This repository is a Cookbook of Recipes 👩🏽🍳 👨🏻🍳. A collection of recipes and tutorials for analysing ocean and sea ice model output produced by the Consortium for Ocean-Sea Ice Modelling in Australia (COSIMA).
We explain: a "recipe" here is an example an analysis of some ocean-sea ice model output or some ocean-related observational datasets. Each "recipe" comes in a self-contained and well-documented Jupyter notebook. All the recipes combined form a cookbook 📒!
Most recipes use output from the ACCESS-OM2 model, while some also use results from configurations of the Modular Ocean Model 6 (MOM6) and remote sensing observations.
To access the data used in these recipes you need an account with the Australian-based National Computational Infrastructure (NCI).
To get started, clone this repository in your local space on one of the NCI HPC machines so you can have access to model output. You should then be able to run these recipes (i.e., example analyses) through an Australian Research Environment (ARE) JupyterLab session running python or via any other way you might want to run a Jupyter notebook on an NCI HPC machine. You need to join projects hh5, xp65, ik11, cj50 and ol01 to run the recipes and access the data analysed.
If you plan to use an ARE session, then remember to include the projects in the Storage line: gdata/xp65+gdata/ik11+gdata/cj50+gdata/hh5+gdata/ol01 as well as any of your own project you need access to. In Module directories, set /g/data/hh5/public/modules and in Modules set conda/analysis3. Use a Compute Size of large or greater.
If you have never used the NCI see these first steps instructions and getting started with ARE.
Have you made a recipe for analysing something that is not already included in this cookbook? You are more than welcome to share it and include it in the cookbook! Consider contributing your recipe back to the repository. We are always delighted to expand our cookbook with more recipes. If the process of contributing to the repository sounds a bit intimidating to you, rest assured that we will guide you and help you with submitting your contribution.
To make a contribution follow the steps laid out in the beginner's guide on how to contribute. If they sound intimidating then don't worry! Just raise an issue explaining briefly what the contribution you want to make is and we'll help out with the process!
We are in the process of transitioning these recipes from using cosima-cookbook infrastructure to load model output to an intake catalogue. That said, you will find recipes that use either method to access model data.
We strongly urge you to transition to intake catalogue and (pretty please 🥺) help us with converting all the recipes to using that!
The notebook ACCESS-NRI_Intake_Catalog outlines the basic philosophy of the Intake catalog and how to transition from using the cosima-cookbook to the Intake catalogue. This is the best place to start if you are not familiar with the Intake catalog.
Also included here are some other tutorials, related to techniques (e.g., Making_Maps_with_Cartopy.ipynb) or tools (e.g., Model Agnostic Analysis). Last, note that you can still find here some other tutorials related to the deprecated Python package cosima_cookbook, which was the old tool we used to load model output with. Note: not to be confused with the Cookbook of Recipes you are looking at!
The main part of this cookbook: All the recipes! These are Jupyter notebooks for either simple or not-so-simple diagnostics and analyses. All notebooks are aimed to be self-contained and well-documented and explained. If you can find a recipe that suits your purposes, then this is the best place to start.
Jupyter notebooks to reproduce (as far as possible) the figures from the ACCESS-OM2 model announcement paper (GMD, 2020). These notebooks are mostly uncommented, but they should be functional. They are intended to demonstrate methods to undertake the calculations used in the paper.
We request that users of ACCESS-OM2 model code or output consider:
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citing Kiss et al. (2020) (http://doi.org/10.5194/gmd-13-401-2020)
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including an acknowledgement such as the following:
The authors thank the vibrant community of the Consortium for Ocean-Sea Ice Modelling in Australia (COSIMA; http://www.cosima.org.au) for making the ACCESS-OM2 suite of models available at https://github.com/COSIMA/access-om2.
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let us know of any publications which use these models or data so we can add them to our list.
If you use a recipe from the Cookbook for your research or teaching, or have based your analysis on one of the recipes, we would be grateful if you could cite: