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
1925758025,I_kwDOAMm_X85yyLxJ,8271,time encoding fails for subdaily frequencies and `days since`,5659125,closed,0,,,3,2023-10-04T09:12:59Z,2023-10-06T14:08:53Z,2023-10-06T14:08:53Z,NONE,,,,"### What happened?

This is my example, that doesn't work since `v2023.09.0`:

```python
import numpy as np
import pandas as pd
import xarray as xr

time = pd.date_range(""1970-01-01"", ""1970-01-31"", freq=""6h"")
ds = xr.Dataset(coords=dict(time=time))

units = ""days since 1960-01-01 00:00:00""
calendar = ""gregorian""
encoding = dict(time=dict(units=units, calendar=calendar, dtype=np.dtype(""float64"")))

ds.to_netcdf(""test.nc"", encoding=encoding)

! ncdump -v time test.nc
```

This gives the following output:

```
netcdf test {
dimensions:
	time = 121 ;
variables:
	double time(time) ;
		time:_FillValue = NaN ;
		time:units = ""days since 1960-01-01"" ;
		time:calendar = ""gregorian"" ;
data:

 time = 3653, 3653, 3653, 3653, 3654, 3654, 3654, 3654, 3655, 3655, 3655, 
    3655, 3656, 3656, 3656, 3656, 3657, 3657, 3657, 3657, 3658, 3658, 3658, 
    3658, 3659, 3659, 3659, 3659, 3660, 3660, 3660, 3660, 3661, 3661, 3661, 
    3661, 3662, 3662, 3662, 3662, 3663, 3663, 3663, 3663, 3664, 3664, 3664, 
    3664, 3665, 3665, 3665, 3665, 3666, 3666, 3666, 3666, 3667, 3667, 3667, 
    3667, 3668, 3668, 3668, 3668, 3669, 3669, 3669, 3669, 3670, 3670, 3670, 
    3670, 3671, 3671, 3671, 3671, 3672, 3672, 3672, 3672, 3673, 3673, 3673, 
    3673, 3674, 3674, 3674, 3674, 3675, 3675, 3675, 3675, 3676, 3676, 3676, 
    3676, 3677, 3677, 3677, 3677, 3678, 3678, 3678, 3678, 3679, 3679, 3679, 
    3679, 3680, 3680, 3680, 3680, 3681, 3681, 3681, 3681, 3682, 3682, 3682, 
    3682, 3683 ;
}
```

It seems like the subdaily fraction is truncated. Note, that this does not happend, if i set the units to the start of the time range, e.g., units = ""days since 1970-01-01 00:00:00"". This results correctly in 

```
netcdf test {
dimensions:
	time = 121 ;
variables:
	double time(time) ;
		time:_FillValue = NaN ;
		time:units = ""days since 1970-01-01"" ;
		time:calendar = ""gregorian"" ;
data:

 time = 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3, 3.25, 
    3.5, 3.75, 4, 4.25, 4.5, 4.75, 5, 5.25, 5.5, 5.75, 6, 6.25, 6.5, 6.75, 7, 
    7.25, 7.5, 7.75, 8, 8.25, 8.5, 8.75, 9, 9.25, 9.5, 9.75, 10, 10.25, 10.5, 
    10.75, 11, 11.25, 11.5, 11.75, 12, 12.25, 12.5, 12.75, 13, 13.25, 13.5, 
    13.75, 14, 14.25, 14.5, 14.75, 15, 15.25, 15.5, 15.75, 16, 16.25, 16.5, 
    16.75, 17, 17.25, 17.5, 17.75, 18, 18.25, 18.5, 18.75, 19, 19.25, 19.5, 
    19.75, 20, 20.25, 20.5, 20.75, 21, 21.25, 21.5, 21.75, 22, 22.25, 22.5, 
    22.75, 23, 23.25, 23.5, 23.75, 24, 24.25, 24.5, 24.75, 25, 25.25, 25.5, 
    25.75, 26, 26.25, 26.5, 26.75, 27, 27.25, 27.5, 27.75, 28, 28.25, 28.5, 
    28.75, 29, 29.25, 29.5, 29.75, 30 ;
}
```

