# WeatherFlow Applications Gallery

Real-world application blueprints demonstrating how to use WeatherFlow for specific domains.

## Overview

The Applications Gallery provides complete, runnable examples that solve focused problems in different domains. Each application is designed as a template that users can adapt to their specific needs.

## Available Applications

### 1. Renewable Energy Forecasting
**Directory:** `renewable_energy/`

Predict wind and solar power generation using weather forecasts from WeatherFlow.

- **Wind Power Forecasting**: Convert wind speed/direction predictions to power output
- **Solar Power Forecasting**: Convert solar irradiance predictions to PV generation
- **Grid Integration**: Multi-site ensemble forecasting for grid operators
- **Use Cases**: Wind farms, solar installations, grid planning, energy trading

### 2. Extreme Event Analysis
**Directory:** `extreme_event_analysis/`

Detect, track, and analyze extreme weather events.

- **Event Detection**: Identify heatwaves, cold spells, atmospheric rivers
- **Performance Analysis**: Evaluate model skill during extreme events
- **Risk Assessment**: Quantify forecast uncertainty for high-impact events
- **Use Cases**: Emergency management, insurance, agriculture, public health

### 3. Educational Laboratory
**Directory:** `educational/`

Plug-and-play teaching materials for atmospheric dynamics courses.

- **Interactive Dashboards**: Explore atmospheric flows and dynamics
- **Guided Exercises**: Step-by-step problems with solutions
- **Visualization Tools**: Publication-quality figures for lectures
- **Use Cases**: Graduate courses, workshops, self-study

## Quick Start

Each application includes:

- **README.md**: Overview, requirements, and instructions
- **Runnable Scripts**: Complete Python scripts or notebooks
- **Sample Data**: Small datasets for testing (or download instructions)
- **Configuration Files**: Easy-to-modify parameters
- **Output Examples**: Expected results for validation

### Example: Wind Power Forecasting

```bash
cd applications/renewable_energy
python wind_power_forecast.py --config wind_farm_config.yaml
```

Or use the Jupyter notebook:

```bash
jupyter notebook renewable_energy_forecasting.ipynb
```

## Application Structure

Each application follows this structure:

```
application_name/
├── README.md                  # Application-specific documentation
├── requirements.txt           # Additional dependencies
├── config/                    # Configuration files
│   └── example_config.yaml
├── scripts/                   # Python scripts
│   └── main_script.py
├── notebooks/                 # Jupyter notebooks
│   └── application_demo.ipynb
├── data/                      # Sample data or download scripts
│   └── download_data.sh
└── outputs/                   # Example outputs
    └── sample_output.png
```

## Contributing Applications

We welcome contributions! To add a new application:

1. Create a new directory under `applications/`
2. Follow the standard structure above
3. Include comprehensive documentation
4. Ensure all scripts run without errors
5. Submit a pull request

See `CONTRIBUTING_APPLICATIONS.md` for detailed guidelines.

## License

All applications are released under MIT License unless otherwise specified.
