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A Random Forest SSR Emulator trained with the EarthSenseData (Stamatis et al., 2025).

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☀️ Hyperion – Surface Solar Radiation Emulator

Hyperion is a Random Forest emulator that predicts monthly Surface Solar Radiation (SSR)
from 2 basic atmospheric parameters: Cloud cover, and AOD.
It was trained on radiative-transfer model inputs/outputs from the EarthSenseData (Stamatis et al., 2025) (https://zenodo.org/records/17382343).


🧠 Features

  • Predict SSR for single input values or entire time-series files (CSV/XLSX)
  • Download results instantly in CSV format
  • Interactive Bokeh dashboard
  • Fully portable via Docker
  • Uses scikit-learn 1.7 compatible .pkl model

🎬 Demo

Hyperion Demo


📦 Model

First, download the model and place it in the Hyperion folder:

Zenodo DOI: https://zenodo.org/records/17429272

Filename: Hyperion_RF.pkl (~40 MB)


🚀 Run Locally (Python)

# 1. Clone and enter repo
git clone https://github.com/mixstam1821/Hyperion.git
cd Hyperion

# 2. Create virtual environment (optional)
python -m venv venv
source venv/bin/activate  # (Linux/macOS)
venv\Scripts\activate     # (Windows)

# 3. Install dependencies
pip install -r requirements.txt

# 4. Run app
bokeh serve --show Hyperion_GUI.py --port=9959

# 5. Open http://localhost:9959/Hyperion_GUI

🐳 Run with Docker

# Build image
docker build -t hyperion-app .

# Run container
docker run -p 7860:7860 hyperion-app

# Open http://localhost:7860/Hyperion_GUI

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A Random Forest SSR Emulator trained with the EarthSenseData (Stamatis et al., 2025).

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