Performance assessment of WRF-ELEC and lightning potential index for improved forecasting in Odisha, India.
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| Title: | Performance assessment of WRF-ELEC and lightning potential index for improved forecasting in Odisha, India. |
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| Authors: | Mahapatra, Debasish1,2 (AUTHOR), Panda, S. K.2 (AUTHOR) subrat.atmos@curaj.ac.in, Banik, Trisanu3 (AUTHOR), Banerjee, Bijit Kumar2,4 (AUTHOR) |
| Source: | Natural Hazards. May2026, Vol. 122 Issue 9, p1-22. 22p. |
| Abstract: | Lightning represents a significant natural hazard that causes substantial loss of life and property globally, particularly in tropical and subtropical regions experiencing intense convective activity. Accurate prediction of lightning occurrence and intensity remains a critical challenge for operational weather forecasting and hazard mitigation. Recent advances in numerical weather prediction have enabled the development of specialized lightning parameterization schemes that explicitly represent electrification processes within convective clouds. This study evaluates the performance of the WRF-ELEC lightning parameterization scheme alongside the Lightning Potential Index (LPI) diagnostic for predicting lightning activity over Odisha, India, a region highly susceptible to severe convective weather. Model simulations were validated against ground-based observations from the Indian Institute of Tropical Meteorology (IITM) Lightning Location Network for four convective events: 15 June 2019, 24 June 2020, 27 July 2020, and 8 August 2021. Quantitative verification using flash origin density (FOD) from WRF-ELEC revealed superior performance compared to LPI-derived lightning density, with lower aggregate mismatch counts (maximum: 12, mean: 1.06 versus maximum: 19, mean: 2.74), reduced percentage mismatch (maximum: 50%, mean: 4.42% versus maximum: 79.17%, mean: 11.48%), and substantially lower normalized linear intensity mismatch (maximum: 4.40, mean: 0.16 versus maximum: 19.48, mean: 2.01). These results demonstrate that the WRF-ELEC scheme provides enhanced predictive capability for operational lightning forecasting and can support improved hazard mitigation strategies in regions susceptible to severe convective weather. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
| Abstract: | Lightning represents a significant natural hazard that causes substantial loss of life and property globally, particularly in tropical and subtropical regions experiencing intense convective activity. Accurate prediction of lightning occurrence and intensity remains a critical challenge for operational weather forecasting and hazard mitigation. Recent advances in numerical weather prediction have enabled the development of specialized lightning parameterization schemes that explicitly represent electrification processes within convective clouds. This study evaluates the performance of the WRF-ELEC lightning parameterization scheme alongside the Lightning Potential Index (LPI) diagnostic for predicting lightning activity over Odisha, India, a region highly susceptible to severe convective weather. Model simulations were validated against ground-based observations from the Indian Institute of Tropical Meteorology (IITM) Lightning Location Network for four convective events: 15 June 2019, 24 June 2020, 27 July 2020, and 8 August 2021. Quantitative verification using flash origin density (FOD) from WRF-ELEC revealed superior performance compared to LPI-derived lightning density, with lower aggregate mismatch counts (maximum: 12, mean: 1.06 versus maximum: 19, mean: 2.74), reduced percentage mismatch (maximum: 50%, mean: 4.42% versus maximum: 79.17%, mean: 11.48%), and substantially lower normalized linear intensity mismatch (maximum: 4.40, mean: 0.16 versus maximum: 19.48, mean: 2.01). These results demonstrate that the WRF-ELEC scheme provides enhanced predictive capability for operational lightning forecasting and can support improved hazard mitigation strategies in regions susceptible to severe convective weather. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 0921030X |
| DOI: | 10.1007/s11069-026-08116-7 |
