diff --git a/nes/nc_projections/default_nes.py b/nes/nc_projections/default_nes.py
index 8edaa24a9643cdd6286326c075c3600a64bcd75e..aac531c4272abf692649944ce9aef7342becc72e 100644
--- a/nes/nc_projections/default_nes.py
+++ b/nes/nc_projections/default_nes.py
@@ -157,6 +157,7 @@ class Nes(object):
             # Complete dimensions
             self._time = times
             self._time_bnds = self.__get_time_bnds(create_nes)
+            self._lat_bnds, self._lon_bnds = self.__get_coordinates_bnds(create_nes)
             self._lev = {'data': np.array([0]),
                          'units': '',
                          'positive': 'up'}
@@ -169,6 +170,7 @@ class Nes(object):
             self.time = self._time[self.read_axis_limits['t_min']:self.read_axis_limits['t_max']]
             self.time_bnds = self._time_bnds
             self.lev = deepcopy(self._lev)
+            self.lat_bnds, self.lon_bnds = self._lat_bnds, self._lon_bnds
 
             # Set NetCDF attributes
             self.global_attrs = self.__get_global_attributes(create_nes)
@@ -199,6 +201,7 @@ class Nes(object):
             self._lev = self._get_coordinate_dimension(['lev', 'level', 'lm', 'plev'])
             self._lat = self._get_coordinate_dimension(['lat', 'latitude'])
             self._lon = self._get_coordinate_dimension(['lon', 'longitude'])
+            self._lat_bnds, self._lon_bnds = self.__get_coordinates_bnds()
 
             # Set axis limits for parallel reading
             self.read_axis_limits = self.get_read_axis_limits()
@@ -209,6 +212,7 @@ class Nes(object):
             self.lev = self._get_coordinate_values(self._lev, 'Z')
             self.lat = self._get_coordinate_values(self._lat, 'Y')
             self.lon = self._get_coordinate_values(self._lon, 'X')
+            self.lat_bnds, self.lon_bnds = self._lat_bnds, self._lon_bnds
 
             # Set axis limits for parallel writing
             self.write_axis_limits = self.get_write_axis_limits()
@@ -288,6 +292,10 @@ class Nes(object):
             del self._lat
             del self.lon
             del self._lon
+            del self._lat_bnds
+            del self.lat_bnds
+            del self._lon_bnds
+            del self.lon_bnds
         except AttributeError:
             pass
 
@@ -433,6 +441,36 @@ class Nes(object):
 
         return None
 
+    def set_lat_bnds(self, lat_bnds):
+        """
+        Modify the original latitude bounds values with new ones.
+
+        Parameters
+        ----------
+        lat_bnds : list
+            List with the new latitude bounds information to be set.
+        """
+
+        self._lat_bnds = deepcopy(lat_bnds)
+        self.lat_bnds = deepcopy(lat_bnds)
+
+        return None
+
+    def set_lon_bnds(self, lon_bnds):
+        """
+        Modify the original longitude bounds values with new ones.
+
+        Parameters
+        ----------
+        lon_bnds : list
+            List with the new longitude bounds information to be set.
+        """
+
+        self._lon_bnds = deepcopy(lon_bnds)
+        self.lon_bnds = deepcopy(lon_bnds)
+
+        return None
+
     def create_bounds(self, coordinates, inc, spatial_nv=2, inverse=False):
         """
         Calculate the vertices coordinates.
@@ -1122,7 +1160,7 @@ class Nes(object):
 
         Returns
         -------
-        time : list
+        time_bnds : list
             List of time bounds (datetime) of the NetCDF data.
         """
 
@@ -1142,10 +1180,55 @@ class Nes(object):
             else:
                 time_bnds = None
             time_bnds = self.comm.bcast(time_bnds, root=0)
+
         self.free_vars('time_bnds')
 
         return time_bnds
 
+    def __get_coordinates_bnds(self, create_nes=False):
+        """
+        Get the NetCDF coordinates bounds values.
+
+        Parameters
+        ----------
+        create_nes : bool
+            Indicates if you want to create the object from scratch (True) or through an existing file.
+
+        Returns
+        -------
+        lat_bnds : list
+            List of latitude bounds of the NetCDF data.
+        lon_bnds : list
+            List of longitude bounds of the NetCDF data.
+        """
+
+        if self.is_xarray:
+            lat_bnds = self.variables['lat_bnds']
+            lon_bnds = self.variables['lon_bnds']
+        else:
+            if self.master:
+                if not create_nes:
+                    if 'lat_bnds' in self.netcdf.variables.keys():
+                        lat_bnds = self.netcdf.variables['lat_bnds'][:]
+                    else:
+                        lat_bnds = None
+                    if 'lon_bnds' in self.netcdf.variables.keys():
+                        lon_bnds = self.netcdf.variables['lon_bnds'][:]
+                    else:
+                        lon_bnds = None
+                else:
+                    lat_bnds = None
+                    lon_bnds = None
+            else:
+                lat_bnds = None
+                lon_bnds = None
+            lat_bnds = self.comm.bcast(lat_bnds, root=0)
+            lon_bnds = self.comm.bcast(lon_bnds, root=0)
+
+        self.free_vars(['lat_bnds', 'lon_bnds'])
+
+        return lat_bnds, lon_bnds
+
     def _get_coordinate_dimension(self, possible_names):
         """
         Read the coordinate dimension data.
@@ -1547,7 +1630,7 @@ class Nes(object):
 
     def _create_dimensions(self, netcdf):
         """
-        Create the 'lev' and 'time' dimension.
+        Create 'time', 'time_bnds', 'lev', 'lon' and 'lat' dimensions.
 
         Parameters
         ----------
@@ -1555,9 +1638,14 @@ class Nes(object):
             netcdf4-python opened Dataset.
         """
 
+        # Create time dimension
         netcdf.createDimension('time', None)
+
+        # Create time_nv (number of vertices) dimension
         if self._time_bnds is not None:
             netcdf.createDimension('time_nv', 2)
+        
+        # Create lev, lon and lat dimensions
         netcdf.createDimension('lev', len(self.lev['data']))
         netcdf.createDimension('lon', len(self._lon['data']))
         netcdf.createDimension('lat', len(self._lat['data']))
@@ -1566,7 +1654,7 @@ class Nes(object):
 
     def _create_dimension_variables(self, netcdf):
         """
-        Create the 'lev' and 'time' variables.
+        Create the 'time', 'time_bnds', 'lev', 'lat', 'lat_bnds', 'lon' and 'lon_bnds' variables.
 
         Parameters
         ----------
@@ -1614,20 +1702,40 @@ class Nes(object):
         lat.axis = 'Y'
         lat.long_name = 'latitude coordinate'
         lat.standard_name = 'latitude'
+        if self._lat_bnds is not None:
+            lat.bounds = 'lat_bnds'
         if self.size > 1:
             lat.set_collective(True)
         lat[:] = self._lat['data']
 
+        # LATITUDES BOUNDS
+        if self._lat_bnds is not None:
+            lat_bnds_var = netcdf.createVariable('lat_bnds', np.float64, self._var_dim + ('spatial_nv',), 
+                                                 zlib=self.zip_lvl, complevel=self.zip_lvl)
+            if self.size > 1:
+                lat_bnds_var.set_collective(True)
+            lat_bnds_var[:] = self._lat_bnds[:]
+
         # LONGITUDES
         lon = netcdf.createVariable('lon', np.float64, self._lon_dim, zlib=self.zip_lvl > 0, complevel=self.zip_lvl)
         lon.units = 'degrees_east'
         lon.axis = 'X'
         lon.long_name = 'longitude coordinate'
         lon.standard_name = 'longitude'
+        if self._lon_bnds is not None:
+            lon.bounds = 'lon_bnds'
         if self.size > 1:
             lon.set_collective(True)
         lon[:] = self._lon['data']
 
