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Performance of Lightning Potential Index, Lightning Threat Index, and the Product of CAPE and Precipitation in the WRF Model.
In: Earth & Space Science, Jg. 10 (2023-09-01), Heft 9, S. 1-16
Online
academicJournal
Zugriff:
Lightning is a naturally occurring phenomenon with significant socioeconomic and environmental impacts, underlining the need for the application of advanced methods to predict it. This study aims to evaluate the performance of the Weather Research and Forecasting (WRF) model in the prediction of the lightning potential index (LPI), the lightning threat index (LTI), and the product of convective available potential energy (CAPE) and precipitation (CAPE × P). Based on the intensity of convection and the number of lightning flashes, we simulated seven thundercloud events that occurred in Tehran between 2008 and 2013. The simulated LPI, LTI, and CAPE × P values are compared both qualitatively and quantitatively against ground‐based lighting data obtained from the world wide lightning location network (WWLLN). LPI, LTI, and CAPE × P predict the location of lightning with relatively good accuracy, although LPI outperforms LTI and CAPE × P. We also compared the simulated area‐averaged LPI, LTI, and CAPE × P against the number of lightning flashes from the WWLLN data, based on which LPI shows a better performance. Overall, LPI can be used as an effective index for the prediction of lightning. As LPI is based on cloud microphysics and LTI and CAPE × P are thermodynamic‐based methods, a better performance of LPI implies that a method based on the microphysical approach can better predict lightning. The performance of LPI, LTI, and CAPE × P is also sensitive to the horizontal resolution of model simulations, with a considerable improvement in simulations with higher horizontal resolutions. Plain Language Summary: Lightning is a naturally occurring discharge of electricity that poses a potential threat to people in open areas and infrastructure and may ignite wildfires, underlining the need for improved understanding and prediction of this phenomenon. We aim to evaluate the performance of three lightning prediction methods, which include the lightning potential index (LPI), the lightning threat index (LTI), and the product of convective available potential energy (CAPE) and precipitation (CAPE × P). The evaluation was conducted by the comparison of these lightning prediction methods in the Weather Research and Forecasting (WRF) model against ground‐based lighting data obtained from the world wide lightning location network (WWLLN). Based on the intensity of convection and the number of lightning flashes, we simulated seven thundercloud events that occurred in Tehran between 2008 and 2013. LPI, LTI, and CAPE × P predict the location and the number of lightning flashes with relatively good accuracy, with a better performance of LPI developed based on the microscale structure of clouds compared to LTI and CAPE × P developed based on thermodynamic laws. The performance of LPI, LTI, and CAPE × P shows better forecasting skills in simulations with higher horizontal resolutions. Key Points: Lightning potential index (LPI) outperforms lightning threat index (LTI) and CAPE × P in terms of the prediction of the location and the number of lightningLPI is based on the microphysical approach and can better predict lightningThe performance of LPI, LTI, and CAPE × P is improved in simulations with higher horizontal resolutions [ABSTRACT FROM AUTHOR]
Titel: |
Performance of Lightning Potential Index, Lightning Threat Index, and the Product of CAPE and Precipitation in the WRF Model.
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Autor/in / Beteiligte Person: | Saleh, Narges ; Gharaylou, Maryam ; Farahani, Majid M. ; Alizadeh, Omid |
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Zeitschrift: | Earth & Space Science, Jg. 10 (2023-09-01), Heft 9, S. 1-16 |
Veröffentlichung: | 2023 |
Medientyp: | academicJournal |
ISSN: | 2333-5084 (print) |
DOI: | 10.1029/2023EA003104 |
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