A Review of Ancient and Modern Rainfall Prediction Methods over Indian Region

Authors

  • Jaya Yadav Multidisciplinary Centre of Geoinformatics, Delhi Technological University, Delhi, India Author
  • Kailash Chandra Tiwari Multidisciplinary Centre of Geoinformatics, Delhi Technological University, Delhi, India Author
  • Ashim Kumar Mitra SATMET, Indian Meteorological Department, Delhi, India Author

Keywords:

Brihat Samhita, Ancient Meteorology, Machine Learning, Rainfall prediction

Abstract

Weather has been studied for a long time. The major milestone for modern meteorol-ogy started with the invention of weather instruments. However, the various aspects of meteorology prior to that, here referred to as ancient meteorology, were written down in many ancient scriptures and have remained unfamiliar till recent times. These texts have references to hydrologic processes, including rainfall and its prediction. One such text is Brihat Samhita, written around 500 A.D. by Varaha Mihira, with great details of the atmosphere for rainfall prediction. A rigorous discussion on the features of processes of ancient meteorology, especially rainfall, from the Brihat Samhita is missing. There are many variables that determine rainfall. Clouds are a key component among them and their types have been given emphasis for rainfall prediction by ancient as well as mod-ern meteorology. Cloud types can be visually identified, physically or in meteorological data such as satellites, but that is more of a qualitative approach. Various cloud prod-ucts are available for determining the presence of clouds in satellite images. But defining cloud types quantitatively from the same is still difficult and thereafter affecting rain-fall prediction. However, Artificial Intelligence/Machine Learning (AI/ML) techniques have emerged as a new option for development of quantitative approach from large data such as satellite data. Thus, this review paper discusses the aspects of rainfall predic-tion, in the ancient and the modern eras, and further use of AI/ML techniques for cloud classification from satellite data.

 

 

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2026-07-20

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