Multi-Hazard Early Warning Decision Support System

The Multi-Hazard Early Warning Decision Support System (MH-EWDSS) marks a significant advancement in India’s weather forecasting and disaster management framework. It reflects the country’s shift toward a more technology-driven and proactive approach for dealing with natural disasters and extreme weather events. The system strengthens India’s capability to provide faster, more accurate, and real-time weather warnings, thereby helping authorities and communities prepare in advance and reduce disaster-related losses.

About the Multi-Hazard Early Warning Decision Support System

The Multi-Hazard Early Warning Decision Support System is an advanced digital forecasting platform developed by the Indian Meteorological Department (IMD) using open-source technology along with in-house scientific expertise. It is a major digital transformation initiative launched under Mission Mausam, which focuses on modernizing India’s meteorological infrastructure and forecasting systems.

The platform was officially launched in January 2024 under the Ministry of Earth Sciences (MoES), which acts as the nodal ministry for the initiative.

The system functions in real time and integrates advanced technologies such as Geographic Information System (GIS) mapping to improve the collection, analysis, and dissemination of weather-related information. Through GIS-based visualization, forecasters can easily monitor developing weather systems and identify regions vulnerable to hazards like cyclones, floods, heatwaves, thunderstorms, and heavy rainfall.

Digital and Technological Features

One of the most important aspects of the system is its high degree of automation. More than 90% of weather data collection, quality checking, and data integration processes are now automated. This significantly reduces human intervention and enables quicker detection of weather systems and associated risks.

The system also makes better use of Numerical Weather Prediction (NWP) models. Earlier, only limited forecasting model inputs were effectively utilized, but now more than 95% of model inputs are incorporated into the forecasting process. This improves the overall accuracy and reliability of weather predictions.

Another major improvement is the re-engineering of the forecasting and warning generation process. The entire forecasting workflow has been redesigned to support faster decision-making and real-time warning dissemination. This ensures that alerts reach authorities and the public more quickly during emergencies.

Increase in Forecast Lead Time

A highly significant achievement of the system is the increase in forecast lead time from 5 days to 7 days. This additional preparation time is extremely valuable for disaster management authorities, local governments, and vulnerable communities.

Longer lead times allow authorities to:

• plan evacuations,

• mobilize emergency services,

• secure infrastructure,

• and issue public advisories well in advance.

This can greatly reduce the loss of life, property damage, and economic disruption caused by extreme weather events.

Faster Forecast Preparation

The system has also reduced the time required to prepare forecasts by nearly 3 hours. Earlier, preparing detailed forecasts used to take approximately 6 hours, but the upgraded digital infrastructure now enables much faster processing and dissemination of warnings.

This speed is particularly important during rapidly developing weather events such as:

• cyclones,

• flash floods,

• cloudbursts,

• and severe thunderstorms.

Faster warnings improve emergency response and allow communities to act quickly.

Importance for Disaster Risk Reduction

The Multi-Hazard Early Warning Decision Support System is a major step toward strengthening India’s disaster resilience and climate preparedness. As climate change increases the frequency and intensity of extreme weather events, accurate and timely forecasting has become essential for protecting human lives and infrastructure.

The system improves coordination between:

• meteorological agencies,

• disaster management authorities,

• local administrations,

• and emergency response teams.

By enabling real-time monitoring and rapid dissemination of warnings, the platform helps reduce risks associated with multiple hazards simultaneously.

Mission Mausam

The MH-EWDSS is an important component of Mission Mausam, India’s broader initiative aimed at modernizing weather forecasting systems through advanced technologies such as:

• artificial intelligence,

• high-performance computing,

• data analytics,

• and improved observational networks.

Mission Mausam seeks to make India more climate-resilient and capable of responding effectively to environmental and weather-related challenges.

Conclusion

The Multi-Hazard Early Warning Decision Support System represents a transformative development in India’s meteorological and disaster management capabilities. By combining automation, GIS mapping, advanced forecasting models, and real-time data analysis, the system significantly improves the speed and accuracy of weather warnings. Its ability to provide longer forecast lead times and faster alerts strengthens disaster preparedness, reduces risks, and supports India’s goal of building a more resilient and climate-ready society.