issue_comments: 1060493852

This will fail like append. just tried to make some kind of realistic example like reprojecting from a geographic to an orthogonal system. If you look at all the stages you need to go through... and still not sure this is working as it should

``` python import xarray as xr from rasterio.enums import Resampling import numpy as np

def init_coord(ds): ''' To have the geometry right''' arr_r=some_processing(ds.isel(time=slice(0,1)) return arr_r.x.values, arr_r.y.values

def some_processing(arr): ''' A reprojection routine''' arr = arr.rio.write_crs('EPSG:4326') arr_r = arr.rio.reproject('EPSG:3857', shape=(250, 250), resampling=Resampling.bilinear, nodata=np.nan) return arr_r

filename='processed_dataset.zarr' ds = xr.tutorial.open_dataset('air_temperature') x,y=init_coord(ds) ds_to_write=xr.Dataset({'coords':{'time':('time',ds.time.values),'x':('x', x),'y':('y',y)}}) ds_to_write.to_zarr(filename, compute =false, encoding={"time": {"chunks": [1]}}) for i in range(len(ds.time)): # some kind of heavy processing arr_r=some_processing(ds.isel(time=slice(i,i+1)) agg_r_t= agg_r.drop(['spatial_ref']).expand_dims({'time':[ds.time.values[i]]}) buff= xr.Dataset(({'air':agg_r_t}).chunk({'time':1,'x':250,'y':250}) buff.drop(['x','y']).to_zarr(filename, , region={'time':slice(i,i+1)}) ``` You would need to change the processing function to something like:

python def some_processing(arr): ''' A reprojection routine''' arr = arr.rio.write_crs('EPSG:4326') arr_r = arr.rio.reproject('EPSG:3857', shape=(250, 250), resampling=Resampling.bilinear, nodata=np.nan) del arr_r.attrs["_FillValue"] return arr_r Sorry maybe I am repetitive but I want to be sure that it is clearly illustrated. I have done another test on the cloud, checking the values at the moment.