### What did you expect to happen?

I expect subdaily frequencies to be encoded correctly also if the units startdate is different from the startdate of the time axis, e.g. `v2023.08.0` correctly preserves fractions:

```
netcdf test {
dimensions:
	time = 121 ;
variables:
	double time(time) ;
		time:_FillValue = NaN ;
		time:units = ""days since 1960-01-01"" ;
		time:calendar = ""gregorian"" ;
data:

 time = 3653, 3653.25, 3653.5, 3653.75, 3654, 3654.25, 3654.5, 3654.75, 3655, 
    3655.25, 3655.5, 3655.75, 3656, 3656.25, 3656.5, 3656.75, 3657, 3657.25, 
    3657.5, 3657.75, 3658, 3658.25, 3658.5, 3658.75, 3659, 3659.25, 3659.5, 
    3659.75, 3660, 3660.25, 3660.5, 3660.75, 3661, 3661.25, 3661.5, 3661.75, 
    3662, 3662.25, 3662.5, 3662.75, 3663, 3663.25, 3663.5, 3663.75, 3664, 
    3664.25, 3664.5, 3664.75, 3665, 3665.25, 3665.5, 3665.75, 3666, 3666.25, 
    3666.5, 3666.75, 3667, 3667.25, 3667.5, 3667.75, 3668, 3668.25, 3668.5, 
    3668.75, 3669, 3669.25, 3669.5, 3669.75, 3670, 3670.25, 3670.5, 3670.75, 
    3671, 3671.25, 3671.5, 3671.75, 3672, 3672.25, 3672.5, 3672.75, 3673, 
    3673.25, 3673.5, 3673.75, 3674, 3674.25, 3674.5, 3674.75, 3675, 3675.25, 
    3675.5, 3675.75, 3676, 3676.25, 3676.5, 3676.75, 3677, 3677.25, 3677.5, 
    3677.75, 3678, 3678.25, 3678.5, 3678.75, 3679, 3679.25, 3679.5, 3679.75, 
    3680, 3680.25, 3680.5, 3680.75, 3681, 3681.25, 3681.5, 3681.75, 3682, 
    3682.25, 3682.5, 3682.75, 3683 ;
}
```

### Minimal Complete Verifiable Example

```Python
import numpy as np
import pandas as pd
import xarray as xr

time = pd.date_range(""1970-01-01"", ""1970-01-31"", freq=""6h"")
ds = xr.Dataset(coords=dict(time=time))

units = ""days since 1960-01-01 00:00:00""
calendar = ""gregorian""
encoding = dict(time=dict(units=units, calendar=calendar, dtype=np.dtype(""float64"")))

ds.to_netcdf(""test.nc"", encoding=encoding)

! ncdump -v time test.nc
```


### MVCE confirmation

- [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [X] Complete example — the example is self-contained, including all data and the text of any traceback.
- [X] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result.
- [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

### Relevant log output

_No response_

### Anything else we need to know?

This is still an issue in the current main.

### Environment

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:39:40) [Clang 15.0.7 ]
python-bits: 64
OS: Darwin
OS-release: 22.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: (None, 'UTF-8')
libhdf5: 1.14.2
libnetcdf: 4.9.2

xarray: 2023.9.1.dev12+gd5f17858
pandas: 2.1.1
numpy: 1.24.4
scipy: 1.11.3
netCDF4: 1.6.4
pydap: installed
h5netcdf: 1.2.0
h5py: 3.9.0
Nio: None
zarr: 2.16.1
cftime: 1.6.2
nc_time_axis: 1.4.1
PseudoNetCDF: 3.2.2
iris: 3.7.0
bottleneck: 1.3.7
dask: 2023.9.3
distributed: 2023.9.3
matplotlib: 3.8.0
cartopy: 0.22.0
seaborn: 0.13.0
numbagg: 0.2.2
fsspec: 2023.9.2
cupy: None
pint: 0.20.1
sparse: 0.14.0
flox: 0.7.2
numpy_groupies: 0.10.2
setuptools: 68.2.2
pip: 23.2.1
conda: None
pytest: 7.4.2
mypy: None
IPython: 8.16.1
sphinx: None

</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8271/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
1507817863,PR_kwDOAMm_X85GCbr9,7399,fix convert_calendar on static variables in Dataset,5659125,open,0,,,3,2022-12-22T12:44:34Z,2023-10-04T08:10:36Z,,FIRST_TIME_CONTRIBUTOR,,0,pydata/xarray/pulls/7399,"<!-- Feel free to remove check-list items aren't relevant to your change -->

- [x] Closes #7398
- [x] Tests added
- [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst`

This PR implements the workaround suggested in #6879.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7399/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
1498255931,I_kwDOAMm_X85ZTZI7,7381,Document cftime arithmetic limitations,5659125,open,0,,,3,2022-12-15T11:24:04Z,2023-07-17T09:34:12Z,,NONE,,,,"### What is your issue?

