diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 1dac72335d2..d55d737aa1c 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -1214,6 +1214,9 @@ def fillna(self, value):
         out = ops.fillna(self, value)
         return out
 
+    def ffill(self, dim, limit=None):
+        return ops.ffill(self, dim, limit)
+
     def combine_first(self, other):
         """Combine two DataArray objects, with union of coordinates.
 
diff --git a/xarray/core/ops.py b/xarray/core/ops.py
index 2ed3f81d185..a32eaf1b0e2 100644
--- a/xarray/core/ops.py
+++ b/xarray/core/ops.py
@@ -153,6 +153,22 @@ def fillna(data, other, join="left", dataset_join="left"):
                        dataset_fill_value=np.nan,
                        keep_attrs=True)
 
+def ffill(data, dim, limit=None):
+    axis_num = data.get_axis_num(dim)
+
+    if not has_bottleneck:
+        raise ImportError('ffill requires bottleneck to be installed')
+
+    data = data.copy()
+
+    if limit is None:
+        # bottleneck raises an error if you pass `None`
+        data.values = bn.push(data.values, axis=axis_num)
+    else:
+        data.values = bn.push(data.values, axis=axis_num, n=limit)
+
+    return data
+
 
 def where_method(self, cond, other=dtypes.NA):
     """Return elements from `self` or `other` depending on `cond`.
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index d39232c04c8..5c7c7cc7104 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -3146,3 +3146,21 @@ def test_raise_no_warning_for_nan_in_binary_ops():
     with pytest.warns(None) as record:
         xr.DataArray([1, 2, np.NaN]) > 0
     assert len(record) == 0
+
+
+@pytest.mark.parametrize('da', (1, 2), indirect=True)
+def test_ffill_functions(da):
+    result = da.ffill('time')
+    assert result.isnull().sum() == 0
+
+def test_ffill_limit(da):
+    da = DataArray(
+        [0, np.nan, np.nan, np.nan, np.nan, 3, 4, 5, np.nan, 6, 7],
+        dims='time')
+    result = da.ffill('time')
+    expected = DataArray([0, 0, 0, 0, 0, 3, 4, 5, 5, 6, 7], dims='time')
+    assert_array_equal(result, expected)
+
+    result = da.ffill('time', limit=1)
+    expected = DataArray(
+        [0, 0, np.nan, np.nan, np.nan, 3, 4, 5, 5, 6, 7], dims='time')