Abstract

In this work, we present two related methods for calculating fronts from oceanographic data. fronts, with the advantage that it can highlight the movement of individual eddy-like features (such as the Agulhas rings). We will present our python GitHub repository, which will allow researchers to easily apply these methods to their own datasets.

Paper: https://doi.org/10.5194/os-17-1545-2021

Preprint: https://doi.org/10.5194/os-2021-40

Presentation at AGU2021: https://doi.org/10.1002/essoar.10507114.1 ; https://youtu.be/J8TMZlteN9s

Contents:

• Abstract
• src package
  • Subpackages
    • src.data_loading package
    • src.models package
    • src.plot package
    • src.plot_utils package
    • src.preprocessing package
  • Submodules
  • src.animate module
  • src.constants module
  • src.make_figures module
  • src.move_figures module
  • src.time_wrapper module
  • Module contents
• Defining Southern Ocean fronts using unsupervised classification
  • Paper: https://doi.org/10.5194/os-17-1545-2021
  • Preprint: https://doi.org/10.5194/os-2021-40
  • Presentation at AGU2021: https://doi.org/10.1002/essoar.10507114.1
  • Short description
  • I metric for K=5
  • Getting started
  • Project Organization
  • Requirements
• Animations gallery
  • I metric for K=5
  • I metric for K=4
  • I metric for K=2
• Current state of code
• Unsupervised classification
  • Perception
  • Possible objectives
• About
  • Co-authors
  • Funding

Indices and tables

• Index

• Module Index

• Search Page