A New Thunderstorm Identification Algorithm Based on Total Lightning Activity

Huang, Yijun; Fan, Yadong; Li, Cai; Cheng, Si; Wang, Jianguo

doi:10.1029/2021ea002079

Cited by 2 publications

(2 citation statements)

References 43 publications

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“…However, In the future, they [42,68] plan that the number of case studies will be expanded to encompass numerous hail events. Comparably, this research [43,69] raises several doubts concerning the spatial size employed in this model [70], and additional research into the model's spatial scale could lead to improved prediction models for outages caused by thunderstorms.…”

Section: Discussionmentioning

confidence: 96%

“…Statistical Methods [43] the 8-connectivity combinatorial method proposed for intracloud pulses and cloud-to-ground stocks uses fixed thresholding and included datasets of 149041 on May 15, 242673 on May 16, and 76958 on May 24, 2014. However [44], two statistical techniques, respectively, are: Using During 2009 and 2012 meteorological data from 34 sites, and in 2018, a second technique was presented that uses total days with lightning minus the total number of days without it reported by Total days with thunderstorms reported by weather stations, as well as WWLLN.…”

Section: 3mentioning

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: 96%

Section: 3mentioning

confidence: 99%

Thunderstorms Prediction Using Satellite Images

Amjad¹,

Malik²,

Ghous³

et al. 2023

ijisct

View full text Add to dashboard Cite

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Relationship between radar reflectivity thresholds and very low frequency/low frequency total lightning for thunderstorm identification

Huang,

Wang,

Cai

et al. 2024

High Voltage

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To improve our knowledge of the spatio‐temporal correspondence between radar reflectivity and VLF/LF total lightning data, this paper proposes indexes to quantify the horizontal distribution and temporal evolution characteristics between radar composite reflectivity images and total lightning density map, lightning clusters and radar cells with different radar reflectivity thresholds (30, 35, 40, 45 and 50 dBZ), respectively. It is found that the number of radar grid cells with radar reflectivity over 30 dBZ is ten times the number of lightning grid cells. At the identification stage, the lightning activity regions in a radar cell account for less than 30% using thresholds of 30, 35 and 40 dBZ, respectively, and the radar cell has more than one lightning cluster, which means that the mesoscale convective systems typically have more than one draft, and drafts are only small part of the convection. The majority of the centroid deviations is less than 10 km, indicating that there are some shifts between electrically active regions and convective regions. Results suggest that VLF/LF total lightning data are consistent with radar data and total lightning data can be used individually on a smaller spatio‐temporal scale than radar data.

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A New Thunderstorm Identification Algorithm Based on Total Lightning Activity

Abstract: Thunderstorms have a severe impact on many sectors, such as agriculture, aviation, infrastructures and power systems (Houston et al., 2015). Lightning caused by thunderstorms (Hayward et al., 2020) is responsible for damages and interruptions of power system (

Cited by 2 publications

References 43 publications

Thunderstorms Prediction Using Satellite Images

Thunderstorms Prediction Using Satellite Images

Relationship between radar reflectivity thresholds and very low frequency/low frequency total lightning for thunderstorm identification

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