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# CMIP6 Hackathon Project Template | ||
# Ocean biogeochemistry team | ||
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[This template](https://github.com/cmip6hack/project-template) provides a starting point for [CMIP6 Hackathon](https://cmip6hack.github.io/#/) projects. | ||
## Questions: | ||
This project will examine historical simulations and future projections of ocean carbon and heat uptake and storage in the CMIP6 ensemble, and explore their impacts on marine ecosystems drivers, with a focus on primary productivity. Hacking will explore: | ||
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### What's included? | ||
1. How do models simulate carbon and heat uptake compared to available observations? What are future projections under different ssp’s? what regions dominate carbon and heat uptake vs. storage? What are differences across models (uptake rates, regional differences, etc.) and what processes might explain these differences? | ||
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1. `catalogs`: data catalogs that can be used by Intake-ESM. | ||
1. `environments`: Conda environment files for the NCAR/Google Cloud deployments. | ||
1. `notebooks`: a place for storing Jupyter Notebooks. | ||
1. `README.md`: this document - consider modifying to make it a description of your project on GitHub. | ||
1. `LICENSE`: a default (MIT) license file for your project. You can change this if you feel the need. | ||
2. How well do models simulate the mean distribution and long-term trends of ecosystem drivers (SST, pH/aragonite saturation depth, [O2]/hypoxic depth, NPP) compared to available observations? Can we identify persistent or new biases since CMIP5? What are CMIP6 projections for marine ecosystem drivers in a warming climate? What are spatial characteristics, timescales of emergence, and differences across models? Is there a relationship between models’ carbon and heat uptake efficiency and the severity of their projected impacts on these ecosystem drivers? How did increased climate sensitivity since CMIP5 in certain models (e.g. CESM2) influence these impacts in these models? | ||
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### How to use this Template | ||
3. Projections of NPP especially showcase major differences across CMIP5 models in sign and amplitude over important ocean regions (Eastern/central tropical Pacific, Subpolar gyres, etc. Fig 5. Bopp et al 2013). Does this spread still exist in CMIP6? Do projected changes in carbon export at depth mirror the changes in NPP? What physical and biogeochemical processes explain NPP and carbon export changes across regions and models (e.g. changes in easterlies, upwelling, nutrient transport by the EUC or the overturning circulation, stratification and ventilation, remineralization rates, etc.)? | ||
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Project leads should follow the next four steps. This only needs to be done once. | ||
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1. Navigate to https://github.com/cmip6hack/project-template | ||
2. Click the "Use this template" button | ||
3. Name your project (consider prepending with "cmip6hack", so something like `cmip6hack-myproject`) | ||
4. Provide a brief description | ||
5. Tell your teammates where to find your repository and tell them to "Fork" the project. | ||
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Once the initial setup is done, everyone will want to clone the repository onto the compute system they plan to use for the hackathon. | ||
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1. Open a JupyterLab session on the system you plan to use. | ||
1. Open a terminal in the JupyterLab environment. | ||
1. Clone your project: `git clone https://github.com/username/cmip6hack-myproject.git` | ||
1. Get to work! | ||
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### How to make your project citable | ||
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[Zenodo](https://about.zenodo.org/) is a data archiving tool that can help make your project citable by assigning a DOI to the project's GitHub repository. | ||
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Follow the guidelines here https://guides.github.com/activities/citable-code | ||
We will prioritize developing efficient workflows for loading, analysis, and plotting of model outputs and comparison to observations, and aim for process-based examination of model projections, inter-model differences, and model biases. |
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{ | ||
"esmcat_version": "0.1.0", | ||
"id": "pangeo-cmip6", | ||
"description": "This is an ESM collection for CMIP6 Zarr data residing in Pangeo's Google Storage.", | ||
"catalog_file": "https://storage.googleapis.com/pangeo-cmip6/pangeo-cmip6-zarr-consolidated-stores.csv", | ||
"attributes": [ | ||
{ | ||
"column_name": "activity_id", | ||
"vocabulary": "https://raw.githubusercontent.com/WCRP-CMIP/CMIP6_CVs/master/CMIP6_activity_id.json" | ||
}, | ||
{ | ||
"column_name": "source_id", | ||
"vocabulary": "https://raw.githubusercontent.com/WCRP-CMIP/CMIP6_CVs/master/CMIP6_source_id.json" | ||
}, | ||
{ | ||
"column_name": "institution_id", | ||
"vocabulary": "https://raw.githubusercontent.com/WCRP-CMIP/CMIP6_CVs/master/CMIP6_institution_id.json" | ||
}, | ||
{ | ||
"column_name": "experiment_id", | ||
"vocabulary": "https://raw.githubusercontent.com/WCRP-CMIP/CMIP6_CVs/master/CMIP6_experiment_id.json" | ||
}, | ||
{ "column_name": "member_id", "vocabulary": "" }, | ||
{ | ||
"column_name": "table_id", | ||
"vocabulary": "https://raw.githubusercontent.com/WCRP-CMIP/CMIP6_CVs/master/CMIP6_table_id.json" | ||
}, | ||
{ "column_name": "variable_id", "vocabulary": "" }, | ||
{ | ||
"column_name": "grid_label", | ||
"vocabulary": "https://raw.githubusercontent.com/WCRP-CMIP/CMIP6_CVs/master/CMIP6_grid_label.json" | ||
}, | ||
{ | ||
"column_name": "version", | ||
"vocabulary": "" | ||
}, | ||
{ | ||
"column_name": "dcpp_start_year", | ||
"vocabulary": "" | ||
} | ||
], | ||
"assets": { | ||
"column_name": "zstore", | ||
"format": "zarr" | ||
}, | ||
"aggregation_control": { | ||
"variable_column_name": "variable_id", | ||
"groupby_attrs": [ | ||
"activity_id", | ||
"institution_id", | ||
"source_id", | ||
"experiment_id", | ||
"table_id", | ||
"grid_label" | ||
], | ||
"aggregations": [ | ||
{ | ||
"type": "union", | ||
"attribute_name": "variable_id" | ||
}, | ||
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{ | ||
"type": "join_new", | ||
"attribute_name": "member_id", | ||
"options": { "coords": "minimal", "compat": "override" } | ||
}, | ||
{ | ||
"type": "join_new", | ||
"attribute_name": "dcpp_init_year", | ||
"options": { "coords": "minimal", "compat": "override" } | ||
} | ||
] | ||
} | ||
} |
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