+        # LONGITUDES BOUNDS
+        if self._lon_bnds is not None:
+            lon_bnds_var = netcdf.createVariable('lon_bnds', np.float64, self._var_dim + ('spatial_nv',), 
+                                                 zlib=self.zip_lvl, complevel=self.zip_lvl)
+            if self.size > 1:
+                lon_bnds_var.set_collective(True)
+            lon_bnds_var[:] = self._lon_bnds[:]
+
         return None
 
     def _create_variables(self, netcdf, chunking=False):
diff --git a/nes/nc_projections/latlon_nes.py b/nes/nc_projections/latlon_nes.py
index c31b06d89a6945ce1c59c9301c437ee4912135f7..d8f05eea59c29ad128353768563a93c8c429c27e 100644
--- a/nes/nc_projections/latlon_nes.py
+++ b/nes/nc_projections/latlon_nes.py
@@ -96,6 +96,24 @@ class LatLonNes(Nes):
                         avoid_last_hours=avoid_last_hours, first_level=first_level, last_level=last_level)
         return new
 
+    def _create_dimensions(self, netcdf):
+        """
+        Create 'spatial_nv' dimension and the super dimensions ('time', 'time_nv', 'lev', 'lat', 'lon').
+
+        Parameters
+        ----------
+        netcdf : Dataset
+            NetCDF object.
+        """
+
+        super(LatLonNes, self)._create_dimensions(netcdf)
+        
+        # Create spatial_nv (number of vertices) dimension
+        if (self._lat_bnds is not None) and (self._lon_bnds is not None):
+            netcdf.createDimension('spatial_nv', 2)
+
+        return None
+
     def _create_centre_coordinates(self, **kwargs):
         """
         Calculate centre latitudes and longitudes from grid details.
diff --git a/nes/nc_projections/lcc_nes.py b/nes/nc_projections/lcc_nes.py
index 235d1be2a9f36d25c021e0cac2f468cadd35e949..db92c9bee963994331e0123eac40cfd68da9363e 100644
--- a/nes/nc_projections/lcc_nes.py
+++ b/nes/nc_projections/lcc_nes.py
@@ -144,7 +144,7 @@ class LCCNes(Nes):
 
     def _create_dimensions(self, netcdf):
         """
-        Create the 'y', 'x' dimensions and the super dimensions ('lev', 'time').
+        Create 'y', 'x' and 'spatial_nv' dimensions and the super dimensions ('lev', 'time').
 
         Parameters
         ----------
@@ -153,9 +153,14 @@ class LCCNes(Nes):
         """
         super(LCCNes, self)._create_dimensions(netcdf)
 
+        # Create y and x dimensions
         netcdf.createDimension('y', len(self._y['data']))
         netcdf.createDimension('x', len(self._x['data']))
 
+        # Create spatial_nv (number of vertices) dimension
+        if (self._lat_bnds is not None) and (self._lon_bnds is not None):
+            netcdf.createDimension('spatial_nv', 4)
+
         return None
 
     def _create_dimension_variables(self, netcdf):
diff --git a/nes/nc_projections/mercator_nes.py b/nes/nc_projections/mercator_nes.py
index a6e640c3d8506f9a0feb39403e4b52ba958d27f4..50e2a691da6f07a419d377796f4b4fb1ac310e77 100644
--- a/nes/nc_projections/mercator_nes.py
+++ b/nes/nc_projections/mercator_nes.py
@@ -144,18 +144,24 @@ class MercatorNes(Nes):
 
     def _create_dimensions(self, netcdf):
         """
-        Create the 'y', 'x' dimensions and the super dimensions ('lev', 'time').
+        Create 'y', 'x' and 'spatial_nv' dimensions and the super dimensions ('lev', 'time').
 
         Parameters
         ----------
         netcdf : Dataset
             NetCDF object.
         """
+
         super(MercatorNes, self)._create_dimensions(netcdf)
 
+        # Create y and x dimensions
         netcdf.createDimension('y', len(self._y['data']))
         netcdf.createDimension('x', len(self._x['data']))
 
+        # Create spatial_nv (number of vertices) dimension
+        if (self._lat_bnds is not None) and (self._lon_bnds is not None):
+            netcdf.createDimension('spatial_nv', 4)
+
         return None
 
     def _create_dimension_variables(self, netcdf):
diff --git a/nes/nc_projections/points_nes.py b/nes/nc_projections/points_nes.py
index a17e297c660ccf62b44f13fafaa6281c35c0eb0b..8136d6ce487347364890926ab598b2fc6a6d4622 100644
--- a/nes/nc_projections/points_nes.py
+++ b/nes/nc_projections/points_nes.py
@@ -117,7 +117,7 @@ class PointsNes(Nes):
 
     def _create_dimensions(self, netcdf):
         """
-        Create the 'lev', 'time_nv', 'station' dimensions.
+        Create 'lev', 'time_nv', 'station', 'spatial_nv' and 'strlen' dimensions.
 
         Parameters
         ----------
@@ -127,9 +127,16 @@ class PointsNes(Nes):
 
         # Create time dimension
         netcdf.createDimension('time', None)
+
+        # Create time_nv (number of vertices) dimension
         if self._time_bnds is not None:
             netcdf.createDimension('time_nv', 2)
 
+        # Create spatial_nv (number of vertices) dimension
+        if (self._lat_bnds is not None) and (self._lon_bnds is not None):
+            netcdf.createDimension('spatial_nv', 2)
+
+        # Create station dimension
         # The number of longitudes is equal to the number of stations
         netcdf.createDimension('station', len(self._lon['data']))
 
@@ -142,7 +149,7 @@ class PointsNes(Nes):
 
     def _create_dimension_variables(self, netcdf):
         """
-        Create the 'time', 'time_bnds' and 'station' variables.
+        Create the 'time', 'time_bnds', 'station', 'lat', 'lat_bnds', 'lon' and 'lon_bnds' variables.
 
         Parameters
         ----------
@@ -191,10 +198,20 @@ class PointsNes(Nes):
         lat.axis = 'Y'
         lat.long_name = 'latitude coordinate'
         lat.standard_name = 'latitude'
+        if self._lat_bnds is not None:
+            lat.bounds = 'lat_bnds'
         if self.size > 1:
             lat.set_collective(True)
         lat[:] = self._lat['data']
 
+        # LATITUDES BOUNDS
+        if self._lat_bnds is not None:
+            lat_bnds_var = netcdf.createVariable('lat_bnds', np.float64, self._var_dim + ('spatial_nv',), 
+                                                 zlib=self.zip_lvl, complevel=self.zip_lvl)
+            if self.size > 1:
+                lat_bnds_var.set_collective(True)
+            lat_bnds_var[:] = self._lat_bnds[:]
+
         # LONGITUDES
         lon = netcdf.createVariable('lon', np.float64, self._lon_dim, 
                                      zlib=self.zip_lvl > 0, complevel=self.zip_lvl)
@@ -202,10 +219,20 @@ class PointsNes(Nes):
         lon.axis = 'X'
         lon.long_name = 'longitude coordinate'
         lon.standard_name = 'longitude'
+        if self._lon_bnds is not None:
+            lon.bounds = 'lon_bnds'
         if self.size > 1:
             lon.set_collective(True)
         lon[:] = self._lon['data']
 
+        # LONGITUDES BOUNDS
+        if self._lon_bnds is not None:
+            lon_bnds_var = netcdf.createVariable('lon_bnds', np.float64, self._var_dim + ('spatial_nv',), 
+                                                 zlib=self.zip_lvl, complevel=self.zip_lvl)
+            if self.size > 1:
+                lon_bnds_var.set_collective(True)
+            lon_bnds_var[:] = self._lon_bnds[:]
+
         return None
 
     def _get_coordinate_values(self, coordinate_info, coordinate_axis):
diff --git a/nes/nc_projections/points_nes_ghost.py b/nes/nc_projections/points_nes_ghost.py
index a90158ae89a5e77027e7850bf4853ad3a4d2bc93..b8fc489a115f35c23fb1b22593aa05039dbd759a 100644
--- a/nes/nc_projections/points_nes_ghost.py
+++ b/nes/nc_projections/points_nes_ghost.py
@@ -127,7 +127,8 @@ class PointsNesGHOST(PointsNes):
 
     def _create_dimensions(self, netcdf):
         """
-        Create the 'N_flag_codes' and 'N_qa_codes' dimensions and the super dimensions ('time', 'station').
+        Create 'N_flag_codes' and 'N_qa_codes' dimensions and the super dimensions 
+        ('lev', 'time_nv', 'station', 'spatial_nv' and 'strlen').
 
