On the prediction and analysis of pre-monsoon thunderstorms and their meteorological associations

Nag, Atanu

doi:10.1007/s12648-019-01407-9

Cited by 1 publication

(2 citation statements)

References 7 publications

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“…During the Australian Black Summer in the southeastern Australian province of Victoria, no lightning-caused forest fires were documented. Comparably [9], They apply the BEADS algorithm in conjunction with CEEMDAN-SG for the first time to eliminate noise in the full frequency domain in the 3D AEFS. This can improve the signal-to-noise ratio (SNR) of AEFS, reduce the error in measuring the electric field, and make it possible to analyze the change in AEFS more accurately.…”

Section: Discussionmentioning

confidence: 99%

“…Statistical methods utilize historical data on thunderstorms, assuming that future storms will be like those in the past. The primary objective of analyzing historical weather data is to identify those characteristics of thunderstorms that serve as reliable predictors of future events [9]. After establishing these connections, accurate data can be utilized to predict future situations confidently.…”

Section: Methodsmentioning

confidence: 99%

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Thunderstorms Prediction Using Satellite Images

Amjad¹,

Malik²,

Ghous³

et al. 2023

ijisct

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Human life and property are put at risk by lightning, heavy hail, and strong winds caused by thunderstorms. Accurate prediction of thunderstorms has long been a difficult problem. In difference from conventional methods, the modern methods for predicting thunderstorms utilize a combination of computer models, observation (via the use of radars and satellite photos), and modern knowledge and patterns employed by thunderstorms stations. Observations: Using these methods, it is possible to make reasonably accurate predictions. Prediction models based on complex formulas run the majority of forecasting computer models. Artificial neural networks, machine learning, deep learning, and statistics are all examples of adaptive systems that alter their structure in response to information flowing through the network. In this reviewed paper, different Artificial intelligence techniques are used such as machine learning, deep learning, and ANN (Artificial neural network). Different statistical models were presented to predict thunderstorm systems. Various researchers achieved technical milestones by presenting statistical methods on thunderstorm systems using satellite data.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%