diff --git a/ci/requirements/py36-min-nep18.yml b/ci/requirements/py36-min-nep18.yml
index c10fdf67dc4..a5eded49cd4 100644
--- a/ci/requirements/py36-min-nep18.yml
+++ b/ci/requirements/py36-min-nep18.yml
@@ -11,7 +11,7 @@ dependencies:
   - msgpack-python=0.6  # remove once distributed is bumped. distributed GH3491
   - numpy=1.17
   - pandas=0.25
-  - pint=0.9  # Actually not enough as it doesn't implement __array_function__yet!
+  - pint=0.11
   - pip
   - pytest
   - pytest-cov
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 32c86563a57..200463a7b22 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -28,7 +28,7 @@ New Features
 - Support new h5netcdf backend keyword `phony_dims` (available from h5netcdf
   v0.8.0 for :py:class:`~xarray.backends.H5NetCDFStore`.
   By `Kai Mühlbauer <https://github.com/kmuehlbauer>`_.
-- implement pint support. (:issue:`3594`, :pull:`3706`)
+- Support unit aware arrays with pint. (:issue:`3594`, :pull:`3706`, :pull:`3611`)
   By `Justus Magin <https://github.com/keewis>`_.
 
 
diff --git a/xarray/tests/test_units.py b/xarray/tests/test_units.py
index 75e743c3455..5577ad7911f 100644
--- a/xarray/tests/test_units.py
+++ b/xarray/tests/test_units.py
@@ -1,3 +1,4 @@
+import functools
 import operator
 from distutils.version import LooseVersion
 
@@ -8,6 +9,7 @@
 import xarray as xr
 from xarray.core import formatting
 from xarray.core.npcompat import IS_NEP18_ACTIVE
+from xarray.testing import assert_allclose, assert_identical
 
 from .test_variable import VariableSubclassobjects
 
@@ -70,53 +72,17 @@ def array_strip_units(array):
         return array
 
 
-def array_attach_units(data, unit, convert_from=None):
-    try:
-        unit, convert_from = unit
-    except TypeError:
-        pass
-
+def array_attach_units(data, unit):
     if isinstance(data, Quantity):
-        if not convert_from:
-            raise ValueError(
-                "cannot attach unit {unit} to quantity ({data.units})".format(
-                    unit=unit, data=data
-                )
-            )
-        elif isinstance(convert_from, unit_registry.Unit):
-            data = data.magnitude
-        elif convert_from is True:  # intentionally accept exactly true
-            if data.check(unit):
-                convert_from = data.units
-                data = data.magnitude
-            else:
-                raise ValueError(
-                    "cannot convert quantity ({data.units}) to {unit}".format(
-                        unit=unit, data=data
-                    )
-                )
-        else:
-            raise ValueError(
-                "cannot convert from invalid unit {convert_from}".format(
-                    convert_from=convert_from
-                )
-            )
+        raise ValueError(f"cannot attach unit {unit} to quantity {data}")
 
-    # to make sure we also encounter the case of "equal if converted"
-    if convert_from is not None:
-        quantity = (data * convert_from).to(
-            unit
-            if isinstance(unit, unit_registry.Unit)
-            else unit_registry.dimensionless
-        )
-    else:
-        try:
-            quantity = data * unit
-        except np.core._exceptions.UFuncTypeError:
-            if unit != 1:
-                raise
+    try:
+        quantity = data * unit
+    except np.core._exceptions.UFuncTypeError:
+        if isinstance(unit, unit_registry.Unit):
+            raise
 
-            quantity = data
+        quantity = data
 
     return quantity
 
@@ -241,6 +207,11 @@ def attach_units(obj, units):
 
 
 def convert_units(obj, to):
+    # preprocess
+    to = {
+        key: None if not isinstance(value, unit_registry.Unit) else value
+        for key, value in to.items()
+    }
     if isinstance(obj, xr.Dataset):
         data_vars = {
             name: convert_units(array.variable, {None: to.get(name)})
@@ -282,6 +253,7 @@ def convert_units(obj, to):
 
 
 def assert_units_equal(a, b):
+    __tracebackhide__ = True
     assert extract_units(a) == extract_units(b)
 
 
@@ -414,9 +386,8 @@ def __repr__(self):
         return f"function_{self.name}"
 
