Replication package for: A physically consistent SEVIRI-based framework for seamless fog life cycle monitoring over thermally heterogeneous interfaces

This repository contains the complete replication package, core processing algorithms, and processed datasets for the manuscript:

“A physically consistent SEVIRI-based framework for seamless fog life cycle monitoring over thermally heterogeneous interfaces” submitted to the International Journal of Applied Earth Observation and Geoinformation (JAG), Elsevier.

The package is fully structured to ensure total scientific transparency and 100% reproducibility of the framework’s core diagnostic functions and the figures presented in the manuscript.

1. Repository Structure & Contents

• scripts_reproduce_figures/: Contains the standalone Python scripts (fig05_*.py, fig06_*.py, fig07_*.py, and fig12_*.py) programmed to automatically regenerate the main experimental plots and matrices of the manuscript.

• script_functions_manuscript/: Includes operators.py, hosting the core diagnostic functions of the framework 

• input_files/ & typology1/: Standardized matrices containing processed input variables, solar elevation data, and extracted spatial metrics.

• Metadata & Guidelines: Includes a comprehensive README.md with execution instructions, a unified requirements.txt for environment configuration, a LICENSE file, and a native CITATION.cff for software preservation.

2. Technical Context & Dataset Details

The dataset captures fog life cycle transitions (day, night, and twilight) over one of Europe’s largest artificial inland water bodies (the Alqueva reservoir, Portugal), a radiometrically complex environment for geostationary sensors. Data inputs originate from Meteosat Second Generation (MSG) SEVIRI Level 1.5 data and NWC SAF Cloud Type (CT) products. 

3. How to Use

To replicate the findings, clone/extract this repository, install the dependencies via pip install -r requirements.txt, and run the target figure scripts. All data reading operations use relative paths to ensure seamless out-of-the-box execution.