: | pre-monsoon lightning;thermodynamics indices;synoptic composites;threshold value;Bangladesh |
Issue Date: | 31-May-2025 |
Publisher: | Elsevier |
Citation: | Rafiuddin, M. et al. (2025) 'Pre-monsoon lightning in Bangladesh: Separating most from least active days with thermodynamic and synoptic composites', Atmospheric Research, 325, 108261, pp. 1 - 12. doi: 10.1016/j.atmosres.2025.108261. |
Abstract: | The pre-monsoon season (March–May) in Bangladesh is the most hazardous period for lightning-related human casualties, particularly during morning and afternoon hours. This heightened risk is primarily associated with labor-intensive manual agriculture on smallholder farms. This study investigates the atmospheric conditions corresponding to the 50 most active and 50 least active pre-monsoon lightning days between 2015 and 2020. Analysis of sounding and reanalysis data reveals distinct differences across nearly all dynamic, thermodynamic, surface, and upper-air composite parameters. On the most active lightning days, the environment typically features a SWEAT index exceeding 230, a mixed-layer mixing ratio above 15 g kg^−1, and high values of the most unstable convective available potential energy (≥1580 J kg^−1), along with elevated instability—all conducive to thunderstorms with heavy rainfall. Notably, on 20 % of these active days, storm-relative environmental helicity reaches between 300 and 485 m2 s^−2, indicating a high potential for supercell thunderstorms and intense lightning activity. In contrast, the least-active lightning days are characterized by weaker storm systems. These variations are primarily driven by strong, warm, moist southwesterly winds from the Bay of Bengal, which enhance horizontal temperature gradients and atmospheric instability. Regression models identified potential instability, cloud ice water content, and cloud liquid water content as strong synoptic-scale predictors of lightning activity. Principal component analysis (PCA) further highlighted the critical role of cloud-scale thermodynamic and kinematic variables in distinguishing lightning intensity. These findings provide a foundation for developing daily lightning forecast systems, with potential benefits for public safety and protection of lightning-sensitive infrastructure. |
Description: | Data availability: GLD360 data were provided by Vaisala Inc. Researchers can request access to GLD360 data through the Vaisala Research Data Grant Program through the following link: https://www.vaisala.com/en/lp/request-vaisala-lightning-data-research-use. |
URI: | https://bura.brunel.ac.uk/handle/2438/31413 |
DOI: | https://doi.org/10.1016/j.atmosres.2025.108261 |
ISSN: | 0169-8095 |
Other Identifiers: | ORCiD: Mohammed Sarfaraz Gani Adnan https://orcid.org/0000-0002-7276-1891 Abstract number: 108261 |
Appears in Collections: | Dept of Civil and Environmental Engineering Research Papers |
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FullText.pdf | Copyright © 2025 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( https://creativecommons.org/licenses/by/4.0/ ). | 8.5 MB | Adobe PDF | View/Open |
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