WeatherGPT bridges global numerical weather prediction (NOAA GFS) with high-resolution reanalysis (ECMWF ERA5) using an XGBoost bias-correction engine and conversational AI.
Official Title: WeatherGPT: Conversational AI for Weather Forecasting, Alerts, and Climate Information (Theme: Disaster Management).
Weather information is often distributed through multiple portals, bulletins, satellite products, and forecast systems, making it difficult for common users, researchers, disaster managers, and government agencies to quickly obtain actionable insights.
Develop WeatherGPT: an intelligent conversational platform integrating meteorological datasets, forecasting models (GFS/WRF), disaster early warnings, location-based advisories, voice interaction for rural accessibility, and multilingual Indian language support.
Traditional Numerical Weather Prediction (NWP) models like NOAA GFS calculate atmospheric fluid dynamics on global grids. However, localized micro-climates and topography create systematic temperature errors up to ±5°C.
Global numerical circulation models (GFS) smooth out hyper-local topography such as urban heat islands, river valleys, and coastal sea breezes. This leads to consistent over-prediction of daytime surface heating and under-prediction of nighttime cooling.
WeatherGPT trains a specialized XGBoost error-correction model on multi-decade ECMWF ERA5 reanalysis observations. It learns the non-linear residual bias function ΔT = T_ERA5 - T_GFS across cyclic temporal, seasonal, and spatial coordinates.
From raw numerical weather model grids to hyper-local natural language intelligence.
Fetches 0.25° global grid 16-day numerical forecasts from NOAA GFS run cycles (00z, 06z, 12z, 18z).
Extracts 2m temperature, surface pressure, humidity, u/v wind vectors, solar radiation, cyclic sine-cosine encodings, and forecast lead time.
Evaluates the high-dimensional gradient boosted decision tree to predict exact temperature residual corrections (ΔT).
Groq LLM agent synthesizes structured weather parameters into natural language explanations in Hinglish or English with speech audio synthesis.
Interactive temperature comparison over a 24-hour diurnal cycle. Observe how WeatherGPT's corrected curve tracks the ERA5 ground-truth observations.
Aligned with Smart India Hackathon SIH26068 expected outcomes and deliverables.
Ask weather queries naturally in English or Hinglish. Powered by Groq LLM agent with real-time tool calling into the XGBoost numerical pipeline.
Seamless timeline blending multi-year ERA5 historical climate trends with 16-day ML-enhanced GFS forecasts in a responsive graph interface.
Event-driven background service monitoring India Meteorological Department warnings with district-matched VAPID Web Push notifications.
Interactive micro-courses, quizzes, and AI-assisted simplified explanations for atmospheric science topics (Thunderstorms, Heat Waves, Cyclones).
Hands-free voice query processing using Groq Whisper Speech-to-Text and real-time Text-to-Speech audio response generation for rural accessibility.
Built with rich glassmorphism aesthetics, fluid HSL color spaces, responsive grid layouts, and instantaneous dark/light theme switching.
Overview of the 4 key application views available in WeatherGPT.
Natural language conversational assistant with instant response cards, voice input mic, structured weather metrics, and speech audio playback controls.
Interactive climate historical graph connecting historical ERA5 reanalysis data with 16-day machine learning bias-corrected forecasts.
District-based alert subscription manager with live IMD warning status monitoring and instant VAPID push notification delivery.
Multi-column learning grid featuring interactive lessons, atmospheric science quizzes, progress tracking, and AI-assisted simplified explanations.
Engineered for low latency, maximum precision, and scalable background processing.