 
-@pytest.mark.xfail(reason="test bug: apply_ufunc should not be called that way")
 def test_apply_ufunc_dataarray(dtype):
-    func = function(
+    func = functools.partial(
         xr.apply_ufunc, np.mean, input_core_dims=[["x"]], kwargs={"axis": -1}
     )
 
@@ -427,12 +398,12 @@ def test_apply_ufunc_dataarray(dtype):
     expected = attach_units(func(strip_units(data_array)), extract_units(data_array))
     actual = func(data_array)
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
-@pytest.mark.xfail(reason="test bug: apply_ufunc should not be called that way")
 def test_apply_ufunc_dataset(dtype):
-    func = function(
+    func = functools.partial(
         xr.apply_ufunc, np.mean, input_core_dims=[["x"]], kwargs={"axis": -1}
     )
 
@@ -450,10 +421,10 @@ def test_apply_ufunc_dataset(dtype):
     expected = attach_units(func(strip_units(ds)), extract_units(ds))
     actual = func(ds)
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
-@pytest.mark.xfail(reason="blocked by `reindex` / `where`")
 @pytest.mark.parametrize(
     "unit,error",
     (
@@ -475,36 +446,40 @@ def test_apply_ufunc_dataset(dtype):
         "coords",
     ),
 )
-@pytest.mark.parametrize("fill_value", (np.float64(10), np.float64(np.nan)))
+@pytest.mark.parametrize("fill_value", (10, np.nan))
 def test_align_dataarray(fill_value, variant, unit, error, dtype):
     original_unit = unit_registry.m
 
     variants = {
-        "data": (unit, 1, 1),
-        "dims": (original_unit, unit, 1),
-        "coords": (original_unit, 1, unit),
+        "data": (unit, original_unit, original_unit),
+        "dims": (original_unit, unit, original_unit),
+        "coords": (original_unit, original_unit, unit),
     }
     data_unit, dim_unit, coord_unit = variants.get(variant)
 
     array1 = np.linspace(0, 10, 2 * 5).reshape(2, 5).astype(dtype) * original_unit
     array2 = np.linspace(0, 8, 2 * 5).reshape(2, 5).astype(dtype) * data_unit
     x = np.arange(2) * original_unit
-    x_a1 = np.array([10, 5]) * original_unit
-    x_a2 = np.array([10, 5]) * coord_unit
 
     y1 = np.arange(5) * original_unit
     y2 = np.arange(2, 7) * dim_unit
+    y_a1 = np.array([3, 5, 7, 8, 9]) * original_unit
+    y_a2 = np.array([7, 8, 9, 11, 13]) * coord_unit
 
-    data_array1 = xr.DataArray(
-        data=array1, coords={"x": x, "x_a": ("x", x_a1), "y": y1}, dims=("x", "y")
-    )
-    data_array2 = xr.DataArray(
-        data=array2, coords={"x": x, "x_a": ("x", x_a2), "y": y2}, dims=("x", "y")
-    )
+    coords1 = {"x": x, "y": y1}
+    coords2 = {"x": x, "y": y2}
+    if variant == "coords":
+        coords1["y_a"] = ("y", y_a1)
+        coords2["y_a"] = ("y", y_a2)
+
+    data_array1 = xr.DataArray(data=array1, coords=coords1, dims=("x", "y"))
+    data_array2 = xr.DataArray(data=array2, coords=coords2, dims=("x", "y"))
 
     fill_value = fill_value * data_unit
     func = function(xr.align, join="outer", fill_value=fill_value)
-    if error is not None:
+    if error is not None and not (
+        np.isnan(fill_value) and not isinstance(fill_value, Quantity)
+    ):
         with pytest.raises(error):
             func(data_array1, data_array2)
 
@@ -524,15 +499,19 @@ def test_align_dataarray(fill_value, variant, unit, error, dtype):
         **stripped_kwargs,
     )
     expected_a = attach_units(expected_a, units_a)
-    expected_b = convert_units(attach_units(expected_b, units_a), units_b)
+    if isinstance(array2, Quantity):
+        expected_b = convert_units(attach_units(expected_b, units_a), units_b)
+    else:
+        expected_b = attach_units(expected_b, units_b)
 
     actual_a, actual_b = func(data_array1, data_array2)
 
