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xnemogcm: Presubmission Inquiry #154

@rcaneill

Description

@rcaneill

Submitting Author: Romain Caneill (@rcaneill)
Package Name: xnemogcm
One-Line Description of Package: Interface to open NEMO global circulation model output dataset with xarray and create a xgcm grid.
Repository Link (if existing): https://github.com/rcaneill/xnemogcm/


Code of Conduct & Commitment to Maintain Package

Description

xnemogcm is an interface to open NEMO ocean global circulation model output dataset and create a xgcm grid. NEMO 3.6, 4.0, and 4.2.0 are tested and supported. It can handle large simulations, is aware of meshgrid files, and makes it easy to handle the netCDF outputs od NEMO.

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checks that satisfy community requirements. If your package fits into an
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Scope

  • Please indicate which category or categories.
    Check out our [package scope page][PackageCategories] to learn more about our
    scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

  • Data retrieval

  • Data extraction

  • Data processing/munging

  • Data deposition

  • Data validation and testing

  • Data visualization

  • Workflow automation

  • Citation management and bibliometrics

  • Scientific software wrappers

  • Database interoperability

Domain Specific & Community Partnerships

  • Geospatial

  • Education

  • Pangeo

  • Unsure/Other (explain below)

  • Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

xnemogcm extracts the NEMO output and adds metadata (+ do some other things as change coordinate names, etc), and produces new xarray datasets. It is thus data processing.

I checked the unsure/Other box as a more specific area is physical oceanography.

  • Who is the target audience and what are the scientific applications of this package?

The target audience is anyone working with NEMO outputs and python. The scientific applications are any analyse that one want to do with NEMO outputs.

  • Are there other Python packages that accomplish similar things? If so, how does yours differ?

Yes, xorca. My package differs as 1) it is more recent, updated to work with newer versions of NEMO, and 2) it uses a very different method to sort variables on the proper grid point (center, face, etc) (cf https://xgcm.readthedocs.io/en/latest/grids.html). xorca uses hardcoded variables, while xnemogcm uses attributes (either output directly by NEMO, or they can also be given while calling the processing functions).

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