Union Minister of State (Independent Charge) for Science & Technology and Earth Sciences, Dr. Jitendra Singh in a written reply in the Rajya Sabha informed about advancement in weather forecasting systems.
The Ministry of Earth Sciences (MoES) explores integrating Artificial Intelligence (AI) technologies into weather forecasting systems in addition to physics-based numerical models. This initiative is part of a broader strategy to enhance the accuracy and efficiency of meteorological predictions, which are crucial for various sectors, including agriculture, disaster management, and urban planning. The key initiatives, future plans, and innovative projects are as follows:
Collaborative Research Across Institutes: Institutions under MoES are actively working to incorporate AI/Machine Learning (ML) methodologies into their research activities and operational frameworks. This collaborative approach ensures a comprehensive application of AI technologies across Earth Sciences.
Achievements and outcomes of AI and ML in the research and development of weather prediction are provided below:
Improved the short-range precipitation forecast in 1-day, 2-day, and 3-day lead times with a reduction in bias.
Developed high-resolution (300 meters) urban gridded meteorological datasets for temperature and precipitation.
Developed the time-varying Normalized Difference Urbanization Index with a spatial resolution of 30 meters from 1992-2023.
Developed very high-resolution precipitation datasets for verification purposes.
To monitor and predict Tropical Cyclone Heat Potential (TCHP) using AI/ML methodologies.
The AI/ML is used to correct the bias of the NWP model products.
The Ministry has established a dedicated virtual center on AI/ML/Deep Learning (DL) at the Indian Institute of Tropical Meteorology (IITM) in Pune. This center focuses on leveraging AI, ML, and DL techniques for advancements in Earth Sciences. It has already developed several AI/ML-based applications tailored for localized predictions and the analysis of weather and climate patterns.
