diff --git a/xarray/backends/zarr.py b/xarray/backends/zarr.py
index 410a6a49a7b..8fcc968ca67 100644
--- a/xarray/backends/zarr.py
+++ b/xarray/backends/zarr.py
@@ -487,7 +487,7 @@ def extract_zarr_variable_encoding(
 # The only change is to raise an error for object dtypes.
 def encode_zarr_variable(var, needs_copy=True, name=None):
     """
-    Converts an Variable into an Variable which follows some
+    Converts a Variable into another Variable which follows some
     of the CF conventions:
 
         - Nans are masked using _FillValue (or the deprecated missing_value)
diff --git a/xarray/compat/npcompat.py b/xarray/compat/npcompat.py
index 05cb4dcc110..cdd59093f65 100644
--- a/xarray/compat/npcompat.py
+++ b/xarray/compat/npcompat.py
@@ -64,7 +64,7 @@ def isdtype(  # type: ignore[misc]
             )
         if unknown_kinds := {k for k in str_kinds if k not in kind_mapping}:
             raise ValueError(
-                f"unknown kind: {unknown_kinds}, must be a np.dtype or one of {list(kind_mapping)}"
+                f"unknown kind: {unknown_kinds}, must be an np.dtype or one of {list(kind_mapping)}"
             )
 
         # verified the dtypes already, no need to check again
diff --git a/xarray/core/indexing.py b/xarray/core/indexing.py
index 6e8ab00f09d..f5e3183fd8c 100644
--- a/xarray/core/indexing.py
+++ b/xarray/core/indexing.py
@@ -1023,7 +1023,7 @@ def as_indexable(array):
 def _outer_to_vectorized_indexer(
     indexer: BasicIndexer | OuterIndexer, shape: _Shape
 ) -> VectorizedIndexer:
-    """Convert an OuterIndexer into an vectorized indexer.
+    """Convert an OuterIndexer into a vectorized indexer.
 
     Parameters
     ----------
diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index 7848d64f338..95408614b31 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -353,7 +353,7 @@ class Variable(NamedArray, AbstractArray, VariableArithmetic):
 
     The main functional difference between Variables and numpy arrays is that
     numerical operations on Variables implement array broadcasting by dimension
-    name. For example, adding an Variable with dimensions `('time',)` to
+    name. For example, adding a Variable with dimensions `('time',)` to
     another Variable with dimensions `('space',)` results in a new Variable
     with dimensions `('time', 'space')`. Furthermore, numpy reduce operations
     like ``mean`` or ``sum`` are overwritten to take a "dimension" argument
diff --git a/xarray/util/generate_ops.py b/xarray/util/generate_ops.py
index 74fec786afa..a1f9268f769 100644
--- a/xarray/util/generate_ops.py
+++ b/xarray/util/generate_ops.py
@@ -72,7 +72,7 @@
     ("__invert__", "operator.invert"),
 )
 # round method and numpy/pandas unary methods which don't modify the data shape,
-# so the result should still be wrapped in an Variable/DataArray/Dataset
+# so the result should still be wrapped in a Variable/DataArray/Dataset
 OTHER_UNARY_METHODS = (
     ("round", "ops.round_"),
     ("argsort", "ops.argsort"),