-    assert_equal_with_units(expected_a, actual_a)
-    assert_equal_with_units(expected_b, actual_b)
+    assert_units_equal(expected_a, actual_a)
+    assert_allclose(expected_a, actual_a)
+    assert_units_equal(expected_b, actual_b)
+    assert_allclose(expected_b, actual_b)
 
 
-@pytest.mark.xfail(reason="blocked by `reindex` / `where`")
 @pytest.mark.parametrize(
     "unit,error",
     (
@@ -558,31 +537,37 @@ def test_align_dataarray(fill_value, variant, unit, error, dtype):
 def test_align_dataset(fill_value, unit, variant, error, dtype):
     original_unit = unit_registry.m
 
-    variants = {"data": (unit, 1, 1), "dims": (1, unit, 1), "coords": (1, 1, unit)}
+    variants = {
+        "data": (unit, original_unit, original_unit),
+        "dims": (original_unit, unit, original_unit),
+        "coords": (original_unit, original_unit, unit),
+    }
     data_unit, dim_unit, coord_unit = variants.get(variant)
 
     array1 = np.linspace(0, 10, 2 * 5).reshape(2, 5).astype(dtype) * original_unit
     array2 = np.linspace(0, 10, 2 * 5).reshape(2, 5).astype(dtype) * data_unit
 
     x = np.arange(2) * original_unit
-    x_a1 = np.array([10, 5]) * original_unit
-    x_a2 = np.array([10, 5]) * coord_unit
 
     y1 = np.arange(5) * original_unit
     y2 = np.arange(2, 7) * dim_unit
+    y_a1 = np.array([3, 5, 7, 8, 9]) * original_unit
+    y_a2 = np.array([7, 8, 9, 11, 13]) * coord_unit
 
-    ds1 = xr.Dataset(
-        data_vars={"a": (("x", "y"), array1)},
-        coords={"x": x, "x_a": ("x", x_a1), "y": y1},
-    )
-    ds2 = xr.Dataset(
-        data_vars={"a": (("x", "y"), array2)},
-        coords={"x": x, "x_a": ("x", x_a2), "y": y2},
-    )
+    coords1 = {"x": x, "y": y1}
+    coords2 = {"x": x, "y": y2}
+    if variant == "coords":
+        coords1["y_a"] = ("y", y_a1)
+        coords2["y_a"] = ("y", y_a2)
+
+    ds1 = xr.Dataset(data_vars={"a": (("x", "y"), array1)}, coords=coords1)
+    ds2 = xr.Dataset(data_vars={"a": (("x", "y"), array2)}, coords=coords2)
 
     fill_value = fill_value * data_unit
     func = function(xr.align, join="outer", fill_value=fill_value)
-    if error is not None:
+    if error is not None and not (
+        np.isnan(fill_value) and not isinstance(fill_value, Quantity)
+    ):
         with pytest.raises(error):
             func(ds1, ds2)
 
@@ -600,12 +585,17 @@ def test_align_dataset(fill_value, unit, variant, error, dtype):
         strip_units(ds1), strip_units(convert_units(ds2, units_a)), **stripped_kwargs
     )
     expected_a = attach_units(expected_a, units_a)
-    expected_b = convert_units(attach_units(expected_b, units_a), units_b)
+    if isinstance(array2, Quantity):
+        expected_b = convert_units(attach_units(expected_b, units_a), units_b)
+    else:
+        expected_b = attach_units(expected_b, units_b)
 
     actual_a, actual_b = func(ds1, ds2)
 
-    assert_equal_with_units(expected_a, actual_a)
-    assert_equal_with_units(expected_b, actual_b)
+    assert_units_equal(expected_a, actual_a)
+    assert_allclose(expected_a, actual_a)
+    assert_units_equal(expected_b, actual_b)
+    assert_allclose(expected_b, actual_b)
 
 
 def test_broadcast_dataarray(dtype):
@@ -615,28 +605,53 @@ def test_broadcast_dataarray(dtype):
     a = xr.DataArray(data=array1, dims="x")
     b = xr.DataArray(data=array2, dims="y")
 