         Parameters
         ----------
@@ -137,6 +138,7 @@ class PointsNesGHOST(PointsNes):
 
         super(PointsNesGHOST, self)._create_dimensions(netcdf)
 
+        # Create N_flag_codes and N_qa_codes dimensions
         netcdf.createDimension('N_flag_codes', self._flag['data'].shape[2])
         netcdf.createDimension('N_qa_codes', self._qa['data'].shape[2])
 
@@ -144,7 +146,7 @@ class PointsNesGHOST(PointsNes):
 
     def _create_dimension_variables(self, netcdf):
         """
-        Create the 'station' variables.
+        Create the 'time', 'time_bnds', 'station', 'lat', 'lat_bnds', 'lon' and 'lon_bnds' variables.
 
         Parameters
         ----------
@@ -193,10 +195,20 @@ class PointsNesGHOST(PointsNes):
         lat.axis = 'Y'
         lat.long_name = 'latitude coordinate'
         lat.standard_name = 'latitude'
+        if self._lat_bnds is not None:
+            lat.bounds = 'lat_bnds'
         if self.size > 1:
             lat.set_collective(True)
         lat[:] = self._lat['data']
 
+        # LATITUDES BOUNDS
+        if self._lat_bnds is not None:
+            lat_bnds_var = netcdf.createVariable('lat_bnds', np.float64, self._var_dim + ('spatial_nv',), 
+                                                 zlib=self.zip_lvl, complevel=self.zip_lvl)
+            if self.size > 1:
+                lat_bnds_var.set_collective(True)
+            lat_bnds_var[:] = self._lat_bnds[:]
+
         # LONGITUDES
         lon = netcdf.createVariable('longitude', np.float64, self._lon_dim, 
                                      zlib=self.zip_lvl > 0, complevel=self.zip_lvl)
@@ -204,10 +216,20 @@ class PointsNesGHOST(PointsNes):
         lon.axis = 'X'
         lon.long_name = 'longitude coordinate'
         lon.standard_name = 'longitude'
+        if self._lon_bnds is not None:
+            lon.bounds = 'lon_bnds'
         if self.size > 1:
             lon.set_collective(True)
         lon[:] = self._lon['data']
 
+        # LONGITUDES BOUNDS
+        if self._lon_bnds is not None:
+            lon_bnds_var = netcdf.createVariable('lon_bnds', np.float64, self._var_dim + ('spatial_nv',), 
+                                                 zlib=self.zip_lvl, complevel=self.zip_lvl)
+            if self.size > 1:
+                lon_bnds_var.set_collective(True)
+            lon_bnds_var[:] = self._lon_bnds[:]
+
     def erase_flags(self):
         first_time_idx = self.get_time_id(self.hours_start, first=True)
         last_time_idx = self.get_time_id(self.hours_end, first=False)
diff --git a/nes/nc_projections/points_nes_providentia.py b/nes/nc_projections/points_nes_providentia.py
index d45f8269a0be879d1272dcd82925e61523e60826..347bf31626d0029ac6f989f5aedfc326e8e80027 100644
--- a/nes/nc_projections/points_nes_providentia.py
+++ b/nes/nc_projections/points_nes_providentia.py
@@ -169,7 +169,8 @@ class PointsNesProvidentia(PointsNes):
 
     def _create_dimensions(self, netcdf):
         """
-        Create the 'grid_edge', 'model_latitude', 'model_longitude' dimensions.
+        Create 'grid_edge', 'model_latitude' and 'model_longitude' dimensions and the super dimensions
+        ('lev', 'time_nv', 'station', 'spatial_nv', 'strlen').
 
         Parameters
         ----------
@@ -179,6 +180,7 @@ class PointsNesProvidentia(PointsNes):
 
         super(PointsNesProvidentia, self)._create_dimensions(netcdf)
         
+        # Create grid_edge, model_latitude and model_longitude dimensions
         netcdf.createDimension('grid_edge', len(self._grid_edge_lon['data']))
         netcdf.createDimension('model_latitude', self._model_centre_lon['data'].shape[0])
         netcdf.createDimension('model_longitude', self._model_centre_lon['data'].shape[1])
diff --git a/nes/nc_projections/rotated_nes.py b/nes/nc_projections/rotated_nes.py
index ae3abb2a394fb6b24d10614ec77a2036ac37d092..697921e36855b89623d0305fafc9e4f718a2eddb 100644
--- a/nes/nc_projections/rotated_nes.py
+++ b/nes/nc_projections/rotated_nes.py
@@ -145,7 +145,7 @@ class RotatedNes(Nes):
 
     def _create_dimensions(self, netcdf):
         """
-        Create the 'rlat', 'rlon' dimensions and the super dimensions ('lev', 'time').
+        Create 'rlat', 'rlon'  and 'spatial_nv' dimensions and the super dimensions ('lev', 'time').
 
         Parameters
         ----------
@@ -154,9 +154,14 @@ class RotatedNes(Nes):
         """
         super(RotatedNes, self)._create_dimensions(netcdf)
 
+        # Create rlat and rlon dimensions
         netcdf.createDimension('rlon', len(self._rlon['data']))
         netcdf.createDimension('rlat', len(self._rlat['data']))
 
+        # Create spatial_nv (number of vertices) dimension
+        if (self._lat_bnds is not None) and (self._lon_bnds is not None):
+            netcdf.createDimension('spatial_nv', 4)
+
         return None
 
     def _create_dimension_variables(self, netcdf):
@@ -259,14 +264,14 @@ class RotatedNes(Nes):
         stph = np.sin(tph)
         ctph = np.cos(tph)
 
-        # Latitudes
+        # LATITUDES
         sph = (ctph0 * stph) + (stph0 * ctph * ctlm)
         sph[sph > 1.] = 1.
         sph[sph < -1.] = -1.
         aph = np.arcsin(sph)
         aphd = aph / degrees_to_radians
 
