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This study investigates rainfall patterns in the subdivisions of Southern India from 1901 to 2015, focusing on Kerala, Telangana, Tamil Nadu, coastal Karnataka, and Andhra Pradesh. Using deep Long Short-Term Memory (LSTM) neural networks, we analyzed historical climate data to uncover complex patterns and variations in rainfall. The results provide insights into the intricacies of rainfall distribution in these regions, highlighting both consistent and fluctuating trends. Coastal Karnataka and Kerala exhibit higher and more consistent rainfall, while Tamil Nadu and Telangana show greater variability. The study employs advanced statistical methods and data visualization tools aiding in the development of informed strategies for agriculture, hydrology, and environmental management. These findings are crucial for policymakers and researchers in crafting sustainable water management practices and resilient agricultural strategies amidst climate change. The current study emphasizes the need for adaptive techniques to address specific climate conditions and adaptive strategies to achieve resilient growth in the aspect of a changing climate.

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A Deep Dive into Southern India’s Rainfall: LSTM Perspectives

  • 会议论文

  • 发表日期：

    2025年

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  • Megha Dhaka,
  • Jeevika Rajput,
  • Yajnaseni Dash,
  • Ajith Abraham

摘要

This study investigates rainfall patterns in the subdivisions of Southern India from 1901 to 2015, focusing on Kerala, Telangana, Tamil Nadu, coastal Karnataka, and Andhra Pradesh. Using deep Long Short-Term Memory (LSTM) neural networks, we analyzed historical climate data to uncover complex patterns and variations in rainfall. The results provide insights into the intricacies of rainfall distribution in these regions, highlighting both consistent and fluctuating trends. Coastal Karnataka and Kerala exhibit higher and more consistent rainfall, while Tamil Nadu and Telangana show greater variability. The study employs advanced statistical methods and data visualization tools aiding in the development of informed strategies for agriculture, hydrology, and environmental management. These findings are crucial for policymakers and researchers in crafting sustainable water management practices and resilient agricultural strategies amidst climate change. The current study emphasizes the need for adaptive techniques to address specific climate conditions and adaptive strategies to achieve resilient growth in the aspect of a changing climate.