Tooth (2026) NOC-MSM/nemo_cookbook: v2026.03.b1

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

Journal: Open MIND
Year: 2026
Date: 2026-03-30
Authors: Ollie Tooth
DOI: 10.5281/zenodo.18292768

Research Groups

National Oceanography Centre (NOC) - Marine Systems Modelling (MSM) group (inferred from NOC-MSM/nemo_cookbook).

Short Summary

This release introduces significant enhancements to the nemo_cookbook Python library, including a new NEMODataArray object and advanced grid-aware methods, to streamline and improve the analysis of NEMO ocean model outputs.

Objective

To enhance the functionality, usability, and robustness of the nemo_cookbook library by introducing new data structures and methods for grid-aware computation, improving existing features, and fixing bugs, thereby facilitating more efficient and accurate analysis of NEMO ocean model data.

Study Configuration

Spatial Scale: Not directly applicable to the software development itself. The nemo_cookbook is designed to process NEMO model outputs, which can span global to regional scales.
Temporal Scale: Not directly applicable to the software development itself. The nemo_cookbook is designed to process NEMO model outputs, which can span from sub-daily to multi-decadal scales.

Methodology and Data

Models used: The nemo_cookbook library is developed to process outputs from the NEMO (Nucleus for European Modelling of the Ocean) model.
Data sources: The software is designed to analyze data generated by NEMO ocean models. The specific source of these model outputs (e.g., specific simulations, reanalysis products) is not detailed in this release note.

Main Results

Introduction of the NEMODataArray object with properties (e.g., .mask, .metrics, .grid) and methods (e.g., .apply_mask(), .sel_like(), .diff(), .depth_integral(), .weighted_mean(), .interp_to(), .transform_vertical_grid()) for grid-aware computation.
Enhanced NEMODataTree constructors to support linear free-surface approximation.
Addition of two new NEMO Cookbook Recipes: Upper Ocean Heat Content and Meridional Ocean Heat Transport.
Resolution of several bugs, including issues with add_geoindex(), extract_section(), compute_binned_statistic(), and interpolate_grid().
Improved documentation and development workflow support (Pixi, GitHub templates).

Contributions

This release significantly advances the nemo_cookbook library by providing a more robust and intuitive framework for analyzing NEMO model outputs. The introduction of NEMODataArray and grid-aware methods simplifies complex oceanographic calculations, making the analysis of NEMO data more accessible and efficient for the scientific community.

Funding

Not specified in the provided release notes.

Citation

@article{Tooth2026NOCMSMnemocookbook,
  author = {Tooth, Ollie},
  title = {NOC-MSM/nemo_cookbook: v2026.03.b1},
  journal = {Open MIND},
  year = {2026},
  doi = {10.5281/zenodo.18292768},
  url = {https://doi.org/10.5281/zenodo.18292768}
}

Original Source: https://doi.org/10.5281/zenodo.18292768