This repository allows for the re-computation of the composite front detection of ocean fronts on the Southwestern Atlantic Continental Shelf from Absolute Dynamic Topography (ADT) and Sea Surface Temperatures (SST). The approach is based on horizontal gradients of the fields. The data given in the repository are ADT from multi-mission gridded altimetry enhanced with SWOT KaRIn ("SWOT MIOST", https://doi.org/10.24400/527896/a01-2025.001) and remote-sensed SST (OSTIA, https://doi.org/10.48670/moi-00165), which are publicly available through Copnicus Marine Service.
- Python ≥3.10
(- conda)
The software has been developed and tested using the Conda environment provided in environment.yml. Packages can also be manually be added, see first part of the .ipynb file. Otherwise:
conda env create -f environment.yml --name <environment_name>
conda activate <environment_name>
Run the code by running the Composite_Front_Detection_git.ipnyb file in Jupyer Notebook or VSCode.
- Load sample data given or implement others
- compute horizontal gradients
- Pre-defined plots show you the monthly mean gradients
- compute joint front probability and plot --> see details in the study region and identify fronts
MIT License
Marie-Christin Juhl
Deutsches Geodätisches Forschungsinstitut der Universität München (DGFI-TUM)
[email protected]
(Feel free to contact!)