issue_comments: 852069023

Dear all and thank you for your work on Xarray,

Link to @magau comment, I have a netcdf with multiple variables in different format (float, short, byte). Using open_mfdataset 'short' and 'byte' are converted in 'float64' (no scaling, but some masking for the float data). It doesn't raise major issue for me, but it is taking plenty of memory space for nothing.

Below an example of the 3 format from (ncdump -h): short total_nobs(time, lat, lon) ; total_nobs:long_name = "Number of SSS in the time interval" ; total_nobs:valid_min = 0s ; total_nobs:valid_max = 10000s ; float pct_var(time, lat, lon) ; pct_var:_FillValue = NaNf ; pct_var:long_name = "Percentage of SSS_variability that is expected to be not explained by the products" ; pct_var:units = "%" ; pct_var:valid_min = 0. ; pct_var:valid_max = 100. ; byte sss_qc(time, lat, lon) ; sss_qc:long_name = "Sea Surface Salinity Quality, 0=Good; 1=Bad" ; sss_qc:valid_min = 0b ; sss_qc:valid_max = 1b ;

And how they appear after opening in as xarray using open_mfdataset: total_nobs (time, lat, lon) float64 dask.array<chunksize=(48, 584, 1388), meta=np.ndarray> pct_var (time, lat, lon) float32 dask.array<chunksize=(48, 584, 1388), meta=np.ndarray> sss_qc (time, lat, lon) float64 dask.array<chunksize=(48, 584, 1388), met

Is there any recommandation? Regards