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.
Authors
- S Jagadeeshwaran
- Sivarama Krishnan (ORCID: https://orcid.org/0000-0002-6163-7799)
- R. D.
Institutions
- Karpagam Academy of Higher Education (IN)
Publication Details
- 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