-        # Longitudes
+        # LONGITUDES
         anum = ctph * stlm
         denom = (ctlm * ctph - stph0 * sph) / ctph0
         relm = np.arctan2(anum, denom) - math.pi
diff --git a/tutorials/1.Introduction/1.5.Read_Write_Mercator.ipynb b/tutorials/1.Introduction/1.5.Read_Write_Mercator.ipynb
index ec31ac656aa0a887efb6a91322133907f74e3800..67f9bb479f4f32d46bc68c8ff0f816ca3bd1d204 100644
--- a/tutorials/1.Introduction/1.5.Read_Write_Mercator.ipynb
+++ b/tutorials/1.Introduction/1.5.Read_Write_Mercator.ipynb
@@ -44,15 +44,6 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# xr.open_dataset(nc_path_1, decode_times=False).drop(['lat_bnds', 'lon_bnds']).to_netcdf('input/mercator_grid_example.nc')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -409,17 +400,20 @@
        "  fill: currentColor;\n",
        "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:    (time: 1, y: 236, x: 210)\n",
+       "Dimensions:    (time: 1, y: 236, x: 210, nv: 4)\n",
        "Coordinates:\n",
        "  * time       (time) float64 0.0\n",
        "    lat        (y, x) float32 -43.52 -43.52 -43.52 -43.52 ... 49.6 49.6 49.6\n",
        "    lon        (y, x) float32 -18.91 -18.46 -18.01 -17.56 ... 74.22 74.67 75.12\n",
        "  * x          (x) float64 -1.01e+05 -5.101e+04 ... 1.03e+07 1.035e+07\n",
        "  * y          (y) float64 -5.382e+06 -5.332e+06 ... 6.318e+06 6.368e+06\n",
+       "Dimensions without coordinates: nv\n",
        "Data variables:\n",
+       "    lat_bnds   (y, x, nv) float32 ...\n",
+       "    lon_bnds   (y, x, nv) float32 ...\n",
        "    var_aux    (time, y, x) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
        "    mercator   int32 -2147483647\n",
-       "    cell_area  (y, x) float32 1.316e+09 1.316e+09 ... 1.051e+09 1.051e+09</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d4c2fdcb-0bba-4f4a-b1e5-f3415c8ca114' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d4c2fdcb-0bba-4f4a-b1e5-f3415c8ca114' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>y</span>: 236</li><li><span class='xr-has-index'>x</span>: 210</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8ddfeff8-eafc-4ca4-94fe-ade6a8e027c7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8ddfeff8-eafc-4ca4-94fe-ade6a8e027c7' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-4fccc488-224e-4ec6-a258-094177868a75' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fccc488-224e-4ec6-a258-094177868a75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61dc5414-87b7-44e8-9269-7bd431a0ce52' class='xr-var-data-in' type='checkbox'><label for='data-61dc5414-87b7-44e8-9269-7bd431a0ce52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>months since 2000-01-01 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>calendar :</span></dt><dd>gregorian</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd32bd03-2269-47d6-99c0-061b00868878' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd32bd03-2269-47d6-99c0-061b00868878' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-498e5f0a-f52b-4b78-a8e9-ac87fa5ecf90' class='xr-var-data-in' type='checkbox'><label for='data-498e5f0a-f52b-4b78-a8e9-ac87fa5ecf90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([[-43.5182  , -43.5182  , -43.5182  , ..., -43.5182  , -43.5182  ,\n",
+       "    cell_area  (y, x) float32 1.316e+09 1.316e+09 ... 1.051e+09 1.051e+09</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0aef4f29-8a03-4885-975b-84c4e0d42c58' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0aef4f29-8a03-4885-975b-84c4e0d42c58' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>y</span>: 236</li><li><span class='xr-has-index'>x</span>: 210</li><li><span>nv</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-73fea74e-30e2-41b7-8ffd-6de2690f25cc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-73fea74e-30e2-41b7-8ffd-6de2690f25cc' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-d5f0346e-67be-471f-9f7b-2db54686d203' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5f0346e-67be-471f-9f7b-2db54686d203' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-baef0418-5f5c-46f8-a999-a93b4ed8a978' class='xr-var-data-in' type='checkbox'><label for='data-baef0418-5f5c-46f8-a999-a93b4ed8a978' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>months since 2000-01-01 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>calendar :</span></dt><dd>gregorian</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d80aec41-c0ce-470a-9db5-06141853556a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d80aec41-c0ce-470a-9db5-06141853556a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a8912a4-8a9d-477a-985b-5ca2560aca45' class='xr-var-data-in' type='checkbox'><label for='data-9a8912a4-8a9d-477a-985b-5ca2560aca45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([[-43.5182  , -43.5182  , -43.5182  , ..., -43.5182  , -43.5182  ,\n",
        "        -43.5182  ],\n",
        "       [-43.191082, -43.191082, -43.191082, ..., -43.191082, -43.191082,\n",
        "        -43.191082],\n",
@@ -431,7 +425,7 @@
        "       [ 49.31089 ,  49.31089 ,  49.31089 , ...,  49.31089 ,  49.31089 ,\n",
        "         49.31089 ],\n",
        "       [ 49.60332 ,  49.60332 ,  49.60332 , ...,  49.60332 ,  49.60332 ,\n",
-       "         49.60332 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-99860731-b6a7-4773-8326-759927c04d31' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99860731-b6a7-4773-8326-759927c04d31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a4fb1a2-68a3-4807-b7c3-248acc553fb1' class='xr-var-data-in' type='checkbox'><label for='data-3a4fb1a2-68a3-4807-b7c3-248acc553fb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([[-18.9089  , -18.459013, -18.009129, ...,  74.217415,  74.6673  ,\n",
+       "         49.60332 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-515482b3-0ba7-4703-a02f-623cdaba108e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-515482b3-0ba7-4703-a02f-623cdaba108e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a394502-b35f-4143-b9ee-d8888f5553bc' class='xr-var-data-in' type='checkbox'><label for='data-7a394502-b35f-4143-b9ee-d8888f5553bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([[-18.9089  , -18.459013, -18.009129, ...,  74.217415,  74.6673  ,\n",
        "         75.11718 ],\n",
        "       [-18.9089  , -18.459013, -18.009129, ...,  74.217415,  74.6673  ,\n",
        "         75.11718 ],\n",
@@ -443,12 +437,12 @@
        "       [-18.9089  , -18.459013, -18.009129, ...,  74.217415,  74.6673  ,\n",
        "         75.11718 ],\n",
        "       [-18.9089  , -18.459013, -18.009129, ...,  74.217415,  74.6673  ,\n",
-       "         75.11718 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.01e+05 -5.101e+04 ... 1.035e+07</div><input id='attrs-d4f4ab2c-c0eb-4833-84d4-314dfaa9382c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4f4ab2c-c0eb-4833-84d4-314dfaa9382c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7405f6ca-c430-4255-bf91-8031d2a003ed' class='xr-var-data-in' type='checkbox'><label for='data-7405f6ca-c430-4255-bf91-8031d2a003ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1000 m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-1.010145e+05, -5.101450e+04, -1.014500e+03, ...,  1.024899e+07,\n",
-       "        1.029899e+07,  1.034899e+07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.382e+06 -5.332e+06 ... 6.368e+06</div><input id='attrs-390c0124-c863-4b52-90b6-da5cfe0c64b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-390c0124-c863-4b52-90b6-da5cfe0c64b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e04b776-c876-4f5c-9b98-398fc0596fc3' class='xr-var-data-in' type='checkbox'><label for='data-8e04b776-c876-4f5c-9b98-398fc0596fc3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1000 m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-5382460., -5332460., -5282460., ...,  6267540.,  6317540.,  6367540.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-88feda83-da55-427d-8137-4af1dccac8ff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-88feda83-da55-427d-8137-4af1dccac8ff' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>var_aux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-695ef871-294f-4263-a009-d1618a68b436' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-695ef871-294f-4263-a009-d1618a68b436' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-633797ea-cacd-417c-a312-fb255476a3c1' class='xr-var-data-in' type='checkbox'><label for='data-633797ea-cacd-417c-a312-fb255476a3c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>?</dd><dt><span>cell_measures :</span></dt><dd>area: cell_area</dd><dt><span>grid_mapping :</span></dt><dd>mercator</dd></dl></div><div class='xr-var-data'><pre>array([[[0., 0., ..., 0., 0.],\n",
+       "         75.11718 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.01e+05 -5.101e+04 ... 1.035e+07</div><input id='attrs-4826cebe-d4b8-453c-a00a-b3a2c3cd9787' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4826cebe-d4b8-453c-a00a-b3a2c3cd9787' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd221dee-0b68-488e-9b78-570d8f448be7' class='xr-var-data-in' type='checkbox'><label for='data-bd221dee-0b68-488e-9b78-570d8f448be7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1000 m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-1.010145e+05, -5.101450e+04, -1.014500e+03, ...,  1.024899e+07,\n",
