🌍 NASA Weather Data Query System

High-performance weather data management and visualization platform powered by NASA CFS GRIB2 data

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✨ Key Features

🔧 Backend (8 Core Modules)

1. cfs_fetch.py - Automated NASA CFS data downloader with retry mechanisms
2. grib_api.py - FastAPI REST API server for spatio-temporal queries
3. bunk_index.py - GRIB2 file indexer with SQLite for fast lookups
4. query_file_index.py - Command-line query tool with JSON/CSV export
5. grid_util.py - Geospatial coordinate transformation utilities
6. inspect_grib.py - GRIB2 file inspector and validator
7. performance_test.py - Performance benchmarking and load testing
8. main.py - Integrated launcher for one-command startup

🎨 Frontend Visualization

Professional weather animations (20 FPS) on 1°×1° regional maps:

• 🌡️ Temperature - Heatmap with thermal ripples & dynamic thermometer
• 💨 Wind Speed - Streamline flow with animated arrows & rotating windmill
• ❄️ Snow Coverage - Falling snowflakes with accumulation & snowman
• 🌧️ Precipitation - Raindrop animation with splashes & umbrella
• ☁️ Cloud Coverage - Moving clouds with shadows & rotating sun

All elements dynamically scale based on real-time data values.

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📸 Screenshots

Statistical Results

Professional Visualization

LLM Implementation

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🛠️ Tech Stack

Backend: Python 3.8+ • FastAPI • cfgrib • SQLite • NumPy

Frontend: React 18 • TypeScript • Next.js • Tailwind CSS • Canvas API • Leaflet

Architecture: RESTful API • Frontend-Backend Separation • Real-time Data Processing

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🌟 Highlights

✅ 8 Backend Modules - Complete data pipeline from download to query
✅ Professional Visualizations - 5 animated weather effects with dynamic scaling
✅ GPT Integration - AI-powered weather analysis and insights
✅ Frontend-Backend Separation - Modern microservices architecture
✅ High Performance - <100ms queries, 100+ concurrent users, 60 FPS rendering
✅ One-Command Startup - ./start.sh launches everything
✅ NASA Data Integration - Direct access to CFS GRIB2 archives
✅ Production-Ready - Robust error handling, logging, and monitoring

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🚀 Quick Start

# Install dependencies
pip install -r requirements.txt
cd frontend && npm install

# Configure environment
export GRIB_DATA_DIR=/path/to/data
cd frontend && cp env.example env

# Start system (one command!)
./start.sh

Access:

• Backend API: http://localhost:8000
• Frontend UI: http://localhost:3000

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📡 API Example

curl -X POST http://localhost:8000/api/query-data \
  -H "Content-Type: application/json" \
  -d '{
    "start_iso": "2025-10-04T00:00:00",
    "end_iso": "2025-10-04T23:59:59",
    "lon_min_0_360": 280.8,
    "lon_max_0_360": 281.8,
    "lat_min": 43.68,
    "lat_max": 44.68,
    "variable": "t2m",
    "level": "heightAboveGround"
  }'

Supported Variables: t2m (Temperature) • tcc (Cloud Coverage) • u10 (Wind Speed) • snowc (Snow Coverage) • cpr (Precipitation)

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📊 Performance

• Query Speed: < 100ms
• Concurrent Users: 100+
• Animation: 60 FPS rendering, 20 FPS playback
• Data Coverage: Global 0.5° × 0.5° resolution

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🗂️ Project Structure

weatherproject/
├── cfs_fetch.py              # Data downloader
├── grib_api.py               # FastAPI server
├── bunk_index.py             # GRIB indexer
├── query_file_index.py       # Query tool
├── grid_util.py              # Geospatial utils
├── inspect_grib.py           # File inspector
├── performance_test.py       # Benchmarking
├── main.py                   # Launcher
├── frontend/                 # React + TypeScript UI
│   ├── components/
│   ├── pages/
│   └── lib/api.ts
├── data/                     # GRIB2 files
├── start.sh                  # One-command startup
└── README.MD

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🙏 Acknowledgments

NASA/NOAA - CFS GRIB2 data • ECMWF - cfgrib library • FastAPI - Web framework • React & Next.js - Frontend tools

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