diff --git a/doc/user-guide/indexing.rst b/doc/user-guide/indexing.rst
index 90b7cbaf2a9..4882403342f 100644
--- a/doc/user-guide/indexing.rst
+++ b/doc/user-guide/indexing.rst
@@ -747,7 +747,7 @@ Whether array indexing returns a view or a copy of the underlying
 data depends on the nature of the labels.
 
 For positional (integer)
-indexing, xarray follows the same rules as NumPy:
+indexing, xarray follows the same `rules`_ as NumPy:
 
 * Positional indexing with only integers and slices returns a view.
 * Positional indexing with arrays or lists returns a copy.
@@ -764,8 +764,10 @@ Whether data is a copy or a view is more predictable in xarray than in pandas, s
 unlike pandas, xarray does not produce `SettingWithCopy warnings`_. However, you
 should still avoid assignment with chained indexing.
 
-.. _SettingWithCopy warnings: https://pandas.pydata.org/pandas-docs/stable/indexing.html#returning-a-view-versus-a-copy
+Note that other operations (such as :py:meth:`~xarray.DataArray.values`) may also return views rather than copies.
 
+.. _SettingWithCopy warnings: https://pandas.pydata.org/pandas-docs/stable/indexing.html#returning-a-view-versus-a-copy
+.. _rules: https://numpy.org/doc/stable/user/basics.copies.html
 
 .. _multi-level indexing:
 
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 7a0bdbc4d4c..64f02fa3b44 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -761,11 +761,15 @@ def data(self, value: Any) -> None:
     @property
     def values(self) -> np.ndarray:
         """
-        The array's data as a numpy.ndarray.
+        The array's data converted to numpy.ndarray.
 
-        If the array's data is not a numpy.ndarray this will attempt to convert
-        it naively using np.array(), which will raise an error if the array
-        type does not support coercion like this (e.g. cupy).
+        This will attempt to convert the array naively using np.array(),
+        which will raise an error if the array type does not support
+        coercion like this (e.g. cupy).
+
+        Note that this array is not copied; operations on it follow
+        numpy's rules of what generates a view vs. a copy, and changes
+        to this array may be reflected in the DataArray as well.
         """
         return self.variable.values