Admin Team
14 May

AI AND CLIMATE ACTION IN INDIA

Introduction

Climate change has emerged as a major challenge affecting ecosystems, agriculture, livelihoods, infrastructure, and disaster resilience across the world. In this context, Artificial Intelligence (AI) is increasingly being integrated into climate adaptation and mitigation strategies. India is leveraging AI technologies for weather forecasting, disaster risk reduction, climate modelling, flood forecasting, forest surveillance, groundwater mapping, and sustainable urban governance.The issue gained attention during the India-AI Impact Summit 2026, hosted at Bharat Mandapam, New Delhi, from 16–20 February 2026. The summit is significant as it is the first global AI summit hosted in the Global South, anchored around the pillars of People, Planet, and Progress.


AI-Driven Climate and Disaster Resilience in India

India is increasingly using AI-enabled systems to improve preparedness against climate-induced disasters such as cyclones, floods, landslides, heatwaves, and extreme weather events.

AI in Cyclone Forecasting and Weather Modelling

India has significantly strengthened cyclone forecasting through AI-assisted technologies and high-performance computing systems.

Advanced Dvorak Technique

The India Meteorological Department (IMD) uses the Advanced Dvorak Technique along with satellite-based AI tools to estimate cyclone intensity and track tropical cyclones.The system helps in:

  • Predicting cyclone formation
  • Estimating intensity
  • Forecasting cyclone trajectory
  • Assessing possible landfall impacts

IMD also uses AI-based guidance from the European Centre for Medium-Range Weather Forecasting (ECMWF) for improved forecasting accuracy.


High-Performance Computing Infrastructure

The Ministry of Earth Sciences has installed High-Power Computing Systems with 22 PetaFLOPS capacity for advanced weather prediction and AI research.Important features include:

  • Dedicated Graphics Processing Units (GPUs) for AI work
  • AI and Machine Learning-based weather prediction models
  • Improved climate simulations and forecasting capabilities

These systems strengthen India’s capability in:

  • Extreme weather forecasting
  • Monsoon prediction
  • Climate risk management

AI-Based Research and Development Initiatives

Transformer-Based Neural Networks

Indian researchers have developed transformer-based neural networks capable of forecasting monsoon behaviour up to 18 days in advance.


Global AI Weather Models

Comparative studies involving AI systems such as:

  • GraphCast
  • PanguWeather
  • Aurora
  • FourCastNet

have demonstrated:

  • Cyclone path prediction accuracy up to 96 hours before landfall
  • Approximate accuracy within 200 kilometres in seconds

These advancements improve:

  • Evacuation planning
  • Disaster preparedness
  • Infrastructure protection

SpADANet by IIT Bombay

The Spatially Aware Domain Adaptation Network (SpADANet) developed by IIT Bombay is an AI model used for cyclone and hurricane damage assessment through aerial imagery.Key significance:

  • More than 5% better accuracy than existing systems
  • Works effectively with limited labelled datasets
  • Supports NDMA-type disaster response systems

It addresses constraints such as:

  • Lack of labelled disaster data
  • Limited computing resources
  • Delayed damage assessment

Reliability Ensemble Averaging (REA)

Researchers at IIT Madras use Reliability Ensemble Averaging (REA) to improve climate prediction accuracy.The model:

  • Combines 26 climate models
  • Evaluates predictive accuracy
  • Reduces uncertainty in rainfall prediction

Testing was conducted in:

  • Coimbatore
  • Rajkot
  • Udaipur
  • Siliguri

The findings highlighted limitations in many existing rainfall prediction models and showcased the improved reliability of REA.


Institutional AI Research Ecosystem

AI Research Collaborations

The India Meteorological Department (IMD) has:

  • Created a dedicated AI and Machine Learning research team
  • Signed agreements with:
    • IITs
    • NITs
    • ISRO
    • DRDO
    • Other research institutions

IMD also organizes annual AI and Machine Learning training programmes.


IITM Pune Virtual Centre

The Indian Institute of Tropical Meteorology (IITM), Pune operates a virtual centre for developing AI-based weather and climate applications.


AI in Landslide, Flood and Glacial Monitoring

Indigenous Landslide Early Warning System

India has developed an AI-based landslide early warning system for Himalayan regions.

Important Features

  • Provides alerts up to 3 hours before slope failure
  • Uses low-cost sensors measuring:
    • Soil moisture
    • Rainfall
    • Humidity
    • Temperature
    • Ground displacement
  • Uses machine learning models with over 90% accuracy

The system has been installed at:

  • More than 60 sites in Himachal Pradesh

It detects millimetre-level slope movements and improves evacuation preparedness.


