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<p>Predicting thunderstorms, with their small spatial and temporal scales and complex nonlinear dynamics, poses a significant challenge in meteorology. Predicting severe thunderstorms accurately is essential for various community members. The paper employs an artificial neural network model for predicting severe thunderstorms in northeastern India during April 1st and 17th, 2018, based on meteorological data affected by thunderstorms. To evaluate the abilities with many statistical measures were used including sophisticated learning algorithms (Levenberg-Marquardt, Conjugate Gradient, Quick Propagation, Momentum, Step, and Delta-Bar-Delta) in the prediction of thunderstorms. The Levenberg-Marquardt method accurately forecasts thunderstorm-impacted surface strictures and effectively modeled hourly changes in temperature and comparative humidity, including unexpected drops and rises, one, three, and twenty-four hours in advance. It uniquely identifies nonlinear meteorological time series. Meteorologists and other real-time forecast professionals can benefit from the application of the advanced model.</p>

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Thunderstorm prediction over Eastern state of India during pre-monsoon season in 2018 using artificial neural network model

  • 期刊论文

  • 发表日期：

    2025年4月1日

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  • Nagaraju Vanganuru,
  • P. Sardar Maran,
  • L. Lakshmanan,
  • Anoop Kumar Mishra,
  • Araveti Sandeep

摘要

Predicting thunderstorms, with their small spatial and temporal scales and complex nonlinear dynamics, poses a significant challenge in meteorology. Predicting severe thunderstorms accurately is essential for various community members. The paper employs an artificial neural network model for predicting severe thunderstorms in northeastern India during April 1st and 17th, 2018, based on meteorological data affected by thunderstorms. To evaluate the abilities with many statistical measures were used including sophisticated learning algorithms (Levenberg-Marquardt, Conjugate Gradient, Quick Propagation, Momentum, Step, and Delta-Bar-Delta) in the prediction of thunderstorms. The Levenberg-Marquardt method accurately forecasts thunderstorm-impacted surface strictures and effectively modeled hourly changes in temperature and comparative humidity, including unexpected drops and rises, one, three, and twenty-four hours in advance. It uniquely identifies nonlinear meteorological time series. Meteorologists and other real-time forecast professionals can benefit from the application of the advanced model.