-    expected_a, expected_b = tuple(
-        attach_units(elem, extract_units(a))
-        for elem in xr.broadcast(strip_units(a), strip_units(b))
-    )
+    units_a = extract_units(a)
+    units_b = extract_units(b)
+    expected_a, expected_b = xr.broadcast(strip_units(a), strip_units(b))
+    expected_a = attach_units(expected_a, units_a)
+    expected_b = convert_units(attach_units(expected_b, units_a), units_b)
+
     actual_a, actual_b = xr.broadcast(a, b)
 
-    assert_equal_with_units(expected_a, actual_a)
-    assert_equal_with_units(expected_b, actual_b)
+    assert_units_equal(expected_a, actual_a)
+    assert_identical(expected_a, actual_a)
+    assert_units_equal(expected_b, actual_b)
+    assert_identical(expected_b, actual_b)
 
 
 def test_broadcast_dataset(dtype):
     array1 = np.linspace(0, 10, 2) * unit_registry.Pa
     array2 = np.linspace(0, 10, 3) * unit_registry.Pa
 
-    ds = xr.Dataset(data_vars={"a": ("x", array1), "b": ("y", array2)})
+    x1 = np.arange(2)
+    y1 = np.arange(3)
+
+    x2 = np.arange(2, 4)
+    y2 = np.arange(3, 6)
 
-    (expected,) = tuple(
-        attach_units(elem, extract_units(ds)) for elem in xr.broadcast(strip_units(ds))
+    ds = xr.Dataset(
+        data_vars={"a": ("x", array1), "b": ("y", array2)}, coords={"x": x1, "y": y1}
+    )
+    other = xr.Dataset(
+        data_vars={
+            "a": ("x", array1.to(unit_registry.hPa)),
+            "b": ("y", array2.to(unit_registry.hPa)),
+        },
+        coords={"x": x2, "y": y2},
     )
-    (actual,) = xr.broadcast(ds)
 
-    assert_equal_with_units(expected, actual)
+    units_a = extract_units(ds)
+    units_b = extract_units(other)
+    expected_a, expected_b = xr.broadcast(strip_units(ds), strip_units(other))
+    expected_a = attach_units(expected_a, units_a)
+    expected_b = attach_units(expected_b, units_b)
+
+    actual_a, actual_b = xr.broadcast(ds, other)
+
+    assert_units_equal(expected_a, actual_a)
+    assert_identical(expected_a, actual_a)
+    assert_units_equal(expected_b, actual_b)
+    assert_identical(expected_b, actual_b)
 
 
 @pytest.mark.parametrize(
@@ -706,7 +721,8 @@ def test_combine_by_coords(variant, unit, error, dtype):
     )
     actual = xr.combine_by_coords([ds, other])
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 @pytest.mark.parametrize(
@@ -717,12 +733,7 @@ def test_combine_by_coords(variant, unit, error, dtype):
             unit_registry.dimensionless, DimensionalityError, id="dimensionless"
         ),
         pytest.param(unit_registry.s, DimensionalityError, id="incompatible_unit"),
-        pytest.param(
-            unit_registry.mm,
-            None,
-            id="compatible_unit",
-            marks=pytest.mark.xfail(reason="wrong order of arguments to `where`"),
-        ),
+        pytest.param(unit_registry.mm, None, id="compatible_unit"),
         pytest.param(unit_registry.m, None, id="identical_unit"),
     ),
     ids=repr,
@@ -810,7 +821,8 @@ def test_combine_nested(variant, unit, error, dtype):
     )
     actual = func([[ds1, ds2], [ds3, ds4]])
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 @pytest.mark.parametrize(
@@ -862,7 +874,8 @@ def test_concat_dataarray(variant, unit, error, dtype):
     )
     actual = xr.concat([arr1, arr2], dim="x")
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 @pytest.mark.parametrize(
@@ -912,10 +925,10 @@ def test_concat_dataset(variant, unit, error, dtype):
     )
     actual = xr.concat([ds1, ds2], dim="x")
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
-@pytest.mark.xfail(reason="blocked by `reindex` / `where`")
 @pytest.mark.parametrize(
     "unit,error",
     (
@@ -948,64 +961,81 @@ def test_merge_dataarray(variant, unit, error, dtype):
     data_unit, dim_unit, coord_unit = variants.get(variant)
 
