Multi-Hazard Early Warning System: India's Integrated Initiative in Disaster Management

In a country like India, characterized by its vastness and diverse geographical conditions, extreme weather events—such as floods, cyclones, and heatwaves—occur frequently. Driven by the impacts of climate change, both the frequency and intensity of these disasters are on the rise, thereby significantly heightening the country's vulnerability. In such a scenario, the existence of an effective and timely Early Warning System becomes absolutely imperative.

Multi-Hazard Early Warning Decision Support System (MHEW-DSS)

¨  It is a digital platform that automates the decision-making on critical weather forecasting processes and forecast and warning services to the public, government, and non-government agencies, as well as specific stakeholders.

¨  It has been developed by the India Meteorological Department using open-source technology and in-house expertise.

¨   Launched under Mission Mausam in January 2024, it combines satellite, radar, and other observational data with advanced forecasting tools and utilises Geographic Information System (GIS) maps for efficient collection, analysis, and dissemination of weather data.

¨ It delivers real-time, impact-based multi-hazard forecasting across India, empowering decision-makers and communities by translating complex meteorological data into actionable warnings.

¨   It also includes a public platform named Mausamgram, which provides hyper-local weather forecasts by entering the name of the place or the Pincode of the place. It reflects the Government of India’s vision of a “Weather Ready and Climate Smart Nation” and embodies the philosophy of “Har Har Mausam, Har Ghar Mausam.

Salient Features of the MHEW-DSS

¨     Automated Weather Data Processing: Over 90% of weather data collection, quality checks, and integration are automated.

¨    Better Use of Forecast Models: More than 95% of numerical weather prediction model inputs are now used in forecasting.

¨    Longer Forecast Lead Time: Forecast lead time has increased from 5 days to 7 days.

¨     Faster Forecast Preparation: The time required to prepare forecasts has reduced by about 3 hours from 6 hours.

¨   Cost Savings and Self-Reliance: The system has generated around ₹250 crore in cost savings and eliminated dependence on foreign vendors.

¨ Reduced Evacuation Costs: Improved early warnings have helped reduce evacuation costs to one-third from 1999 to 2024 due to a reduction in cyclone landfall point forecast error in the 3-5 days ahead forecast issued by IMD.

Operational Architecture of the MHEW-DSS

¨ Weather Analysis and Forecast Enabling System (WAFES) helps forecasters analyse data, generate charts, and visualise weather conditions through GIS-based maps.

¨   Using a GIS-enabled platform, it integrates colour-coded alerts for various hazards and disseminates them through digital channels like SMS, emails, Application Programming Interface (API), Mobile App (Mausam), Common Alerting Protocol (CAP) and graphical bulletins to ensure timely action and disaster preparedness.