Improving Cloud Burst Prediction with Meteorological Analysis Driven by Machine Learning

An innovative “Improving cloud burst prediction with Meteorological Analysis driven by Machine Learning” initiative, developed within the Disaster Management domain by the Ministry of Power. This system leverages the capabilities of machine learning to comprehensively analyze a wide range of meteorological parameters and weather patterns, with the primary aim getting the result of whether it is yes or no. Cloudbursts, characterized by their abrupt and intense rainfall, pose significant risks, including flash floods, landslides, and potential harm to both infrastructure and human lives. Thus to combat this issue that may arise we have also provided the required preventive measures that is to be taken at the event of such crisis. The Meteorological Department uses this indicator to determine the likelihood of a cloud burst occurring in order to communicate with the public. The Indian subcontinent, noted for its diverse terrain and distinct monsoon patterns, is under increasing threat from these extreme precipitation events. As climate change accelerates, understanding and properly anticipating these occurrences has become crucial for catastrophe management and mitigation. This conversation highlights the growing concern over cloudbursts and severe rainfall in India, highlighting the critical need for improved forecast and analysis methodologies.

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Published
2024-11-06
DOI
https://doi.org/10.1109/icstsdg61998.2024.11026751
Citations
1
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.27
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article

Improving Cloud Burst Prediction with Meteorological Analysis Driven by Machine Learning

S Jagadeeshwaran, Sivarama Krishnan, R. D.
1 citations
Traffic Prediction and Management Techniques
0.27
article

Improving Cloud Burst Prediction with Meteorological Analysis Driven by Machine Learning

S Jagadeeshwaran, Sivarama Krishnan, R. D.
article en
1 citations

Abstract

An innovative “Improving cloud burst prediction with Meteorological Analysis driven by Machine Learning” initiative, developed within the Disaster Management domain by the Ministry of Power. This system leverages the capabilities of machine learning to comprehensively analyze a wide range of meteorological parameters and weather patterns, with the primary aim getting the result of whether it is yes or no. Cloudbursts, characterized by their abrupt and intense rainfall, pose significant risks, including flash floods, landslides, and potential harm to both infrastructure and human lives. Thus to combat this issue that may arise we have also provided the required preventive measures that is to be taken at the event of such crisis. The Meteorological Department uses this indicator to determine the likelihood of a cloud burst occurring in order to communicate with the public. The Indian subcontinent, noted for its diverse terrain and distinct monsoon patterns, is under increasing threat from these extreme precipitation events. As climate change accelerates, understanding and properly anticipating these occurrences has become crucial for catastrophe management and mitigation. This conversation highlights the growing concern over cloudbursts and severe rainfall in India, highlighting the critical need for improved forecast and analysis methodologies.

Karpagam Academy of Higher Education (IN)
Climate action
Openalex Percentile: Top 39%
Traffic Prediction and Management Techniques
0.27
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Improving Cloud Burst Prediction with Meteorological Analysis Driven by Machine Learning — S Jagadeeshwaran, Sivarama Krishnan, et al. · (2024) | TGRS Research Map | TGRS