Evaluate WRF-based Lightning Potential Index (LPI) lightning parameterization over Sri Lanka during second inter-monsoon in 2018

It is important to develop accurate and reliable lightning prediction system that can be contributed towards the safety of life, both concerning forecasting for the public safety and safety of aviation and electrical power. This study aims to evaluate WRF-based Lightning Potential Index(LPI) lightni...

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Detalhes bibliográficos
Autor: Premathilake, Jayasinghe Sepalage Darshana Shamil
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:Brasil
Recursos:Instituto Superior de Educação Vera Cruz (VeraCruz)
Repositorio:Revista Veras
Idioma:inglés
OAI Identifier:oai:ojs2.ojs.brazilianjournals.com.br:article/66057
Acesso em linha:https://ojs.brazilianjournals.com.br/ojs/index.php/BRJD/article/view/66057
Access Level:acceso abierto
Palavra-chave:lightning prediction
LPI
Sri Lanka
WRF model
Descrição
Resumo:It is important to develop accurate and reliable lightning prediction system that can be contributed towards the safety of life, both concerning forecasting for the public safety and safety of aviation and electrical power. This study aims to evaluate WRF-based Lightning Potential Index(LPI) lightning parameterization and its applicability for predicting lightning over Sri Lanka during the second inter-monsoon. The WRF-ARW model 3.9.1 was used to produce predictions for three lightning events with various physical parameterization schemes with two nested domains with a resolution of 12km and 4km respectively. The model simulated LPI values were evaluated using the Earth Networks Global Lightning (ENGLN) dataset. Results show corresponding lightning simulations were produced with spatial distribution aligned with ground-based lightning data. Results consistently show a high correlation of the LPI index with an hourly CG flash rate over the three cases. Moreover, the WRF model was able to capture the lightning using LPI in Sri Lanka, suggesting that it can be used operationally to predict lightning potential region.