+       "        1.029899e+07,  1.034899e+07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.382e+06 -5.332e+06 ... 6.368e+06</div><input id='attrs-e7543f5e-f4c9-4de5-aca4-1301f7ad4899' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7543f5e-f4c9-4de5-aca4-1301f7ad4899' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdfcc448-194d-4bd7-b221-3cf503bf0688' class='xr-var-data-in' type='checkbox'><label for='data-fdfcc448-194d-4bd7-b221-3cf503bf0688' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1000 m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-5382460., -5332460., -5282460., ...,  6267540.,  6317540.,  6367540.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-023813af-9b0f-4d70-804d-085689bf6a0c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-023813af-9b0f-4d70-804d-085689bf6a0c' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(y, x, nv)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-88aca0de-1e68-45b8-b7d4-c9d489b92f7d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88aca0de-1e68-45b8-b7d4-c9d489b92f7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08cc2eaf-f564-4c35-9f85-9172a33f0bb4' class='xr-var-data-in' type='checkbox'><label for='data-08cc2eaf-f564-4c35-9f85-9172a33f0bb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[198240 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(y, x, nv)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2adf5220-e3a3-4827-b4ab-be8b16574350' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2adf5220-e3a3-4827-b4ab-be8b16574350' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6738769-aa92-4bbe-a542-61a11e5a43bb' class='xr-var-data-in' type='checkbox'><label for='data-c6738769-aa92-4bbe-a542-61a11e5a43bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[198240 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>var_aux</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-33c380a2-be28-4742-a8b7-ee54a9fdfd36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33c380a2-be28-4742-a8b7-ee54a9fdfd36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3cd0abc-aeb9-46d1-8696-5153b516cfab' class='xr-var-data-in' type='checkbox'><label for='data-e3cd0abc-aeb9-46d1-8696-5153b516cfab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>?</dd><dt><span>cell_measures :</span></dt><dd>area: cell_area</dd><dt><span>grid_mapping :</span></dt><dd>mercator</dd></dl></div><div class='xr-var-data'><pre>array([[[0., 0., ..., 0., 0.],\n",
        "        [0., 0., ..., 0., 0.],\n",
        "        ...,\n",
        "        [0., 0., ..., 0., 0.],\n",
-       "        [0., 0., ..., 0., 0.]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mercator</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a395239d-6f68-4cbb-a624-d17871dfa8c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a395239d-6f68-4cbb-a624-d17871dfa8c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a11d032-6d68-4b18-87f8-c1d01a7371b5' class='xr-var-data-in' type='checkbox'><label for='data-5a11d032-6d68-4b18-87f8-c1d01a7371b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping_name :</span></dt><dd>mercator</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>-18.0</dd><dt><span>standard_parallel :</span></dt><dd>-1.5</dd></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cell_area</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8283abe8-a015-4cca-9c8d-7619d90434ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8283abe8-a015-4cca-9c8d-7619d90434ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-719b73ee-be3e-4b30-b393-976abd2bd330' class='xr-var-data-in' type='checkbox'><label for='data-719b73ee-be3e-4b30-b393-976abd2bd330' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>area of the grid cell</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><pre>array([[1.315942e+09, 1.315937e+09, 1.315942e+09, ..., 1.315931e+09,\n",
+       "        [0., 0., ..., 0., 0.]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mercator</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-04d02fdb-1942-44a3-a397-ece7dfcace63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04d02fdb-1942-44a3-a397-ece7dfcace63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb36c11b-f529-46c7-a61f-82da0d974a59' class='xr-var-data-in' type='checkbox'><label for='data-fb36c11b-f529-46c7-a61f-82da0d974a59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping_name :</span></dt><dd>mercator</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>-18.0</dd><dt><span>standard_parallel :</span></dt><dd>-1.5</dd></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cell_area</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1c93d20f-14a7-4dea-b330-82b0c44e59de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c93d20f-14a7-4dea-b330-82b0c44e59de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5adfd32e-a362-4003-bf13-5f60bfa1e8d6' class='xr-var-data-in' type='checkbox'><label for='data-5adfd32e-a362-4003-bf13-5f60bfa1e8d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>area of the grid cell</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><pre>array([[1.315942e+09, 1.315937e+09, 1.315942e+09, ..., 1.315931e+09,\n",
        "        1.315954e+09, 1.315931e+09],\n",
        "       [1.330202e+09, 1.330197e+09, 1.330202e+09, ..., 1.330191e+09,\n",
        "        1.330214e+09, 1.330191e+09],\n",
@@ -460,30 +454,33 @@
        "       [1.063687e+09, 1.063683e+09, 1.063687e+09, ..., 1.063678e+09,\n",
        "        1.063696e+09, 1.063678e+09],\n",
        "       [1.051047e+09, 1.051043e+09, 1.051047e+09, ..., 1.051038e+09,\n",
-       "        1.051056e+09, 1.051038e+09]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c9b1a17-f46b-40c7-a4ac-4a2b06277fbf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7c9b1a17-f46b-40c7-a4ac-4a2b06277fbf' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "        1.051056e+09, 1.051038e+09]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cba21d4b-eb0a-4b07-a136-13b8d9dd7948' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cba21d4b-eb0a-4b07-a136-13b8d9dd7948' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
-       "Dimensions:    (time: 1, y: 236, x: 210)\n",
+       "Dimensions:    (time: 1, y: 236, x: 210, nv: 4)\n",
        "Coordinates:\n",
        "  * time       (time) float64 0.0\n",
        "    lat        (y, x) float32 ...\n",
        "    lon        (y, x) float32 ...\n",
        "  * x          (x) float64 -1.01e+05 -5.101e+04 ... 1.03e+07 1.035e+07\n",
        "  * y          (y) float64 -5.382e+06 -5.332e+06 ... 6.318e+06 6.368e+06\n",
+       "Dimensions without coordinates: nv\n",
        "Data variables:\n",
+       "    lat_bnds   (y, x, nv) float32 ...\n",
+       "    lon_bnds   (y, x, nv) float32 ...\n",
        "    var_aux    (time, y, x) float32 ...\n",
        "    mercator   int32 ...\n",
        "    cell_area  (y, x) float32 ..."
       ]
      },
-     "execution_count": 4,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "xr.open_dataset('input/mercator_grid_example.nc', decode_times=False)"
+    "xr.open_dataset(nc_path_1, decode_times=False)"
    ]
   },
   {
@@ -495,28 +492,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<nes.nc_projections.mercator_nes.MercatorNes at 0x7fee9d34b150>"
+       "<nes.nc_projections.mercator_nes.MercatorNes at 0x7f903a903290>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "nessy_1 = open_netcdf(path='input/mercator_grid_example.nc', info=True)\n",
+    "nessy_1 = open_netcdf(nc_path_1, info=True)\n",
     "nessy_1"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -525,7 +522,7 @@
        "[datetime.datetime(2000, 1, 1, 0, 0)]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -536,7 +533,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -545,7 +542,7 @@
        "{'data': array([0]), 'units': ''}"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -556,7 +553,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -640,7 +637,7 @@
        " 'standard_name': 'projection_x_coordinate'}"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -651,7 +648,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -713,7 +710,7 @@
        " 'standard_name': 'projection_y_coordinate'}"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -724,7 +721,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -755,7 +752,7 @@
        " 'bounds': 'lat_bnds'}"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -766,7 +763,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -797,7 +794,7 @@
        " 'bounds': 'lon_bnds'}"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -806,10 +803,322 @@
     "nessy_1.lon"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "masked_array(\n",
+       "  data=[[[-43.68109893798828, -43.68109893798828, -43.354862213134766,\n",
+       "          -43.354862213134766],\n",
