Cloud-to-Ground Lightning in Cities: Seasonal Variability and Influential Factors

• Published in: Earth systems and environment 2024-06, Vol.8 (2), p.545-560
• Main Authors: Dewan, Ashraf, Islam, K. M. Ashraful, Enan, Muhammad Esmat, Fariha, Tanzim Rahman, Rafiuddin, M., Adnan, Mohammed Sarfaraz Gani
• Format: Article
• Language: English
• Subjects: Aerosols; Bivariate analysis; Cities; Climate; Climate Change/Climate Change Impacts; Climate science; Convective precipitation; Earth and Environmental Science; Earth Sciences; Earth System Sciences; Environmental Science and Engineering; Fatalities; Geography; Hazards; Hydrometeorology; Land use; Lightning; Lightning detection; Metropolitan areas; Monitoring/Environmental Analysis; Original Article; Particulate emissions; Particulate matter; Pollution; Population density; Precipitation; Property damage; Public policy; Regression analysis; Seasonal variations; Sensitivity analysis; Surface temperature; Thunderstorms; Urban areas; Urban environments; Urbanization; Weather hazards; Weather patterns
• ISSN: 2509-9426; 2509-9434
• DOI: 10.1007/s41748-024-00372-6

Urban-induced land use changes have a significant impact on local weather patterns, leading to increased hydro-meteorological hazards in cities. Despite substantial threats posed to humans, understanding atmospheric hazards related to urbanisation, such as thunderstorms, lightning, and convective precipitation, remains unclear. This study aims to analyse seasonal variability of cloud-to-ground (CG) lightning in the five large metropolitans in Bangladesh utilising six years (2015–2020) of Global Lightning Detection Network (popularly known as GLD360) data. It also investigates factors influencing CG strokes. The analysis revealed substantial seasonal fluctuations in CG strokes, with a noticeable increase in lightning activity during the pre-monsoon months from upwind to metropolitan areas across the five cities. Both season and location appear to impact the diurnal variability of CG strokes in these urban centres. Bivariate regression analysis indicated that precipitation and particulate matter (PM) significantly influence lightning generation, whilst population density, urban size, and mean surface temperature have negligible effects. A sensitivity test employing a random forest (RF) model underscored the pivotal role of PM in CG strokes in four of the five cities assessed, highlighting the enduring impact of extreme pollution on lightning activity. Despite low causalities from CG lightning, the risk of property damage remains high in urban environments. This study provides valuable insights for shaping public policies in Bangladesh, a globally recognised climate hotspot.