Indian Land Data Assimilation System (ILDAS)

The Indian Land Data Assimilation System (ILDAS) funded by ISRO (2021–24) estimates:

  • Land surface states
  • Floodplain inundation
  • Hydrological conditions

It integrates:

  • Remote sensing
  • Coupled modelling
  • AI-assisted flood forecasting

BrahmaSATARK and GBM-CLIMPACT

BrahmaSATARK

Provides impact-based flood forecasting for the Brahmaputra Basin.

GBM-CLIMPACT

A climate-impact assessment toolbox for:

  • Ganga Basin
  • Brahmaputra Basin
  • Meghna Basin

These systems improve:

  • River basin management
  • Water sector preparedness
  • Climate resilience

Last-Mile Climate Intelligence

Gram Panchayat Level Weather Forecasting (GPLWF)

Launched by IMD in collaboration with the Ministry of Panchayati Raj, this initiative provides:

  • Gram Panchayat-level weather forecasts
  • Temperature data
  • Rainfall predictions
  • Humidity forecasts
  • Wind information

The service reaches nearly all Gram Panchayats in India through:

  • e-Gramswaraj
  • Meri Panchayat
  • Mausam Gram applications

It helps farmers make informed decisions regarding:

  • Irrigation
  • Harvesting
  • Sowing

Bharat Forecasting System (BharatFS)

Launched on 27 May 2025, BharatFS is an indigenous weather prediction model.

Key Features

FeatureDetails
Forecast Resolution6 km
Previous Resolution12 km
Forecast HorizonUp to 10 days
CoverageVillage-level

The system enhances:

  • Disaster preparedness
  • Agricultural planning
  • Public weather forecasting

Emerging AI Tools in Climate Governance

MausamGPT

The government is developing MausamGPT, a Generative Pre-trained Transformer-based AI chatbot for:

  • Farmers
  • Climate advisory services
  • Weather-related guidance

AI is also being used for:

  • Fire forecasting
  • Fog prediction
  • Lightning alerts
  • Thunderstorm forecasting
  • Rainfall prediction through deep learning systems

Coastal and Sea-Level Monitoring

AI systems are being used for:

  • Coastal vulnerability assessment
  • Sea-level rise monitoring
  • Climate risk mapping

These tools assist:

  • Urban planners
  • Coastal communities
  • Disaster management agencies

in preparing for long-term climate risks.


AI-Powered Forest Surveillance

AI-enabled surveillance systems use:

  • Machine Vision (MV)
  • Real-time camera monitoring
  • Satellite and drone integration

Major Applications

Forest Fire Detection

AI systems help detect and contain fires rapidly.The article highlights that:

  • Humans are responsible for nearly 75% of global wildfires.

Human-Wildlife Conflict Prevention

AI-enabled cameras detect animals moving outside forests.

Monitoring Illegal Activities

AI assists in detecting:

  • Encroachments
  • Illegal felling
  • Forest degradation

These systems strengthen conservation governance and protect natural carbon sinks.


AI in Air Quality and Water Risk Management

AIRAWAT Research Foundation Initiative

The AIRAWAT Research Foundation of IIT Kanpur signed an MoU with IIT Delhi to develop AI-driven solutions for:

  • Air quality monitoring
  • Sustainable urban mobility
  • Waste management
  • Smart infrastructure
  • Bioaerosol monitoring

The initiative supports climate-resilient urban governance.


AI-Based Arsenic Risk Mapping

Researchers at IIT Kharagpur developed an AI-based model to detect arsenic contamination in groundwater along the Ganga Basin.

Important Findings

The study identified:

  • High-risk arsenic zones
  • Safe groundwater regions

The model uses:

  • Geological data
  • Environmental variables
  • Human usage patterns

The initiative supports:

  • Jal Jeevan Mission
  • Safe drinking water planning
  • Groundwater sustainability

Conclusion

India is emerging as a global leader in AI-enabled climate governance and disaster resilience. Through investments in:

  • AI infrastructure
  • High-performance computing
  • Village-level forecasting systems
  • Disaster early warning technologies
  • Climate research collaboration

India is strengthening resilience against climate-induced risks.Initiatives such as:

  • Bharat Forecasting System
  • GPLWF
  • AI-enabled flood forecasting
  • Landslide warning systems
  • AI-powered environmental monitoring

demonstrate how technology can support sustainable development and climate adaptation, especially for vulnerable communities in the Global South.


Necessary Static Part

InstitutionDetails
India Meteorological Department (IMD)Established: 1875
HeadquartersNew Delhi
Parent MinistryMinistry of Earth Sciences
Director GeneralDr. Mrutyunjay Mohapatra
FunctionsWeather forecasting, cyclone warning, climate services, disaster early warning
IITM PuneIndian Institute of Tropical Meteorology involved in AI-based climate applications
ISROSupported ILDAS project (2021–24)
NDMADisaster management coordination and preparedness

Updated – 16 Feb 2026 ; 03:39 PM | PIB [Posted On: 16 FEB 2026 3:09PM by PIB Delhi] | News Source – PIB Delhi

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