diff --git a/pyresample/_spatial_mp.py b/pyresample/_spatial_mp.py
index 08a351aec..7cb45b4d1 100644
--- a/pyresample/_spatial_mp.py
+++ b/pyresample/_spatial_mp.py
@@ -188,7 +188,7 @@ def _run_jobs(target, args, nprocs):
         p.join()
     if ierr.value != 0:
         raise RuntimeError('%d errors in worker processes. Last one reported:\n%s' %
-                           (ierr.value, warn_msg.value.decode()))
+                           (ierr.value, warn_msg.value._object_hook()))
 
 # This is executed in an external process:
 
diff --git a/pyresample/bilinear/xarr.py b/pyresample/bilinear/xarr.py
index 3d2c44002..8cfbf0f0f 100644
--- a/pyresample/bilinear/xarr.py
+++ b/pyresample/bilinear/xarr.py
@@ -273,7 +273,12 @@ def _check_data_shape(data, input_xy_shape):
 
     # Ensure two dimensions
     if data.ndim == 1:
-        data = DataArray(da.map_blocks(np.expand_dims, data.data, 0, new_axis=[0]))
+        data = DataArray(da.map_blocks(np.expand_dims,
+                                       data.data,
+                                       0,
+                                       meta=np.array((), dtype=data.dtype),
+                                       dtype=data.dtype,
+                                       new_axis=[0]))
 
     return data
 
diff --git a/pyresample/bucket/__init__.py b/pyresample/bucket/__init__.py
index 6ea45d768..9851da571 100644
--- a/pyresample/bucket/__init__.py
+++ b/pyresample/bucket/__init__.py
@@ -181,6 +181,8 @@ def _get_indices(self):
         lons = self.source_lons.ravel()
         lats = self.source_lats.ravel()
         result = da.map_blocks(self._get_proj_coordinates, lons, lats,
+                               meta=np.array((), dtype=lons.dtype),
+                               dtype=lons.dtype,
                                new_axis=0, chunks=(2,) + lons.chunks)
         proj_x = result[0, :]
         proj_y = result[1, :]
diff --git a/pyresample/future/resamplers/nearest.py b/pyresample/future/resamplers/nearest.py
index 41167668a..e48c8b3bb 100644
--- a/pyresample/future/resamplers/nearest.py
+++ b/pyresample/future/resamplers/nearest.py
@@ -189,6 +189,7 @@ def _query_resample_kdtree(self,
             valid_output_index, 'ji', *args, kdtree=resample_kdtree,
             neighbours=neighbors, epsilon=epsilon,
             radius=radius_of_influence, dtype=np.int64,
+            meta=np.array((), dtype=np.int64),
             new_axes={'k': neighbors}, concatenate=True)
         return res
 
@@ -339,6 +340,7 @@ def get_sample_from_neighbor_info(
             new_data, src_adims,
             vii_slices=vii_slices, ia_slices=ia_slices,
             fill_value=fill_value,
+            meta=np.array((), dtype=new_data.dtype),
             dtype=new_data.dtype, concatenate=True)
         res = DataArray(res, dims=dst_dims,
                         attrs=deepcopy(data.attrs))
diff --git a/pyresample/geometry.py b/pyresample/geometry.py
index 8970c3d16..70e1c625b 100644
--- a/pyresample/geometry.py
+++ b/pyresample/geometry.py
@@ -873,12 +873,16 @@ def aggregate(self, **dims):
         res = da.map_blocks(self._do_transform, latlong, geocent,
                             self.lons.data, self.lats.data,
                             da.zeros_like(self.lons.data), new_axis=[2],
+                            meta=np.array((), dtype=self.lons.dtype),
+                            dtype=self.lons.dtype,
                             chunks=(self.lons.chunks[0], self.lons.chunks[1], 3))
         res = DataArray(res, dims=['y', 'x', 'coord'], coords=self.lons.coords)
         res = res.coarsen(**dims).mean()
         lonlatalt = da.map_blocks(self._do_transform, geocent, latlong,
                                   res[:, :, 0].data, res[:, :, 1].data,
                                   res[:, :, 2].data, new_axis=[2],
+                                  meta=np.array((), dtype=res.dtype),
+                                  dtype=res.dtype,
                                   chunks=res.data.chunks)
         lons = DataArray(lonlatalt[:, :, 0], dims=self.lons.dims,
                          coords=res.coords, attrs=self.lons.attrs.copy())
diff --git a/pyresample/kd_tree.py b/pyresample/kd_tree.py
index fc0d84ee1..288876ddb 100644
--- a/pyresample/kd_tree.py
+++ b/pyresample/kd_tree.py
@@ -999,6 +999,7 @@ def query_resample_kdtree(self,
                         valid_oi, 'ji', *args, kdtree=resample_kdtree,
                         neighbours=self.neighbours, epsilon=self.epsilon,
                         radius=self.radius_of_influence, dtype=np.int64,
+                        meta=np.array((), dtype=np.int64),
                         new_axes={'k': self.neighbours}, concatenate=True)
         return res, None
 
@@ -1155,6 +1156,7 @@ def contain_coords(var, coord_list):
                         new_data, src_adims,
                         vii_slices=vii_slices, ia_slices=ia_slices,
                         fill_value=fill_value,
+                        meta=np.array((), dtype=new_data.dtype),
                         dtype=new_data.dtype, concatenate=True)
         res = DataArray(res, dims=dst_dims, coords=coords,
                         attrs=deepcopy(data.attrs))
diff --git a/pyresample/utils/proj4.py b/pyresample/utils/proj4.py
index d40cff628..565643c6e 100644
--- a/pyresample/utils/proj4.py
+++ b/pyresample/utils/proj4.py
@@ -145,6 +145,7 @@ def transform(self, x, y, **kwargs):
         result = da.map_blocks(_transform_dask_chunk, x, y,
                                crs_from.to_wkt(), crs_to.to_wkt(),
                                dtype=x.dtype, chunks=x.chunks + ((2,),),
+                               meta=np.array((), dtype=x.dtype),
                                kwargs=self.kwargs,
                                transform_kwargs=kwargs,
                                new_axis=x.ndim)