Replies: 3 comments
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When I first built the catalog for CMIP6, I used the official "data reference syntax" document. In the "filename template" section, they used
There's no other reason other than the one I described above... You should be able to concatenate along the
{
"type": "join_new",
"attribute_name": "variant_label",
"options": { "coords": "minimal", "compat": "override" }
} I know this is not a perfect solution, but this is the easiest approach I can think of right now... |
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@jbusecke, how painful is making |
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This is actually something I do have to iron out in my brain too. I have now learned that for certain experiments these facets are not the same (makes sense in hindsight I guess). I believe this is only relevant for certain activities (e.g. forecasting) where from a single member several forecasts are initialized, so the member_id for each of the runs might stay the same, but the variant_label will have an appended identifier for the particular forecast. In my view this means that your approach to use variant_label is probably the safer one. |
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Working with the pangeo CMIP6 data, I find myself going back and forth between the attribute
variant_label
and the dimensionmember_id
, which I think are exactly the same thing.I have been working on a flexible way to combine/aggregate datasets with different variables/ensemble members etc here, which is entirely based on the datasets attributes (and a bit more flexible).
In order to make these aggregations, specifically the ensemble member aggregation, equivalent to what intake-esm does, I however need to 'artificially' change the
variant_label
attribute to amember_id
dimension.So I guess my question is: Why do we concatenate along 'member_id' in intake-esm, and not 'variant_label'?
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