+       "         [-43.68109893798828, -43.68109893798828, -43.354862213134766,\n",
+       "          -43.354862213134766],\n",
+       "         [-43.68109893798828, -43.68109893798828, -43.354862213134766,\n",
+       "          -43.354862213134766],\n",
+       "         ...,\n",
+       "         [-43.68109893798828, -43.68109893798828, -43.354862213134766,\n",
+       "          -43.354862213134766],\n",
+       "         [-43.68109893798828, -43.68109893798828, -43.354862213134766,\n",
+       "          -43.354862213134766],\n",
+       "         [-43.68109893798828, -43.68109893798828, -43.354862213134766,\n",
+       "          -43.354862213134766]],\n",
+       "\n",
+       "        [[-43.354862213134766, -43.354862213134766, -43.02686309814453,\n",
+       "          -43.02686309814453],\n",
+       "         [-43.354862213134766, -43.354862213134766, -43.02686309814453,\n",
+       "          -43.02686309814453],\n",
+       "         [-43.354862213134766, -43.354862213134766, -43.02686309814453,\n",
+       "          -43.02686309814453],\n",
+       "         ...,\n",
+       "         [-43.354862213134766, -43.354862213134766, -43.02686309814453,\n",
+       "          -43.02686309814453],\n",
+       "         [-43.354862213134766, -43.354862213134766, -43.02686309814453,\n",
+       "          -43.02686309814453],\n",
+       "         [-43.354862213134766, -43.354862213134766, -43.02686309814453,\n",
+       "          -43.02686309814453]],\n",
+       "\n",
+       "        [[-43.02686309814453, -43.02686309814453, -42.69709777832031,\n",
+       "          -42.69709777832031],\n",
+       "         [-43.02686309814453, -43.02686309814453, -42.69709777832031,\n",
+       "          -42.69709777832031],\n",
+       "         [-43.02686309814453, -43.02686309814453, -42.69709777832031,\n",
+       "          -42.69709777832031],\n",
+       "         ...,\n",
+       "         [-43.02686309814453, -43.02686309814453, -42.69709777832031,\n",
+       "          -42.69709777832031],\n",
+       "         [-43.02686309814453, -43.02686309814453, -42.69709777832031,\n",
+       "          -42.69709777832031],\n",
+       "         [-43.02686309814453, -43.02686309814453, -42.69709777832031,\n",
+       "          -42.69709777832031]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[48.86896514892578, 48.86896514892578, 49.16401672363281,\n",
+       "          49.16401672363281],\n",
+       "         [48.86896514892578, 48.86896514892578, 49.16401672363281,\n",
+       "          49.16401672363281],\n",
+       "         [48.86896514892578, 48.86896514892578, 49.16401672363281,\n",
+       "          49.16401672363281],\n",
+       "         ...,\n",
+       "         [48.86896514892578, 48.86896514892578, 49.16401672363281,\n",
+       "          49.16401672363281],\n",
+       "         [48.86896514892578, 48.86896514892578, 49.16401672363281,\n",
+       "          49.16401672363281],\n",
+       "         [48.86896514892578, 48.86896514892578, 49.16401672363281,\n",
+       "          49.16401672363281]],\n",
+       "\n",
+       "        [[49.16401672363281, 49.16401672363281, 49.45732498168945,\n",
+       "          49.45732498168945],\n",
+       "         [49.16401672363281, 49.16401672363281, 49.45732498168945,\n",
+       "          49.45732498168945],\n",
+       "         [49.16401672363281, 49.16401672363281, 49.45732498168945,\n",
+       "          49.45732498168945],\n",
+       "         ...,\n",
+       "         [49.16401672363281, 49.16401672363281, 49.45732498168945,\n",
+       "          49.45732498168945],\n",
+       "         [49.16401672363281, 49.16401672363281, 49.45732498168945,\n",
+       "          49.45732498168945],\n",
+       "         [49.16401672363281, 49.16401672363281, 49.45732498168945,\n",
+       "          49.45732498168945]],\n",
+       "\n",
+       "        [[49.45732498168945, 49.45732498168945, 49.74888229370117,\n",
+       "          49.74888229370117],\n",
+       "         [49.45732498168945, 49.45732498168945, 49.74888229370117,\n",
+       "          49.74888229370117],\n",
+       "         [49.45732498168945, 49.45732498168945, 49.74888229370117,\n",
+       "          49.74888229370117],\n",
+       "         ...,\n",
+       "         [49.45732498168945, 49.45732498168945, 49.74888229370117,\n",
+       "          49.74888229370117],\n",
+       "         [49.45732498168945, 49.45732498168945, 49.74888229370117,\n",
+       "          49.74888229370117],\n",
+       "         [49.45732498168945, 49.45732498168945, 49.74888229370117,\n",
+       "          49.74888229370117]]],\n",
+       "  mask=[[[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]]],\n",
+       "  fill_value=1e+20,\n",
+       "  dtype=float32)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nessy_1.lat_bnds"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "masked_array(\n",
+       "  data=[[[-19.13384246826172, -18.683956146240234, -18.683956146240234,\n",
+       "          -19.13384246826172],\n",
+       "         [-18.683956146240234, -18.234071731567383, -18.234071731567383,\n",
+       "          -18.683956146240234],\n",
+       "         [-18.234071731567383, -17.7841854095459, -17.7841854095459,\n",
+       "          -18.234071731567383],\n",
+       "         ...,\n",
+       "         [73.99246978759766, 74.44235229492188, 74.44235229492188,\n",
+       "          73.99246978759766],\n",
+       "         [74.44235229492188, 74.89224243164062, 74.89224243164062,\n",
+       "          74.44235229492188],\n",
+       "         [74.89224243164062, 75.34212493896484, 75.34212493896484,\n",
+       "          74.89224243164062]],\n",
+       "\n",
+       "        [[-19.13384246826172, -18.683956146240234, -18.683956146240234,\n",
+       "          -19.13384246826172],\n",
+       "         [-18.683956146240234, -18.234071731567383, -18.234071731567383,\n",
+       "          -18.683956146240234],\n",
+       "         [-18.234071731567383, -17.7841854095459, -17.7841854095459,\n",
+       "          -18.234071731567383],\n",
+       "         ...,\n",
+       "         [73.99246978759766, 74.44235229492188, 74.44235229492188,\n",
+       "          73.99246978759766],\n",
+       "         [74.44235229492188, 74.89224243164062, 74.89224243164062,\n",
+       "          74.44235229492188],\n",
+       "         [74.89224243164062, 75.34212493896484, 75.34212493896484,\n",
+       "          74.89224243164062]],\n",
+       "\n",
+       "        [[-19.13384246826172, -18.683956146240234, -18.683956146240234,\n",
+       "          -19.13384246826172],\n",
+       "         [-18.683956146240234, -18.234071731567383, -18.234071731567383,\n",
+       "          -18.683956146240234],\n",
+       "         [-18.234071731567383, -17.7841854095459, -17.7841854095459,\n",
+       "          -18.234071731567383],\n",
+       "         ...,\n",
+       "         [73.99246978759766, 74.44235229492188, 74.44235229492188,\n",
+       "          73.99246978759766],\n",
+       "         [74.44235229492188, 74.89224243164062, 74.89224243164062,\n",
+       "          74.44235229492188],\n",
+       "         [74.89224243164062, 75.34212493896484, 75.34212493896484,\n",
+       "          74.89224243164062]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[-19.13384246826172, -18.683956146240234, -18.683956146240234,\n",
+       "          -19.13384246826172],\n",
+       "         [-18.683956146240234, -18.234071731567383, -18.234071731567383,\n",
+       "          -18.683956146240234],\n",
+       "         [-18.234071731567383, -17.7841854095459, -17.7841854095459,\n",
+       "          -18.234071731567383],\n",
+       "         ...,\n",
+       "         [73.99246978759766, 74.44235229492188, 74.44235229492188,\n",
+       "          73.99246978759766],\n",
+       "         [74.44235229492188, 74.89224243164062, 74.89224243164062,\n",
+       "          74.44235229492188],\n",
+       "         [74.89224243164062, 75.34212493896484, 75.34212493896484,\n",
+       "          74.89224243164062]],\n",
+       "\n",
+       "        [[-19.13384246826172, -18.683956146240234, -18.683956146240234,\n",
+       "          -19.13384246826172],\n",
+       "         [-18.683956146240234, -18.234071731567383, -18.234071731567383,\n",
+       "          -18.683956146240234],\n",
+       "         [-18.234071731567383, -17.7841854095459, -17.7841854095459,\n",
+       "          -18.234071731567383],\n",
+       "         ...,\n",
+       "         [73.99246978759766, 74.44235229492188, 74.44235229492188,\n",
+       "          73.99246978759766],\n",
+       "         [74.44235229492188, 74.89224243164062, 74.89224243164062,\n",
+       "          74.44235229492188],\n",
+       "         [74.89224243164062, 75.34212493896484, 75.34212493896484,\n",
+       "          74.89224243164062]],\n",
+       "\n",
+       "        [[-19.13384246826172, -18.683956146240234, -18.683956146240234,\n",
+       "          -19.13384246826172],\n",
+       "         [-18.683956146240234, -18.234071731567383, -18.234071731567383,\n",