     array1 = np.linspace(0, 1, 2 * 3).reshape(2, 3).astype(dtype) * original_unit
+    x1 = np.arange(2) * original_unit
+    y1 = np.arange(3) * original_unit
+    u1 = np.linspace(10, 20, 2) * original_unit
+    v1 = np.linspace(10, 20, 3) * original_unit
+
     array2 = np.linspace(1, 2, 2 * 4).reshape(2, 4).astype(dtype) * data_unit
-    array3 = np.linspace(0, 2, 3 * 4).reshape(3, 4).astype(dtype) * data_unit
+    x2 = np.arange(2, 4) * dim_unit
+    z2 = np.arange(4) * original_unit
+    u2 = np.linspace(20, 30, 2) * coord_unit
+    w2 = np.linspace(10, 20, 4) * original_unit
 
-    x = np.arange(2) * original_unit
-    y = np.arange(3) * original_unit
-    z = np.arange(4) * original_unit
-    u = np.linspace(10, 20, 2) * original_unit
-    v = np.linspace(10, 20, 3) * original_unit
-    w = np.linspace(10, 20, 4) * original_unit
+    array3 = np.linspace(0, 2, 3 * 4).reshape(3, 4).astype(dtype) * data_unit
+    y3 = np.arange(3, 6) * dim_unit
+    z3 = np.arange(4, 8) * dim_unit
+    v3 = np.linspace(10, 20, 3) * coord_unit
+    w3 = np.linspace(10, 20, 4) * coord_unit
 
     arr1 = xr.DataArray(
         name="a",
         data=array1,
-        coords={"x": x, "y": y, "u": ("x", u), "v": ("y", v)},
+        coords={"x": x1, "y": y1, "u": ("x", u1), "v": ("y", v1)},
         dims=("x", "y"),
     )
     arr2 = xr.DataArray(
-        name="b",
+        name="a",
         data=array2,
-        coords={
-            "x": np.arange(2, 4) * dim_unit,
-            "z": z,
-            "u": ("x", np.linspace(20, 30, 2) * coord_unit),
-            "w": ("z", w),
-        },
+        coords={"x": x2, "z": z2, "u": ("x", u2), "w": ("z", w2)},
         dims=("x", "z"),
     )
     arr3 = xr.DataArray(
-        name="c",
+        name="a",
         data=array3,
-        coords={
-            "y": np.arange(3, 6) * dim_unit,
-            "z": np.arange(4, 8) * dim_unit,
-            "v": ("y", np.linspace(10, 20, 3) * coord_unit),
-            "w": ("z", np.linspace(10, 20, 4) * coord_unit),
-        },
+        coords={"y": y3, "z": z3, "v": ("y", v3), "w": ("z", w3)},
         dims=("y", "z"),
     )
 
-    func = function(xr.merge)
     if error is not None:
         with pytest.raises(error):
-            func([arr1, arr2, arr3])
+            xr.merge([arr1, arr2, arr3])
 
         return
 
-    units = {name: original_unit for name in list("abcuvwxyz")}
+    units = {name: original_unit for name in list("axyzuvw")}
+
     convert_and_strip = lambda arr: strip_units(convert_units(arr, units))
-    expected = attach_units(
-        func([strip_units(arr1), convert_and_strip(arr2), convert_and_strip(arr3)]),
-        units,
+    expected_units = {
+        "a": original_unit,
+        "u": original_unit,
+        "v": original_unit,
+        "w": original_unit,
+        "x": original_unit,
+        "y": original_unit,
+        "z": original_unit,
+    }
+
+    expected = convert_units(
+        attach_units(
+            xr.merge(
+                [
+                    convert_and_strip(arr1),
+                    convert_and_strip(arr2),
+                    convert_and_strip(arr3),
+                ]
+            ),
+            units,
+        ),
+        expected_units,
     )
-    actual = func([arr1, arr2, arr3])
 
-    assert_equal_with_units(expected, actual)
+    actual = xr.merge([arr1, arr2, arr3])
+
+    assert_units_equal(expected, actual)
+    assert_allclose(expected, actual)
 
