An alternative approach, if you know the total number of timesteps in advance, would be to initialize the whole Zarr store at the beginning with a lazy “template” dataset, i.e.
ds_template.to_zarr(tempdir, compute=False)
and then use the region argument to write, i.e. something like
for j in range(ntimesteps):
dd.to_zarr(tempdir, region={'time': slice(j, j+1)}
This might be faster because it won’t actually open the Zarr store with Xarray each time. That’s what I think is happening with append.