Hello John,
> Im good with either/both axis = "ensemble" and/or
> standard_name = "ensemble_member_identifier".
>
> for backwards compatibility, we could consider recognizing
> standard_name = "realization".
do we need anything new - or is standard_name = "realization" enough?
I prefer "realization" to "ensemble" as I think its a bit more neutral -
for instance you can
produce a set of realizations of past and future climates using
detection and attribution techniques, its not clear (to me) that
"ensemble" is the most natural term for these. I think the term
ensemble is a bit loaded to imply a production technique, whereas
realization is more descriptive of the intent. (But I'm happy to be
wrong on this.)
>From what I remember a lot of the issues that caused the previous
discussion on ensembles to stall were around the aggregation of
different files into a single ensemble file, and what you do in this
case to maintain traceability back to the original model experiments.
So a scenario something like:
1. There is a repository of CMIP5 integrations (a collection of
mega-ensembles): a number of models, with a number of initial conditions
and a number of forcing scenarios. The output from each model
integration is stored in its own set of NetCDF files with global
attributes likse source, forcing, experiment, model, institute,
realization used to identify this data in the CMIP5 mega-ensemble. Each
model can be on a different grid.
2. A data user takes all (or a selection of) the files for a
mega-ensemble and puts them on the *same* space-time sampling for
analysis. e.g. decadal mean global means or continent means
3. The result of the analysis may be a reduced size to the original data
and so comfortably fit into one file. If the user wants to share this
data with others and maitain links to the original model integrations -
how do they do this?
I don't know if/when we want to return to this analysis and aggregation
case (is it a CF problem?). To me at least, it feels logically related
to some of the discussion around station data - though I didn't follow
this discussion that closely -
https://cf-pcmdi.llnl.gov/trac/ticket/37#comment:34. As I understood it
the problem there was 'aggregating' over instruments to for a depth
coordinate, whereas here we are aggregating over model integrations to
give an ensemble coordinate.
Jamie
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Received on Wed Mar 17 2010 - 04:14:17 GMT
