Thank you @TomNicholas - strangely I can't reproduce it anymore on my local machine - it all happened on our slurm. The result is correct according to the input file index. In my case I calculated annual and seasonal climate variables on the same input files, but the matrix index i,j were different. One with upper left corner (0,0) and the other one with (0,1167) - as shown in ncview. Nevertheless here is what I did - you can test it with https://www.unidata.ucar.edu/software/netcdf/examples/sresa1b_ncar_ccsm3-example.nc:

```python

import numpy as np import xarray as xr

chunks=4

lonrange=256 latrange=128

creating the chunks - our slurm can't handle dask_jobqueue and dask chunking wasnt possible as well

x=[x.tolist() for x in np.array_split(range(lonrange), chunks)] xextend = [[sublist[0],sublist[-1]] for sublist in x]

y=[y.tolist() for y in np.array_split(range(latrange), chunks)] yextend = [[sublist[0],sublist[-1]] for sublist in y]

concatenating the chunks

allChunks = [[x,y] for x in xextend for y in yextend]

for k in range(0,chunks*chunks):

inter = str(k)

tas = xr.open_dataset('~/pathToFile/sresa1b_ncar_ccsm3-example.nc').isel(longitude=slice(min(allChunks[k][0]), max(allChunks[k][0])), latitude=slice(min(allChunks[k][1]), max(allChunks[k][1])))
    ##instead of my climate calculations
tas.rename({'tas':'test1'}).to_netcdf('~/pathToFile/climateCalculation1_'+inter+'.nc')
tas.rename({'tas':'test2'}).to_netcdf('~/pathToFile/climateCalculation2_'+inter+'.nc')

#combining the single data arrays per chunk
    ##combine using nested
with xr.open_mfdataset('~/pathToFile/climateCalculation*'+inter+'.nc', chunks=-1, parallel=True, engine='h5netcdf', combine='nested') as ds:
    ds.to_netcdf('~/pathToFile/nestedClimateAnnualCalculations_'+inter+'.nc')
    #combine using default coords
    with xr.open_mfdataset('~/pathToFile/climateCalculation*'+inter+'.nc', chunks=-1, parallel=True, engine='h5netcdf') as ds:
        ds.to_netcdf('~/pathToFile/climateAnnualCalculations_'+inter+'.nc')

combining all chunks to one final file

nested input

with xr.open_mfdataset('~/pathToFile/climateCalculations/nestedClimateAnnualCalculations_*', chunks=-1, parallel=True, engine='h5netcdf') as ds:
ds.to_netcdf('~/pathToFile/climateAnnualCalculationsCombinedNested.nc')

with xr.open_mfdataset('~/pathToFile/climateCalculations/climateAnnualCalculations_*', chunks=-1, parallel=True, engine='h5netcdf') as ds:
ds.to_netcdf('~/pathToFile/climateAnnualCalculationsCombined.nc')

```

Hi @areichmuth - I would love to help but I would need some more information from you first.

What is a "tilted grid index"? Do you mean that the files have not been combined in the order you expected them to be?

It's very hard to debug problems unless I can reproduce them locally. Do you have some example data files you could upload that this problem occurs with? Or even better some small code snippet that generates an example which shows the same issue?