id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
242181620,MDU6SXNzdWUyNDIxODE2MjA=,1475,Allow DataArray to hold cell boundaries as coordinate variables,25473287,open,0,,,14,2017-07-11T20:58:44Z,2023-08-24T13:21:05Z,,NONE,,,,"Cell boundaries can be either N+1 sized arrays as suggested by xgcm/xmitgcm#15, or (N,2) sized arrays as suggested by [the CF convention](http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#cell-boundaries). However, a DataArray cannot hold both kinds of coordinate variables because they contain a new dimension.

If you try to assign a new coordinate to a DataArray by `dr.assign_coords()`, you will get
`ValueError: cannot add coordinates with new dimensions to a DataArray`

On the other hand, if your DataSet contains cell boundary variables (for example, #667), the bounds will be dropped when you extract a single variable into a DataArray.

Having cell bounds available in a DataArray is important for a couple of applications:

- Pass cell bounds to DataArray's plotting methods (xgcm/xmitgcm#15). I am aware of the discussion about inferring boundaries (#781). However, for the [Cube-Sphere grid](http://wiki.seas.harvard.edu/geos-chem/index.php/GEOS-Chem_HP#Cubed-sphere_Grid_Geometry) or the Lat-Lon-Cap grid ([reference](http://www.geosci-model-dev.net/8/3071/2015/)) which have tiles covering the poles, I have to explicitly pass cell bounds to the original plt.pcolormesh() to get a good-looking plot. (see [this comment](https://github.com/xgcm/xmitgcm/issues/15#issuecomment-314326358) for details)

- For conservative (i.e. area-weighted) regridding (mentioned in #486).  Cell centers are enough for bilinear interpolation or other simple resamping, but for any Finite-Volume meshes, knowing the boundaries is crucial if you want to conserve the total amount of mass or flux.

Plotting or regridding will work fine if you pass cell bounds as an additional argument to a wrapper function. However, having a single DataArray object containing boundary information seems like a more elegant solution. Is it possible to **let DataArray accept N+1 sized coordinate variables, and be able to inherit them from the parent DataSet**? If that's too drastic, is it possible to write an [accessor](http://xarray.pydata.org/en/stable/internals.html#extending-xarray) to extend DataArray's capability? Say, a ""bound"" accessor for a new attribute `ds.bnd['lat_b']`, which can be kept when a DataArray gets extracted (`ds['data_var'].bnd['lat_b']` )? Does this make sense?","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1475/reactions"", ""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 1}",,,13221727,issue
340486433,MDU6SXNzdWUzNDA0ODY0MzM=,2281,Does interp() work on curvilinear grids (2D coordinates) ? ,25473287,open,0,,,28,2018-07-12T04:36:43Z,2020-09-04T19:24:32Z,,NONE,,,,"I am evaluating `interp()` against xESMF. [Here](http://xesmf.readthedocs.io/en/latest/Curvilinear_grid.html)'s how xESMF would regrid the built-in `'rasm'` data to a regular lat-lon grid.

Seems like `interp()` can convert rectilinear grids (1D coordinates) to curvilinear grids (2D coordinates), according to the [last example](http://xarray.pydata.org/en/stable/interpolation.html#example). How about the reverse? Can it convert 2D coordinate to 1D, or to another 2D coordinate?

That's the test data:
```
dr = xr.tutorial.load_dataset('rasm')['Tair']
...
Coordinates:
  * time     (time) datetime64[ns] 1980-09-16T12:00:00 1980-10-17 ...
    xc       (y, x) float64 189.2 189.4 189.6 189.7 189.9 190.1 190.2 190.4 ...
    yc       (y, x) float64 16.53 16.78 17.02 17.27 17.51 17.76 18.0 18.25 ...
```

That's a simple destination grid:
```
lon = xr.DataArray(np.linspace(-180, 180, 120), dims=['lon'])
lat = xr.DataArray(np.linspace(-90, 90, 60), dims=['lat'])
```

I would expect a syntax like:
```
dr_out = dr.interp(xc=lon, yc=lat)
```

But I got `ValueError: dimensions ['xc', 'yc'] do not exist`, because`interp()` only accepts dimensions (which must be 1D), not coordinates. 

`dr.interp(x=lon, y=lat)` runs but the result is not correct. This is expected because `x` does not mean longitude in the original data. 

@crusaderky @fujiisoup ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2281/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue