Evaluation and Usefulness of Lightning Forecasts Made with Lightning Parameterization Schemes Coupled with the WRF Model

Abstract

The evaluation and usefulness of lightning prediction for Indian subcontinent are demonstrated. Implementation of the lightning parameterizations based on storm parameters, in Weather Research and Forecasting (WRF), with different microphysics schemes are carried out. With the availability of observed lightning measurements over Maharashtra from the lightning detection network (LDN), lightning cases have been identified during pre-monsoon season of 2016–2018. Lightning parameterization based on cloud top height defined by reflectivity threshold factor of 20 dBZ is chosen. Initial analysis is carried out for sixteen lightning events with four microphysical schemes for the usefulness in lightning prediction. Objective analysis is carried out and quantitative model performance (skill scores) is assessed based on observed data. The skills are evaluated for 10 and 50 km square box from the 1 km domain. There is good POD of 0.86, 0.82, 0.85, 0.84 and false alarm ratio (FAR) of 0.28, 0.25, 0.29, 0.26 from WSM6, Thompson, Morrison and WDM6 respectively. There is an overestimation in lightning flash with a spatial and temporal shift. The fractional skill score is evaluated as a function of spatial scale with neighbourhoods from 25 to 250 km. These high skill scores and high degree of correlation between observations and model simulation gives confidence to use the system for real-time operational forecast over India. The skill for 2019 and 2020 pre-monsoon are calculated to address the predictability of operational lightning prediction over India.

A machine learning approach for prediction of seasonal lightning density in different lightning regions of India

“…Such models have gained high popularity in recent past for their accuracy and interpretability at the same time, that is, performance without being confined within the black box of ML (Johari et al ., 2009; Silva et al ., 2022). Studies (Lynn and Yair, 2010) have reported good prospects of WRF coupled models for accurate real‐time forecast of lightning activities for example, Vani et al ., 2022 proposed a model with a POD of 0.90 and FAR of 0.64. The proposed model attempts to device a single model for the first time over entire Indian region.…”

“…Price and Rind (1992) based on cloud top height and vertically integrated ice water path reported excellent accuracy in recreating the spatial lightning pattern. Vani et al ., 2022 evaluated lightning parameterization based on cloud top height defined by reflectivity threshold for 16 pre‐monsoon storms over Maharashtra. The study reported a false alarm ratio of 0.28, 0.25, 0.29, 0.26 from WSM6, Thompson, Morrison and WDM6 parameterizations respectively.…”

Seasonal and Regional Distribution of Lightning Fraction Over Indian Subcontinent

“…One commonly used lightning parameterization in numerical models is based on relating the convective cloud top height and the prevailing updrafts, along with the ratio between intra‐cloud and cloud‐to‐ground lightning flashes from observations (Mohan et al., 2021; Price & Rind, 1992, 1993; Vani et al., 2022; Wong et al., 2013). In the numerical models, the ratio can assume climatology (e.g., that already incorporated over the conterminous United States by Boccippio et al., 2001).…”