That figure is basically what I am getting. Perhaps I designed the MRE poorly, however, I am curious as to what exactly from the encoding introduces the noise (I still need to read through the documentation more thoroughly)? If I don't apply the original encoding, I get a straight line at 0 for the difference plot.

With that being said, if you are willing to try a test with the actual ERA5 data, I've attached it here via a box link. I went back and figured out I need at least several files to get large differences. Oddly enough, if I use only 2 files, the difference looks more like noise (+/- 0.0005). If I only open a single file, no difference. If I add a couple more files, the differences become quite large.

Data: https://epri.box.com/s/spw9plf77lrjj1xz2spmwd34b5ls9dea

```python import xarray as xr import matplotlib.pyplot as plt

Open original time series

ERA5_t2m = xr.open_mfdataset(r'...\Test\T2m_*' + '.nc') # open 4 files

Save time series as netcdf

ERA5_t2m.to_netcdf(r"...\Test\Phx_Temperature_to_netcdf.nc") # save 4 files

open bad netcdf

ERA5_t2m_bad = xr.open_dataset(r'...\Test\Phx_Temperature_to_netcdf.nc')

Lat and lon for Phx

lats = [33.35] lons = [-112.86]

plot the difference between the same point from the two files

plt.plot(ERA5_t2m.t2m.sel(latitude = lats[0], longitude = lons[0], method='nearest') - ERA5_t2m_bad.t2m.sel(latitude = lats[0], longitude = lons[0], method='nearest')) ```