+       "          -18.683956146240234],\n",
+       "         [-18.234071731567383, -17.7841854095459, -17.7841854095459,\n",
+       "          -18.234071731567383],\n",
+       "         ...,\n",
+       "         [73.99246978759766, 74.44235229492188, 74.44235229492188,\n",
+       "          73.99246978759766],\n",
+       "         [74.44235229492188, 74.89224243164062, 74.89224243164062,\n",
+       "          74.44235229492188],\n",
+       "         [74.89224243164062, 75.34212493896484, 75.34212493896484,\n",
+       "          74.89224243164062]]],\n",
+       "  mask=[[[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]],\n",
+       "\n",
+       "        [[False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         ...,\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False],\n",
+       "         [False, False, False, False]]],\n",
+       "  fill_value=1e+20,\n",
+       "  dtype=float32)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nessy_1.lon_bnds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -828,7 +1137,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -847,9 +1156,9 @@
        "    dtype=float32),\n",
        "  'dimensions': ('time', 'y', 'x'),\n",
        "  'units': '?',\n",
+       "  'coordinates': 'lat lon',\n",
        "  'cell_measures': 'area: cell_area',\n",
-       "  'grid_mapping': 'mercator',\n",
-       "  'coordinates': 'lat lon'},\n",
+       "  'grid_mapping': 'mercator'},\n",
        " 'cell_area': {'data': masked_array(\n",
        "    data=[[[[1.31594240e+09, 1.31593690e+09, 1.31594240e+09, ...,\n",
        "             1.31593126e+09, 1.31595354e+09, 1.31593126e+09],\n",
@@ -870,11 +1179,10 @@
        "  'dimensions': ('y', 'x'),\n",
        "  'long_name': 'area of the grid cell',\n",
        "  'standard_name': 'cell_area',\n",
-       "  'units': 'm2',\n",
-       "  'coordinates': 'lat lon'}}"
+       "  'units': 'm2'}}"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -885,7 +1193,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -894,6 +1202,91 @@
      "text": [
       "Rank 000: Creating mercator_file_1.nc\n",
       "Rank 000: NetCDF ready to write\n",
+      "[[[-43.68109893798828 -43.68109893798828 -43.354862213134766\n",
+      "   -43.354862213134766]\n",
+      "  [-43.68109893798828 -43.68109893798828 -43.354862213134766\n",
+      "   -43.354862213134766]\n",
+      "  [-43.68109893798828 -43.68109893798828 -43.354862213134766\n",
+      "   -43.354862213134766]\n",
+      "  ...\n",
+      "  [-43.68109893798828 -43.68109893798828 -43.354862213134766\n",
+      "   -43.354862213134766]\n",
+      "  [-43.68109893798828 -43.68109893798828 -43.354862213134766\n",
+      "   -43.354862213134766]\n",
+      "  [-43.68109893798828 -43.68109893798828 -43.354862213134766\n",
+      "   -43.354862213134766]]\n",
+      "\n",
+      " [[-43.354862213134766 -43.354862213134766 -43.02686309814453\n",
+      "   -43.02686309814453]\n",
+      "  [-43.354862213134766 -43.354862213134766 -43.02686309814453\n",
+      "   -43.02686309814453]\n",
+      "  [-43.354862213134766 -43.354862213134766 -43.02686309814453\n",
+      "   -43.02686309814453]\n",
+      "  ...\n",
+      "  [-43.354862213134766 -43.354862213134766 -43.02686309814453\n",
+      "   -43.02686309814453]\n",
+      "  [-43.354862213134766 -43.354862213134766 -43.02686309814453\n",
+      "   -43.02686309814453]\n",
+      "  [-43.354862213134766 -43.354862213134766 -43.02686309814453\n",
+      "   -43.02686309814453]]\n",
+      "\n",
+      " [[-43.02686309814453 -43.02686309814453 -42.69709777832031\n",
+      "   -42.69709777832031]\n",
+      "  [-43.02686309814453 -43.02686309814453 -42.69709777832031\n",
+      "   -42.69709777832031]\n",
+      "  [-43.02686309814453 -43.02686309814453 -42.69709777832031\n",
+      "   -42.69709777832031]\n",
+      "  ...\n",
+      "  [-43.02686309814453 -43.02686309814453 -42.69709777832031\n",
+      "   -42.69709777832031]\n",
+      "  [-43.02686309814453 -43.02686309814453 -42.69709777832031\n",
+      "   -42.69709777832031]\n",
+      "  [-43.02686309814453 -43.02686309814453 -42.69709777832031\n",
+      "   -42.69709777832031]]\n",
+      "\n",
+      " ...\n",
+      "\n",
+      " [[48.86896514892578 48.86896514892578 49.16401672363281\n",
+      "   49.16401672363281]\n",
+      "  [48.86896514892578 48.86896514892578 49.16401672363281\n",
+      "   49.16401672363281]\n",
+      "  [48.86896514892578 48.86896514892578 49.16401672363281\n",
+      "   49.16401672363281]\n",
+      "  ...\n",
+      "  [48.86896514892578 48.86896514892578 49.16401672363281\n",
+      "   49.16401672363281]\n",
+      "  [48.86896514892578 48.86896514892578 49.16401672363281\n",
+      "   49.16401672363281]\n",
+      "  [48.86896514892578 48.86896514892578 49.16401672363281\n",
+      "   49.16401672363281]]\n",
+      "\n",
+      " [[49.16401672363281 49.16401672363281 49.45732498168945\n",
+      "   49.45732498168945]\n",
+      "  [49.16401672363281 49.16401672363281 49.45732498168945\n",
+      "   49.45732498168945]\n",
+      "  [49.16401672363281 49.16401672363281 49.45732498168945\n",
+      "   49.45732498168945]\n",
+      "  ...\n",
+      "  [49.16401672363281 49.16401672363281 49.45732498168945\n",
+      "   49.45732498168945]\n",
+      "  [49.16401672363281 49.16401672363281 49.45732498168945\n",
+      "   49.45732498168945]\n",
+      "  [49.16401672363281 49.16401672363281 49.45732498168945\n",
+      "   49.45732498168945]]\n",
+      "\n",
+      " [[49.45732498168945 49.45732498168945 49.74888229370117\n",
+      "   49.74888229370117]\n",
+      "  [49.45732498168945 49.45732498168945 49.74888229370117\n",
+      "   49.74888229370117]\n",
+      "  [49.45732498168945 49.45732498168945 49.74888229370117\n",
+      "   49.74888229370117]\n",
+      "  ...\n",
+      "  [49.45732498168945 49.45732498168945 49.74888229370117\n",
+      "   49.74888229370117]\n",
+      "  [49.45732498168945 49.45732498168945 49.74888229370117\n",
+      "   49.74888229370117]\n",
+      "  [49.45732498168945 49.45732498168945 49.74888229370117\n",
+      "   49.74888229370117]]]\n",
       "Rank 000: Dimensions done\n",
       "Rank 000: Writing var_aux var (1/2)\n",
       "Rank 000: Var var_aux created (1/2)\n",
@@ -921,16 +1314,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<nes.nc_projections.mercator_nes.MercatorNes at 0x7fee9d2f3d10>"
+       "<nes.nc_projections.mercator_nes.MercatorNes at 0x7f903a91ff90>"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -949,7 +1342,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -1307,7 +1700,7 @@
        "  fill: currentColor;\n",
        "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:    (time: 1, lev: 1, y: 236, x: 210)\n",
+       "Dimensions:    (time: 1, lev: 1, y: 236, x: 210, spatial_nv: 4)\n",
        "Coordinates:\n",
        "  * time       (time) datetime64[ns] 2000-01-01\n",
        "  * lev        (lev) float64 0.0\n",
@@ -1315,12 +1708,15 @@
        "    lon        (y, x) float64 -18.91 -18.46 -18.01 -17.56 ... 74.22 74.67 75.12\n",
        "  * y          (y) float64 -5.382e+06 -5.332e+06 ... 6.318e+06 6.368e+06\n",
        "  * x          (x) float64 -1.01e+05 -5.101e+04 ... 1.03e+07 1.035e+07\n",
+       "Dimensions without coordinates: spatial_nv\n",
        "Data variables:\n",
+       "    lat_bnds   (y, x, spatial_nv) float64 ...\n",
+       "    lon_bnds   (y, x, spatial_nv) float64 ...\n",
        "    var_aux    (time, lev, y, x) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
        "    cell_area  (time, lev, y, x) float32 1.316e+09 1.316e+09 ... 1.051e+09\n",
        "    mercator   |S1 b&#x27;&#x27;\n",
        "Attributes:\n",
-       "    Conventions:  CF-1.7</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-930558a9-4800-4218-95a8-b7f21d7496e4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-930558a9-4800-4218-95a8-b7f21d7496e4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>lev</span>: 1</li><li><span class='xr-has-index'>y</span>: 236</li><li><span class='xr-has-index'>x</span>: 210</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-788068e1-2a20-468a-bdc8-683e04756a3e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-788068e1-2a20-468a-bdc8-683e04756a3e' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01</div><input id='attrs-2c72287b-dcfd-4253-8e3e-72ba1095a0d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c72287b-dcfd-4253-8e3e-72ba1095a0d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf0f0117-2e93-4422-b433-173802947606' class='xr-var-data-in' type='checkbox'><label for='data-bf0f0117-2e93-4422-b433-173802947606' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-710ad37f-aa16-4a8a-a223-ced15443b518' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-710ad37f-aa16-4a8a-a223-ced15443b518' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bea3f9d7-bbe5-4e3d-9bcf-4a4e162f55d1' class='xr-var-data-in' type='checkbox'><label for='data-bea3f9d7-bbe5-4e3d-9bcf-4a4e162f55d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3f72dcff-95f3-4619-9135-1830a2927511' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f72dcff-95f3-4619-9135-1830a2927511' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97ae6681-da5e-4732-91a4-113484e506e1' class='xr-var-data-in' type='checkbox'><label for='data-97ae6681-da5e-4732-91a4-113484e506e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([[-43.5182  , -43.5182  , -43.5182  , ..., -43.5182  , -43.5182  ,\n",
