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
986436135,MDU6SXNzdWU5ODY0MzYxMzU=,5760,Matrix Index is tilted using combine_by_coords ,25606497,open,0,,,2,2021-09-02T09:22:28Z,2021-09-02T21:49:57Z,,NONE,,,,"My calculations return a strange tilted index. Why does this happen? 


**What happened**:
I combined several user defined chunked netcdf data (900 chunks) into one dataset. For this I used the default combine_by_coords in ds.open_mf_dataset(). My result was a tilted grid index - upper left corner i=0, j=1167. 

Beforehand I calculated some indices on these chunks and combined them with the default combine='by_coords' in ds.open_mf_dataset() but also tested the combine='nested' separately. 

The ones where I used default combine='by_coords' for all functions returned the tilted index.
The ones where I used combine='nested' beforehand and then default combine='by_coords' returned the correct index. 


**What you expected to happen**:
No tilted index. 

**Minimal Complete Verifiable Example**:

```python

##returning wrong index
#calculating some climatic indices on numbered chunks and combined them to one ds per chunk
with xr.open_mfdataset(pathtofile+'annual*'+chunknumber+'.nc', chunks=-1, parallel=True, engine='h5netcdf') as ds:
    ds.to_netcdf(pathtofile, format=""NETCDF4_CLASSIC"", engine=""netcdf4"")

##combining all
with xr.open_mfdataset(pathtofile+'climateAnnual*.nc', chunks=-1, parallel=True, engine='h5netcd') as ds: 
    ds.to_netcdf(pathtofile, format=""NETCDF4_CLASSIC"", engine=""netcdf4"")

##################################################

##returning correct index
#calculating some climatic indices on numbered chunks and combined them to one ds per chunk
with xr.open_mfdataset(pathtofile+'annual*'+chunknumber+'.nc', chunks=-1, parallel=True, engine='h5netcdf', combine='nested') as ds:
    ds.to_netcdf(pathtofile, format=""NETCDF4_CLASSIC"", engine=""netcdf4"")

##combining all
with xr.open_mfdataset(pathtofile+'climateAnnual*.nc', chunks=-1, parallel=True, engine='h5netcd') as ds: 
    ds.to_netcdf(pathtofile, format=""NETCDF4_CLASSIC"", engine=""netcdf4"")



```

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

**Environment**:
Python 3.7.4

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

<!-- Paste the output here xr.show_versions() here -->
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.4 (default, Jun  3 2020, 14:52:58) 
[GCC 8.3.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-1160.15.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: de_DE.UTF-8
LOCALE: ('de_DE', 'UTF-8')
libhdf5: 1.12.0
libnetcdf: 4.7.4

xarray: 0.18.2
pandas: 0.25.3
numpy: 1.17.3
scipy: 1.3.1
netCDF4: 1.5.7
pydap: installed
h5netcdf: 0.11.0
h5py: 3.3.0
Nio: None
zarr: 2.8.3
cftime: 1.5.0
nc_time_axis: 1.3.1
PseudoNetCDF: None
rasterio: 1.2.6
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2021.06.2
distributed: 2021.06.2
matplotlib: 3.4.2
cartopy: None
seaborn: 0.11.1
numbagg: 0.2.1
pint: 0.17
setuptools: 57.0.0
pip: 21.1.3
conda: None
pytest: None
IPython: None
sphinx: None


</details>
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