convert_calendar adds a time dimension to all variables #10266
Description
What happened?
ds.convert_calendar will add a time dimension to all data_vars, even those that did not depend on it.
What did you expect to happen?
No response
Minimal Complete Verifiable Example
import xarray as xr
ds = xr.tutorial.open_dataset("air_temperature")
# Create a non-time dependent variable
ds["other"] = ds["air"].isel(time=0).drop_vars("time")
out = ds.convert_calendar("standard")
`ds`
<xarray.Dataset> Size: 31MB
Dimensions: (lat: 25, time: 2920, lon: 53)
Coordinates:
* lat (lat) float32 100B 75.0 72.5 70.0 67.5 65.0 ... 22.5 20.0 17.5 15.0
* lon (lon) float32 212B 200.0 202.5 205.0 207.5 ... 325.0 327.5 330.0
* time (time) datetime64[ns] 23kB 2013-01-01 ... 2014-12-31T18:00:00
Data variables:
air (time, lat, lon) float64 31MB 241.2 242.5 243.5 ... 296.2 295.7
other (lat, lon) float64 11kB 241.2 242.5 243.5 ... 296.9 296.8 296.6
Attributes:
Conventions: COARDS
title: 4x daily NMC reanalysis (1948)
description: Data is from NMC initialized reanalysis\n(4x/day). These a...
platform: Model
references: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly...
`out`
<xarray.Dataset> Size: 62MB
Dimensions: (time: 2920, lat: 25, lon: 53)
Coordinates:
* lat (lat) float32 100B 75.0 72.5 70.0 67.5 65.0 ... 22.5 20.0 17.5 15.0
* lon (lon) float32 212B 200.0 202.5 205.0 207.5 ... 325.0 327.5 330.0
* time (time) datetime64[ns] 23kB 2013-01-01 ... 2014-12-31T18:00:00
Data variables:
air (time, lat, lon) float64 31MB 241.2 242.5 243.5 ... 296.2 295.7
other (lat, lon, time) float64 31MB 241.2 241.2 241.2 ... 296.6 296.6
Attributes:
Conventions: COARDS
title: 4x daily NMC reanalysis (1948)
description: Data is from NMC initialized reanalysis\n(4x/day). These a...
platform: Model
references: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly...MVCE confirmation
- Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- Complete example — the example is self-contained, including all data and the text of any traceback.
- Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
- New issue — a search of GitHub Issues suggests this is not a duplicate.
- Recent environment — the issue occurs with the latest version of xarray and its dependencies.
Relevant log output
Anything else we need to know?
No response
Environment
INSTALLED VERSIONS
------------------
commit: None
python: 3.12.10 | packaged by conda-forge | (main, Apr 10 2025, 22:21:13) [GCC 13.3.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-1160.105.1.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_CA.UTF-8
LOCALE: ('en_CA', 'UTF-8')
libhdf5: 1.14.3
libnetcdf: 4.9.2
xarray: 2025.3.0
pandas: 2.2.3
numpy: 2.2.5
scipy: 1.15.2
netCDF4: 1.7.2
pydap: 3.5.4
h5netcdf: 1.6.1
h5py: 3.13.0
zarr: 2.18.7
cftime: 1.6.4
nc_time_axis: 1.4.1
iris: None
bottleneck: 1.4.2
dask: 2025.4.0
distributed: 2025.4.0
matplotlib: 3.10.1
cartopy: 0.24.0
seaborn: None
numbagg: None
fsspec: 2025.3.2
cupy: None
pint: 0.24.4
sparse: 0.16.0
flox: 0.10.1
numpy_groupies: 0.11.2
setuptools: 79.0.1
pip: 25.0.1
conda: None
pytest: 8.3.5
mypy: 1.15.0
IPython: 9.1.0
sphinx: 8.1.3