Data section update#1131
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charles-turner-1 wants to merge 5 commits intopaige/data-update-1124from
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charles-turner-1
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Bit of cleanup I need to do here, but let me know whether you think the extra detail is necessary @paigem - I reinstated most of it from the previous catalog bits & just changed the routing |
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| A simple use case of the ACCESS-NRI Intake catalog is a user wants to plot a timeseries of a variable from a specific data product.<br> | ||
| For example, the user is interested in plotting a scalar ocean variable called _temp\_global\_ave_ for an [ACCESS-ESM1.5](/models/access-esm) run called _HI\_CN\_05_ (data product). This is an historical run using the same configuration as CMIP6 ACCESS-ESM1.5 historical _r1i1p1f1_, except that the phosphorus limitation within [CASA-CNP](/models/model_components/bgc_land#casa-cnp) is disabled. |
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This could probably be simplified? Maybe...
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| A simple use case of the ACCESS-NRI Intake catalog is a user wants to plot a timeseries of a variable from a specific data product.<br> | |
| For example, the user is interested in plotting a scalar ocean variable called _temp\_global\_ave_ for an [ACCESS-ESM1.5](/models/access-esm) run called _HI\_CN\_05_ (data product). This is an historical run using the same configuration as CMIP6 ACCESS-ESM1.5 historical _r1i1p1f1_, except that the phosphorus limitation within [CASA-CNP](/models/model_components/bgc_land#casa-cnp) is disabled. | |
| We are interested in plotting a scalar ocean variable called _temp\_global\_ave_ for an [ACCESS-ESM1.5](/models/access-esm) run called _HI\_CN\_05_. This is an historical run using the same configuration as the CMIP6 ACCESS-ESM1.5 historical _r1i1p1f1_, with the phosphorus limitation within [CASA-CNP](/models/model_components/bgc_land#casa-cnp) disabled. |
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| First, load the catalog as follows: | ||
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| ```python | ||
| import intake | ||
| catalog = intake.cat.access_nri | ||
| ``` | ||
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| To see all available catalogs, run: | ||
| ``` | ||
| catalog | ||
| ``` | ||
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| Now you can load and plot available datasets for the <i>temp_global_ave</i> variable of the <i>HI_CN_05</i> data product as follows: | ||
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| ```python | ||
| import matplotlib.pyplot as plt | ||
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| # This returns an xarray Dataset | ||
| dataset = catalog["HI_CN_05"].search(variable="temp_global_ave").to_dask() | ||
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| # Plot the data | ||
| dataset["temp_global_ave"].plot() | ||
| plt.title("") | ||
| plt.grid() | ||
| ``` |
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Maybe this could be simplified further too? Code is simple enough we probably don't need to walk the user through each step.
Suggested change
| First, load the catalog as follows: | |
| ```python | |
| import intake | |
| catalog = intake.cat.access_nri | |
| ``` | |
| To see all available catalogs, run: | |
| ``` | |
| catalog | |
| ``` | |
| Now you can load and plot available datasets for the <i>temp_global_ave</i> variable of the <i>HI_CN_05</i> data product as follows: | |
| ```python | |
| import matplotlib.pyplot as plt | |
| # This returns an xarray Dataset | |
| dataset = catalog["HI_CN_05"].search(variable="temp_global_ave").to_dask() | |
| # Plot the data | |
| dataset["temp_global_ave"].plot() | |
| plt.title("") | |
| plt.grid() | |
| ``` | |
| We can load and plot <i>temp_global_ave</i> for <i>HI_CN_05</i> as follows: | |
| ```python | |
| import intake | |
| import matplotlib.pyplot as plt | |
| # Load the catalogue | |
| catalog = intake.cat.access_nri | |
| # This returns an Xarray Dataset | |
| dataset = catalog["HI_CN_05"].search(variable="temp_global_ave").to_dask() | |
| # Plot the data | |
| dataset["temp_global_ave"].plot() | |
| plt.title("") | |
| plt.grid() |
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Maybe a link to the access-nri-intake-catalog readthedocs tutorial somewhere too?
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Whoops - this was on the old page and I thought it had gotten dragged in for free. I seem to have removed it... Definitely in agreement with you!
charles-turner-1
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Feb 9, 2026
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Accidentally left this comment as a pending review all weekend... Fixing it up now!
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Whoops - this was on the old page and I thought it had gotten dragged in for free. I seem to have removed it... Definitely in agreement with you!
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