The Artificial Intelligence has emerged as a cornerstone of India’s fight against climate change, specifically through indigenous innovations in disaster risk reduction. Anchored in the “Planet” pillar of the summit’s Three Sutras, India is leveraging AI to democratize climate intelligence, achieving 6km resolution village-level weather forecasts through the Bharat Forecasting System. The nation has significantly enhanced its cyclone intensity assessment using the Advanced Dvorak Technique and developed an indigenous landslide early warning system for the Himalayan regions with over 90% accuracy. These initiatives are backed by substantial investments in AI infrastructure, including a 22 PetaFLOPS high-power computing system, of which 10% is dedicated to specialized GPU-led AI research.
Key Pillars of India’s AI-Led Climate Action
Early Warning Systems: Deploying AI to provide landslide alerts up to three hours before slope failures in the Himalayas and monitoring sea-level rise.
Democratizing Forecasts: Delivering high-resolution weather predictions to nearly every Gram Panchayat via the Bharat Forecasting System.
Cyclone Intelligence: Improving path prediction accuracy up to 96 hours ahead of landfall with a 200km accuracy achieved in seconds.
Nature-Based AI Solutions: Utilizing AI-powered forest surveillance for conservation and monitoring water risk management.
MausamGPT: Developing an AI chatbot to provide real-time climate advisories and decision support for farmers and vulnerable populations.
What is the “Advanced Dvorak Technique”? The Advanced Dvorak Technique (ADT) is an AI-assisted tool used by the India Meteorological Department (IMD) to estimate the intensity of tropical cyclones using satellite imagery. Unlike traditional methods that rely on human interpretation of cloud patterns, ADT uses machine learning algorithms to analyze infrared satellite data objectively. This allows for faster and more accurate assessments of a storm’s peak wind speeds and central pressure. In the context of India’s vast coastline, ADT is a critical component of the national early warning system, enabling city planners and disaster management teams to prepare more effectively for cyclone landfalls.
Policy Relevance
India’s AI-led climate strategy represents a transition from “Siloed Disaster Response” to “Predictive Governance,” institutionalizing technology-driven resilience across the federal structure.
Strategic Impact:
Federal Climate Synergy: The deployment of 6km resolution forecasts shifts the compliance burden from state governments to local Gram Panchayats, enabling hyper-local disaster management plans under the Bharat Forecasting System.
Standardizing Indigenous Tech: The 90% accuracy in landslide warnings establishes India as a “Standard Maker” for Himalayan topography, providing a technical template for neighboring APEC and Global South nations.
Operationalizing MausamGPT: By integrating real-time climate advisories into the e-Jagriti portal, the government moves from “Information Broadcast” to a “Citizen-State Redressal” model for climate-induced economic losses.
Bridging the Implementation Gap: Dedicating 10% of high-power computing to AI research ensures that Tier-3 and Tier-4 climate-tech startups can access the GPU infrastructure needed to bypass the hardware bottlenecks identified in global PETs workshops.
Optimizing Supply Chain Deepening: AI-driven water risk management provides the granular data required for the National Crisis Management Committee to secure the raw material supply chains for high-precision manufacturing during extreme weather events.
Relevant Question for Policy Stakeholders: In what ways should 'MeitY' stress-test the '22 PetaFLOPS' high-power computing infrastructure to ensure that 96-hour cyclone predictions remain operational even during a regional 'Blackout Scenario' caused by the storm itself?
Follow the full news here: PIB: AI and Climate Action in India
