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
667203487,MDU6SXNzdWU2NjcyMDM0ODc=,4282,Values change when writing combined Dataset loaded with open_mfdataset,11723107,closed,0,,,1,2020-07-28T16:20:09Z,2022-04-09T03:00:55Z,2022-04-09T03:00:55Z,NONE,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

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**What happened**:

Loading two netcdf files with `open_mfdataset` then writing into a combined file results in some values changed in the file.

**What you expected to happen**:

That the written file contains the same values than the in-memory `Dataset` when read again.

**Minimal Complete Verifiable Example**:

```python
>>> import numpy as np
>>> import xarray as xr
>>> data1 = xr.open_dataset(""file1.nc"")
>>> data2 = xr.open_dataset(""file2.nc"")
>>> merged = xr.open_mfdataset([""file1.nc"", ""file2.nc""])
>>> np.all(np.isclose(merged[""u""].values[0], data1[""u""].values[0]))
True
>>> np.all(np.isclose(merged[""u""].values[-1], data2[""u""].values[-1]))
True
>>> merged.to_netcdf(""foo.nc"")
>>> merged_file = xr.load_dataset(""foo.nc"")
>>> np.all(np.isclose(merged_file[""u""].values, merged[""u""].values))
False
```

The files contain wind data from the ERA5 reanalysis, downloaded from [CDS](https://cds.climate.copernicus.eu/#!/home).

**Anything else we need to know?**:

The issue might be related to the scale and offset values of the variable. Continuing the example:

```python
>>> np.all(np.isclose(merged_file[""u""].values[0], data1[""u""].values[0]))
True
>>> np.all(np.isclose(merged_file[""u""].values[-1], data2[""u""].values[-1]))
False
```

Data from the first file seems to be correct.
When writing the combined dataset, the scale and offset from the first file are written to the combined file:

```python
>>> data1_nomas = xr.open_dataset(""file1.nc"", mask_and_scale=False)
>>> data2_nomas = xr.open_dataset(""file2.nc"", mask_and_scale=False)
>>> merged_file_nomas = xr.open_dataset(""foo.nc"", mask_and_scale=False)
>>> data1_nomas[""u""].attrs
{'scale_factor': 0.002397265127278432, 'add_offset': 25.620963232670736, '_FillValue': -32767, 'missing_value': -32767, 'units': 'm s**-1', 'long_name': 'U component of wind', 'standard_name': 'eastward_wind'}
>>> data2_nomas[""u""].attrs
{'scale_factor': 0.0024358825557859445, 'add_offset': 21.288035293585388, '_FillValue': -32767, 'missing_value': -32767, 'units': 'm s**-1', 'long_name': 'U component of wind', 'standard_name': 'eastward_wind'}
>>> merged_file_nomas[""u""].attrs
{'scale_factor': 0.002397265127278432, 'add_offset': 25.620963232670736, '_FillValue': -32767, 'units': 'm s**-1', 'long_name': 'U component of wind', 'standard_name': 'eastward_wind', 'missing_value': -32767}

```

Maybe the data from the second file is not adjusted to fit the new scaling and offset.


**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.6 | packaged by conda-forge | (default, Jun  1 2020, 18:57:50) 
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 4.15.0-107-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4

xarray: 0.16.0
pandas: 1.0.4
numpy: 1.18.5
scipy: 1.4.1
netCDF4: 1.5.3
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.2.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: 0.9.8.2
iris: None
bottleneck: None
dask: 2.18.1
distributed: 2.21.0
matplotlib: 3.2.1
cartopy: 0.18.0
seaborn: None
numbagg: None
pint: 0.14
setuptools: 49.2.0.post20200712
pip: 20.1.1
conda: 4.8.3
pytest: None
IPython: 7.16.1
sphinx: None



</details>
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