Evaluation of WRF model's lightning prediction capabilities for Sri Lanka during the second inter-monsoon

Abstract

Lightning is a grievous and oppressive weather phenomenon often accompanied by severe thunderstorms, leading to potentially lethal consequences for human life and significant damage to critical infrastructure sectors. Developing an effective lightning prediction system is crucial for public safety, aviation, and electrical power sectors. This study aims to evaluate the applicability of the WRF-based Lightning Potential Index (LPI), K-index, and Convective Available Potential Energy (CAPE) in predicting lightning during the second inter-monsoon over Sri Lanka. The WRF-ARW model version 3.9.1 was employed to produce predictions for three lightning events, utilizing various physical parameterization schemes across two nested domains with resolutions of 12 km and 4 km, respectively. The model-simulated LPI, KI, and CAPE values were assessed using the Earth Networks Global Lightning Network (ENGLN) dataset.

Results indicated that the spatial distribution of the simulated lightning events closely aligned with ground-based lightning data. There was a high correlation between the LPI index and hourly CG flash rates across the three cases, a medium correlation with the K-Index, and a low correlation with CAPE. These findings suggest that the WRF model, particularly using LPI and K-Index, is effective in capturing lightning events in Sri Lanka. Therefore, it holds potential for operational use in predicting lightning-prone regions.