 
-@pytest.mark.xfail(reason="blocked by `reindex` / `where`")
 @pytest.mark.parametrize(
     "unit,error",
     (
@@ -1046,7 +1076,7 @@ def test_merge_dataset(variant, unit, error, dtype):
 
     ds1 = xr.Dataset(
         data_vars={"a": (("y", "x"), array1), "b": (("y", "x"), array2)},
-        coords={"x": x, "y": y, "z": ("x", z)},
+        coords={"x": x, "y": y, "u": ("x", z)},
     )
     ds2 = xr.Dataset(
         data_vars={
@@ -1056,18 +1086,18 @@ def test_merge_dataset(variant, unit, error, dtype):
         coords={
             "x": np.arange(3) * dim_unit,
             "y": np.arange(2, 4) * dim_unit,
-            "z": ("x", np.arange(-3, 0) * coord_unit),
+            "u": ("x", np.arange(-3, 0) * coord_unit),
         },
     )
     ds3 = xr.Dataset(
         data_vars={
-            "a": (("y", "x"), np.zeros_like(array1) * np.nan * data_unit),
-            "b": (("y", "x"), np.zeros_like(array2) * np.nan * data_unit),
+            "a": (("y", "x"), np.full_like(array1, np.nan) * data_unit),
+            "b": (("y", "x"), np.full_like(array2, np.nan) * data_unit),
         },
         coords={
             "x": np.arange(3, 6) * dim_unit,
             "y": np.arange(4, 6) * dim_unit,
-            "z": ("x", np.arange(3, 6) * coord_unit),
+            "u": ("x", np.arange(3, 6) * coord_unit),
         },
     )
 
@@ -1080,12 +1110,20 @@ def test_merge_dataset(variant, unit, error, dtype):
 
     units = extract_units(ds1)
     convert_and_strip = lambda ds: strip_units(convert_units(ds, units))
-    expected = attach_units(
-        func([strip_units(ds1), convert_and_strip(ds2), convert_and_strip(ds3)]), units
+    expected_units = {name: original_unit for name in list("abxyzu")}
+    expected = convert_units(
+        attach_units(
+            func(
+                [convert_and_strip(ds1), convert_and_strip(ds2), convert_and_strip(ds3)]
+            ),
+            units,
+        ),
+        expected_units,
     )
     actual = func([ds1, ds2, ds3])
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_allclose(expected, actual)
 
 
 @pytest.mark.parametrize("func", (xr.zeros_like, xr.ones_like))
@@ -1094,10 +1132,12 @@ def test_replication_dataarray(func, dtype):
     data_array = xr.DataArray(data=array, dims="x")
 
     numpy_func = getattr(np, func.__name__)
-    expected = xr.DataArray(data=numpy_func(array), dims="x")
+    units = extract_units(numpy_func(data_array))
+    expected = attach_units(func(data_array), units)
     actual = func(data_array)
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 @pytest.mark.parametrize("func", (xr.zeros_like, xr.ones_like))
@@ -1114,12 +1154,13 @@ def test_replication_dataset(func, dtype):
     )
 
     numpy_func = getattr(np, func.__name__)
-    expected = ds.copy(
-        data={name: numpy_func(array.data) for name, array in ds.data_vars.items()}
-    )
+    units = extract_units(ds.map(numpy_func))
+    expected = attach_units(func(strip_units(ds)), units)
+
     actual = func(ds)
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 @pytest.mark.xfail(
@@ -1158,7 +1199,8 @@ def test_replication_full_like_dataarray(unit, error, dtype):
     )
     actual = xr.full_like(data_array, fill_value=fill_value)
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 @pytest.mark.xfail(
@@ -1208,7 +1250,8 @@ def test_replication_full_like_dataset(unit, error, dtype):
     )
     actual = xr.full_like(ds, fill_value=fill_value)
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 @pytest.mark.parametrize(
@@ -1250,7 +1293,8 @@ def test_where_dataarray(fill_value, unit, error, dtype):
     )
     actual = xr.where(cond, x, fill_value)
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 @pytest.mark.parametrize(
@@ -1294,7 +1338,8 @@ def test_where_dataset(fill_value, unit, error, dtype):
     )
     actual = xr.where(cond, ds, fill_value)
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 def test_dot_dataarray(dtype):
@@ -1315,7 +1360,8 @@ def test_dot_dataarray(dtype):
     )
     actual = xr.dot(data_array, other)
 
-    assert_equal_with_units(expected, actual)
+    assert_units_equal(expected, actual)
+    assert_identical(expected, actual)
 
 
 def delete_attrs(*to_delete):