PS 26072SOFTWAREDisaster ManagementModerate Scope

AIML based Nowcasting of thunderstorm and lightning using atmospheric observation including multiple radars, satellite, lightning and model data.

Ministry of Earth Sciences (MoES)India Meteorological Department
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30-Second Plain English Summary

Severe thunderstorms, squalls, and cloud-to-ground lightning strikes kill over 2,500 rural farmers and laborers annually in India due to sudden onset and lack of localized nowcasting. Build an AI/ML-based nowcasting and early warning platform for IITM/IMD that ingests Lightning Location Network (LLN) pulses, Doppler radar reflectivity, and INSAT-3D cloud-top temperatures to forecast thunderstorm cell paths and lightning strike hazard zones 30-90 minutes in advance.

5-Dimension Strategic ScorecardOverall Score: 3.8 / 5.0
Innovation
4 / 5
36h Feasibility
4.3 / 5
Uniqueness
3.5 / 5
Jury Appeal
3.5 / 5
Tech Depth
3.7 / 5
Recommended System Architecture Pipeline
Lightning VHF/LF Sensors + Doppler Radar + INSAT-3D -> Storm Cell Tracking Engine (TITAN) -> Lightning Jump AI Predictor -> CAP Alert Gateway -> Farmer Mobile Siren App
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Official Government Problem Description
AIML based Nowcasting of thunderstorm and lightning using atmospheric observation including multiple radars, satellite, lightning and model data.
AI & PPT Citation Format

Smart India Hackathon 2026 Problem Statement PS-26072: "AIML based Nowcasting of thunderstorm and lightning using atmospheric observation including multiple radars, satellite, lightning and model data.", Ministry: Ministry of Earth Sciences (MoES). Strategy & Architecture via SIH ONE (https://sihone.pages.dev/ps/26072)

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