Ensure SeasonResampler preserves datetime resolution

doc/whats-new.rst

@@ -49,6 +49,9 @@ Bug Fixes
   ``np.isclose`` by default to handle accumulated floating point errors from
   slicing operations. Use ``exact=True`` for exact comparison (:pull:`11035`).
   By `Ian Hunt-Isaak <https://github.com/ianhi>`_.
+- Ensure the :py:class:`~xarray.groupers.SeasonResampler` preserves the datetime
+  unit of the underlying time index when resampling (:issue:`11048`,
+  :pull:`11049`). By `Spencer Clark <https://github.com/spencerkclark>`_.
 
 Documentation
 ~~~~~~~~~~~~~

xarray/groupers.py

@@ -14,6 +14,7 @@
 from collections import defaultdict
 from collections.abc import Hashable, Mapping, Sequence
 from dataclasses import dataclass, field
+from functools import partial
 from itertools import chain, pairwise
 from typing import TYPE_CHECKING, Any, Literal, cast
 
@@ -40,6 +41,7 @@
     Bins,
     DatetimeLike,
     GroupIndices,
+    PDDatetimeUnitOptions,
     ResampleCompatible,
     Self,
     SideOptions,
@@ -61,6 +63,11 @@
 RESAMPLE_DIM = "__resample_dim__"
 
 
+def _construct_timestamp_as_unit(unit: PDDatetimeUnitOptions, **kwargs) -> pd.Timestamp:
+    """Construct a pandas.Timestamp object with a specific resolution."""
+    return pd.Timestamp(**kwargs).as_unit(unit)
+
+
 @dataclass(init=False)
 class EncodedGroups:
     """
@@ -960,7 +967,8 @@ def factorize(self, group: T_Group) -> EncodedGroups:
             datetime_class = type(first_n_items(group.data, 1).item())
         else:
             index_class = pd.DatetimeIndex
-            datetime_class = datetime.datetime
+            unit, _ = np.datetime_data(group.dtype)
+            datetime_class = partial(_construct_timestamp_as_unit, unit)
 
         # these are the seasons that are present
         unique_coord = index_class(

xarray/tests/test_groupby.py

@@ -14,7 +14,7 @@
 import xarray as xr
 from xarray import DataArray, Dataset, Variable, date_range
 from xarray.core.groupby import _consolidate_slices
-from xarray.core.types import InterpOptions, ResampleCompatible
+from xarray.core.types import InterpOptions, PDDatetimeUnitOptions, ResampleCompatible
 from xarray.groupers import (
     BinGrouper,
     EncodedGroups,
@@ -3605,6 +3605,15 @@
         gb = da.groupby(time=resampler).sum()
         assert_identical(rs, gb)
 
+    def test_season_resampler_preserves_time_unit(
+        self, time_unit: PDDatetimeUnitOptions
+    ):
+        time = date_range("2000", periods=12, freq="MS", unit=time_unit)
+        da = DataArray(np.ones(time.size), dims="time", coords={"time": time})
+        resampler = SeasonResampler(["DJF", "MAM", "JJA", "SON"])
+        rs = da.resample(time=resampler).sum()
+        assert rs.time.dtype == time.dtype
+
 
 @pytest.mark.parametrize(
     "chunk",