to_zarr with append can break existing dataset

What happened?

When appending an incomplete dataset to an existing zarr store, the existing zarr store can end up in a broken state, because not all dimension sizes of existing variables are updated consistently.

What did you expect to happen?

I would have expected that xarray doesn't break my existing dataset, i.e. either:

• xarray should raise an exception when trying to append (such that the existing dataset doesn't break) or
• appending ds2 should appropriately fill the missing array cells of the b variable with missing values

Minimal Complete Verifiable Example

# /// script
# requires-python = ">=3.13"
# dependencies = [
#     "xarray",
#     "zarr",
# ]
# ///

import xarray as xr
xr.show_versions()

m = {}
ds1 = xr.Dataset({"a": (("x",), [1, 2]), "b": (("x",), [10, 20])})
ds2 = xr.Dataset({"a": (("x",), [3, 4])})
ds1.to_zarr(m)
ds2.to_zarr(m, append_dim="x")
xr.open_dataset(m, engine="zarr")

Steps to reproduce

uv run issue.py

MVCE confirmation

• Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• Complete example — the example is self-contained, including all data and the text of any traceback.
• Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• New issue — a search of GitHub Issues suggests this is not a duplicate.
• Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

ValueError: conflicting sizes for dimension 'x': length 2 on 'b' and length 4 on {'x': 'a'}

Anything else we need to know?

No response

Environment

Start by reproducing the issue with the provided MVCE, then trace the to_zarr entry point and its append_dim handling for incomplete datasets. Done means appending ds2 either raises before modifying the existing store or keeps every variable dimension consistent by filling missing cells appropriately.