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6 changes: 3 additions & 3 deletions docs/model_evaluation/model_diagnostics/index.md
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In addition to monitoring a live model, the package also provides the functionality to load, visualise and compare legacy ACCESS model data with the live model.

For more information and tutorials, please visit:
<div class="card-container">
For more information and tutorials, please visit <a href="https://med-live-diagnostics.readthedocs.io/en/latest/index.html" target="_blank">Model Diagnostics Documentation</a>
<!-- <div class="card-container">
<a href="https://med-live-diagnostics.readthedocs.io/en/latest/index.html" class="vertical-card aspect-ratio2to1" target="_blank">
<div class="card-image-container">
<img src="../../../assets/access_logo_rgb.svg" alt="ACCESS-NRI Model Diagnostics Documentation" class="img-contain white-background with-padding"></img>
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<div class="card-text-container bold ">Model Diagnostics Documentation</div>
</a>
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## Showcase: Monitoring total seawater mass of an ACCESS-CM2 run

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2 changes: 1 addition & 1 deletion docs/model_evaluation/model_evaluation_data/index.md
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# Data
# Climate Data


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The ACCESS-NRI Intake catalog aims to provide a way for Python users to discover and load data across a broad range of climate data products available on <i>Gadi</i>.

For detailed information, tutorials and more, please go to:
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For detailed information, tutorials and more, please go to <a href="https://access-nri-intake-catalog.readthedocs.io/en/latest/index.html" target="_blank">ACCESS-NRI intake catalog documentation</a>.
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<a href="https://access-nri-intake-catalog.readthedocs.io/en/latest/index.html" class="vertical-card aspect-ratio2to1" target="_blank">
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<img src="../../assets/model_evaluation/accessnri_intake.png" alt="ACCESS-NRI intake catalog documentation" class="img-contain white-background with-padding"></img>
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<div class="card-text-container bold ">Documentation</div>
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## What is the ACCESS-NRI Intake catalog?

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NCI not only hosts numerous datasets for climate research, it also manages and optimises curated data collections.

Here, you can browse and search the available NCI data collections:
Here, you can browse and search the available <a href="https://geonetwork.nci.org.au/" target="_blank">NCI data collections</a>.

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<a href="https://geonetwork.nci.org.au/" target="_blank" class="vertical-card aspect-ratio2to1">
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<img src="/assets/model_evaluation/logo_nci_data_catalogs.png" alt="NCI Data Collections" class="img-contain white-background"></img>
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<div class="card-text-container bold">Search for data here</div>
</a>
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Some examples of NCI data collections include:
<ul>
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This documentation is tailored to using <i>ILAMB</i> on <i>Gadi</i> and, hence, it supplements rather than replaces the official documentation. Users are encouraged to read the <a href="https://www.ilamb.org/doc/" target="_blank">ILAMB documentation</a> and relevant <a href="https://www.ilamb.org/doc/tutorial.html" target="_blank">tutorials</a>.

ACCESS-NRI is releasing an NCI configuration of ILAMB under the name **ILAMB-workflow**.
ACCESS-NRI is releasing an NCI configuration of ILAMB under the name *ILAMB-workflow*.

**ILAMB-workflow** is the ACCESS-NRI software and data infrastructure that enables the ILAMB evaluation framework on NCI Gadi. It includes the **ILAMB Python packages**, a series of **ILAMB outputs for ACCESS model evaluation** and the **ILAMB-Data collection of observational datasets**. ILAMB-workflow is configured to use the existing NCI supported CMIP data collections.
*ILAMB-workflow* is the ACCESS-NRI software and data infrastructure that enables the ILAMB evaluation framework on NCI Gadi. It includes the

- *ILAMB* Python packages,
- a series of *ILAMB* outputs for ACCESS model evaluation,
- the *ILAMB-Data* collection of observational datasets.

ILAMB-workflow is configured to use the existing NCI supported CMIP data collections.

## Using ILAMB on Gadi

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### Loading the ILAMB-workflow modules
<!-- #### Load the `access-med` conda environment -->

To load the the `ilamb` module, execute the following commands:
To load the the *ilamb* module, execute the following commands:
```
module use /g/data/xp65/public/modules
module load conda/access-med
```

For ACCESS-NRI documentation on how to run <i>ILAMB</i> on <i>Gadi</i>, visit:
Visit <a href="https://ilamb-workflow.readthedocs.io/en/latest/?badge=latest" target="_blank">ACCESS-NRI documentation</a> on how to run <i>ILAMB</i> on <i>Gadi</i>.

<div class="card-container">
<!-- <div class="card-container">
<a href="https://ilamb-workflow.readthedocs.io/en/latest/?badge=latest" class="vertical-card aspect-ratio2to1" target="_blank">
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<img src="/assets/model_evaluation/logo_ilamb.png" alt="ILAMB on Gadi" class="img-cover white-background"></img>
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<div class="card-text-container bold ">Documentation for ILAMB on Gadi</div>
</a>
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<br>
To run <i>ILAMB</i>, you need to execute the command `ilamb-run` with a number of arguments/ files:
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```
<ul>
<li>
<code>config.cfg</code> defines which observables and observational datasets to be compared.
<i>config.cfg</i> defines which observables and observational datasets to be compared.
<li>
<code>model_setup.txt</code> defines the paths of models that to be compared.
<i>model_setup.txt</i> defines the paths of models that to be compared.
<li>
<code>regions.txt</code> defines the regions to be compared, e.g., <code>global</code>, <code>aust</code> (Australia), etc.
<i>regions.txt</i> defines the regions to be compared, e.g., <i>global</i>, <i>aust</i> (Australia), etc.
</ul>

While these files can be self-defined, ACCESS-NRI provides the necessary files and tools to set your model paths to run on <i>Gadi</i>. All you need to do is decide which observations and models you wish to compare.
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Numerous benchmark comparisons have been defined in the configuration file. The comparison of variables have been organised under different sections, such as the <i>Hydrology Cycle</i>.
<br>
For other variables, such as the <i>git Gross Primary Productivity</i> `gpp`, one or more datasets are available. For example, the gross primary productivity measurements of <a href="https://fluxnet.org/data/fluxnet2015-dataset/" target="_blank">FLUXNET2015</a>.
For other variables, such as the <i>git Gross Primary Productivity</i> (*gpp*), one or more datasets are available. For example, the gross primary productivity measurements of <a href="https://fluxnet.org/data/fluxnet2015-dataset/" target="_blank">FLUXNET2015</a>.
<br>
<br>
By clicking on a row in the table, you can expand it to see the underlying datasets used. The table's colourmap extends from best values in purple to worse data in orange.
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