Hey all,
i have quick use case where i am unsure if that's related to xarray. I just want to do simple arithmetics with a cftime time axis, e.g.

```python
import xarray as xr
import numpy as np
time = xr.DataArray(xr.cftime_range(start=""2000"", periods=6, freq=""1MS"", calendar=""noleap""), dims='time')
```
and then, e.g., compute mid of those timesteps:
```python
time[:-1] + 0.5 * time.diff('time')
```
which results in
```
---------------------------------------------------------------------------
UFuncTypeError                            Traceback (most recent call last)
Input In [72], in <cell line: 1>()
----> 1 time[1:] + 0.5 * time.diff('time')

File /work/ch0636/g300046/conda_envs/pyremo-dev/lib/python3.9/site-packages/xarray/core/_typed_ops.py:206, in DataArrayOpsMixin.__add__(self, other)
    205 def __add__(self, other):
--> 206     return self._binary_op(other, operator.add)

File /work/ch0636/g300046/conda_envs/pyremo-dev/lib/python3.9/site-packages/xarray/core/dataarray.py:3530, in DataArray._binary_op(self, other, f, reflexive)
   3526 other_variable = getattr(other, ""variable"", other)
   3527 other_coords = getattr(other, ""coords"", None)
   3529 variable = (
-> 3530     f(self.variable, other_variable)
   3531     if not reflexive
   3532     else f(other_variable, self.variable)
   3533 )
   3534 coords, indexes = self.coords._merge_raw(other_coords, reflexive)
   3535 name = self._result_name(other)

File /work/ch0636/g300046/conda_envs/pyremo-dev/lib/python3.9/site-packages/xarray/core/_typed_ops.py:396, in VariableOpsMixin.__add__(self, other)
    395 def __add__(self, other):
--> 396     return self._binary_op(other, operator.add)

File /work/ch0636/g300046/conda_envs/pyremo-dev/lib/python3.9/site-packages/xarray/core/variable.py:2519, in Variable._binary_op(self, other, f, reflexive)
   2516 attrs = self._attrs if keep_attrs else None
   2517 with np.errstate(all=""ignore""):
   2518     new_data = (
-> 2519         f(self_data, other_data) if not reflexive else f(other_data, self_data)
   2520     )
   2521 result = Variable(dims, new_data, attrs=attrs)
   2522 return result

UFuncTypeError: ufunc 'add' cannot use operands with types dtype('O') and dtype('<m8[ns]')
```
The problem is the differentiation results in `np.timedelta64` objects:
```python
time.diff('time')
```
![grafik](https://user-images.githubusercontent.com/5659125/207844626-76adf571-92f7-4645-9e9d-5ba01d08afa3.png)
with which the arithmetics are not implemented in `cftime`. However, differentiation with `datetime.timdelta` (which is wrapped by `np.timedelta64`) works in this case since it's implemented in cftime, e.g., when i do `np.diff`, it works:
```python
time[:-1] + 0.5 * np.diff(time)
```
![grafik](https://user-images.githubusercontent.com/5659125/207847974-c263ae12-142e-4004-bcdf-847379b3dc75.png)

i get the expected result. I am not sure what to expect from xarray and if this might be an issue of cftime (e.g., implement differentiation with `np.timedelta64`). I was wondering why the differentiation with cftime objects results in `np.timedelta64` and not `datetime.timedelta` objects (like in the pure numpy differentation).
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7381/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
1507705136,I_kwDOAMm_X85Z3cEw,7398,convert_calendar adds time coordinate to static variables,5659125,open,0,,,1,2022-12-22T11:27:11Z,2023-01-15T15:51:21Z,,NONE,,,,"### What is your issue?

I just recognized that `convert_calendar` adds a time coordinate to variables that have been static before, e.g.,

```python
import numpy as np
import pandas as pd
import xarray as xr

np.random.seed(0)
temperature = 15 + 8 * np.random.randn(2, 2, 3)
precipitation = 10 * np.random.rand(2, 2, 3)
orog = 0 + 100 * np.random.randn(2, 2)
lon = [[-99.83, -99.32], [-99.79, -99.23]]
lat = [[42.25, 42.21], [42.63, 42.59]]
time = pd.date_range(""2014-09-06"", periods=3)
reference_time = pd.Timestamp(""2014-09-05"")


ds = xr.Dataset(
    data_vars=dict(
        temperature=([""x"", ""y"", ""time""], temperature),
        precipitation=([""x"", ""y"", ""time""], precipitation),
        orog = ([""x"", ""y""], orog)
    ),
    coords=dict(
        lon=([""x"", ""y""], lon),
        lat=([""x"", ""y""], lat),
        time=time,
        reference_time=reference_time,
    ),
    attrs=dict(description=""Weather related data.""),
)
ds
```
![grafik](https://user-images.githubusercontent.com/5659125/209124247-4d6bb64f-8396-4a90-bcce-c420b022b0cf.png)
I would like to convert the time axis to cftime objects using
```python
ds.convert_calendar(ds.time.dt.calendar, use_cftime=True)
ds
```
![grafik](https://user-images.githubusercontent.com/5659125/209124475-2ca60508-2d39-432b-816d-0f2718cda5b4.png)
However, this results in an unexpected time coordinate in the `orog` variable...","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7398/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue