Accompanying Python code for Atkins et al. (2025). Recent European marine heatwaves are unprecedented but not unexpected. Communications Earth & Environment.
Includes all code (plus guidance on data access) required to perform UNSEEN analysis and make all figures as they appear in the main text and supplement.
| File | Description |
|---|---|
| config.py | Master file for specifying UNSEEN analysis parameters and data file paths in configuration objects. |
| figure*.py | Manuscript and supplement figure code. |
| methods/ | Directory containing UNSEEN, plotting and utility functions for analysis. |
| LICENSE | Software licensing information. |
| README.md | This file. |
| environment.yml | YAML file for building Conda enironment. |
This repository can be cloned to your local machine by:
git clone https://github.com/j-atkins/UNSEEN_MHWs.git
The environment.yml file can be used to create a Conda environment with all dependencies by:
conda env create -f environment.yml
N.B. The post-processed data from model/observational product output is housed in a separate Zenodo repository. To run the code 'out of the box', it is necessary to access the processed data from the Zenodo repository and house it in a new data/ directory in this codebase repository.
This section describes the source data used in this study. Processed forms of the data, ready for analysis and plotting (including sub-region means versions), are housed in a separate Zenodo data repository, as described in the Set up.
OSTIA near real-time and climate data can be accessed from the Copernicus Marine Environment Monitoring Service.
GloSea data can be accessed from C3S (this version is interpolated to a 1° × 1° grid).
In this study, only GloSea data for the JJA forecast period are used (initalised on 25th April, 1st May and 9th May across each year of the hindcast period).
Jamie Atkins
Institute for Marine and Atmospheric research Utrecht (IMAU)
Utrecht University
email: [email protected]