+       "    Conventions:  CF-1.7</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-156da7b7-d4a9-4914-98a3-855175717c39' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-156da7b7-d4a9-4914-98a3-855175717c39' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>lev</span>: 1</li><li><span class='xr-has-index'>y</span>: 236</li><li><span class='xr-has-index'>x</span>: 210</li><li><span>spatial_nv</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f09bf330-3a3e-4ae7-842d-40b669c92d96' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f09bf330-3a3e-4ae7-842d-40b669c92d96' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01</div><input id='attrs-654fdba4-04a6-4cf3-a5e6-b399597c9194' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-654fdba4-04a6-4cf3-a5e6-b399597c9194' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adf4a7ef-9ed4-4cd6-ba59-e9e7f9bf4645' class='xr-var-data-in' type='checkbox'><label for='data-adf4a7ef-9ed4-4cd6-ba59-e9e7f9bf4645' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-59d9018c-ced2-4487-9223-4b35440d5a18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59d9018c-ced2-4487-9223-4b35440d5a18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1462996d-fb20-450d-acbb-584cfd31c665' class='xr-var-data-in' type='checkbox'><label for='data-1462996d-fb20-450d-acbb-584cfd31c665' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f0fd2b79-8c89-4080-9b98-62d387c351ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0fd2b79-8c89-4080-9b98-62d387c351ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c37b0dcb-f637-46ac-a19a-f4f4bdd33271' class='xr-var-data-in' type='checkbox'><label for='data-c37b0dcb-f637-46ac-a19a-f4f4bdd33271' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([[-43.5182  , -43.5182  , -43.5182  , ..., -43.5182  , -43.5182  ,\n",
        "        -43.5182  ],\n",
        "       [-43.191082, -43.191082, -43.191082, ..., -43.191082, -43.191082,\n",
        "        -43.191082],\n",
@@ -1332,7 +1728,7 @@
        "       [ 49.31089 ,  49.31089 ,  49.31089 , ...,  49.31089 ,  49.31089 ,\n",
        "         49.31089 ],\n",
        "       [ 49.603321,  49.603321,  49.603321, ...,  49.603321,  49.603321,\n",
-       "         49.603321]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0d37d386-ccfe-4389-8f2c-e1996edd9862' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d37d386-ccfe-4389-8f2c-e1996edd9862' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d812ff40-0af5-4b83-840d-be52e1880933' class='xr-var-data-in' type='checkbox'><label for='data-d812ff40-0af5-4b83-840d-be52e1880933' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([[-18.908899, -18.459013, -18.009129, ...,  74.217415,  74.667297,\n",
+       "         49.603321]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2f522c2e-dc51-4599-a942-7ee1fda327db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f522c2e-dc51-4599-a942-7ee1fda327db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fcdeabc-a218-4358-866b-57556737cc86' class='xr-var-data-in' type='checkbox'><label for='data-9fcdeabc-a218-4358-866b-57556737cc86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([[-18.908899, -18.459013, -18.009129, ...,  74.217415,  74.667297,\n",
        "         75.11718 ],\n",
        "       [-18.908899, -18.459013, -18.009129, ...,  74.217415,  74.667297,\n",
        "         75.11718 ],\n",
@@ -1344,16 +1740,16 @@
        "       [-18.908899, -18.459013, -18.009129, ...,  74.217415,  74.667297,\n",
        "         75.11718 ],\n",
        "       [-18.908899, -18.459013, -18.009129, ...,  74.217415,  74.667297,\n",
-       "         75.11718 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.382e+06 -5.332e+06 ... 6.368e+06</div><input id='attrs-60e1cf0b-8cb1-4a23-a56a-c4675cf51367' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60e1cf0b-8cb1-4a23-a56a-c4675cf51367' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20bc90fe-172c-4995-94c1-c1b0717a8048' class='xr-var-data-in' type='checkbox'><label for='data-20bc90fe-172c-4995-94c1-c1b0717a8048' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>units :</span></dt><dd>1000 m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-5382460., -5332460., -5282460., ...,  6267540.,  6317540.,  6367540.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.01e+05 -5.101e+04 ... 1.035e+07</div><input id='attrs-b2dbfa7c-bc48-4284-a250-5eae61b8d666' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2dbfa7c-bc48-4284-a250-5eae61b8d666' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-275b2482-b303-4653-9cf9-3afad33dfd30' class='xr-var-data-in' type='checkbox'><label for='data-275b2482-b303-4653-9cf9-3afad33dfd30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>units :</span></dt><dd>1000 m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-1.010145e+05, -5.101450e+04, -1.014500e+03, ...,  1.024899e+07,\n",
-       "        1.029899e+07,  1.034899e+07])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5e0ca027-4c07-4673-8f97-0bd19ac63127' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5e0ca027-4c07-4673-8f97-0bd19ac63127' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>var_aux</span></div><div class='xr-var-dims'>(time, lev, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c7be928a-3e52-40c9-bf67-2e2aabafdb26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7be928a-3e52-40c9-bf67-2e2aabafdb26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74e324fc-208a-4ba4-8e85-b379bdbe4533' class='xr-var-data-in' type='checkbox'><label for='data-74e324fc-208a-4ba4-8e85-b379bdbe4533' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>?</dd><dt><span>cell_measures :</span></dt><dd>area: cell_area</dd><dt><span>grid_mapping :</span></dt><dd>mercator</dd></dl></div><div class='xr-var-data'><pre>array([[[[0., ..., 0.],\n",
+       "         75.11718 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.382e+06 -5.332e+06 ... 6.368e+06</div><input id='attrs-25f66490-a24e-4b6e-bd73-9514566b65c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25f66490-a24e-4b6e-bd73-9514566b65c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b313520d-875b-4ad9-9189-89346bcd88d7' class='xr-var-data-in' type='checkbox'><label for='data-b313520d-875b-4ad9-9189-89346bcd88d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>units :</span></dt><dd>1000 m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-5382460., -5332460., -5282460., ...,  6267540.,  6317540.,  6367540.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.01e+05 -5.101e+04 ... 1.035e+07</div><input id='attrs-7f96a150-451f-46f7-9cc7-2ba6c9da3503' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f96a150-451f-46f7-9cc7-2ba6c9da3503' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d250a763-059c-4e14-84c2-84070aa8aa90' class='xr-var-data-in' type='checkbox'><label for='data-d250a763-059c-4e14-84c2-84070aa8aa90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>units :</span></dt><dd>1000 m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-1.010145e+05, -5.101450e+04, -1.014500e+03, ...,  1.024899e+07,\n",
+       "        1.029899e+07,  1.034899e+07])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3f990805-360a-4a25-8431-8112e173787d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3f990805-360a-4a25-8431-8112e173787d' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(y, x, spatial_nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ace76f2c-4517-4fad-812c-950609089c97' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ace76f2c-4517-4fad-812c-950609089c97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6daf0a86-0590-4de2-b055-66ab7ede46dc' class='xr-var-data-in' type='checkbox'><label for='data-6daf0a86-0590-4de2-b055-66ab7ede46dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[198240 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(y, x, spatial_nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-55924ff8-8818-4d7b-be22-e8e25252f8c0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55924ff8-8818-4d7b-be22-e8e25252f8c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a55bc6cc-0881-44d1-a4ce-6552c796c458' class='xr-var-data-in' type='checkbox'><label for='data-a55bc6cc-0881-44d1-a4ce-6552c796c458' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[198240 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>var_aux</span></div><div class='xr-var-dims'>(time, lev, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c7065aa-071c-40aa-8ebe-3d000db45b0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c7065aa-071c-40aa-8ebe-3d000db45b0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9e4de69-4f6f-471e-ac3c-4c7a8c4f4f79' class='xr-var-data-in' type='checkbox'><label for='data-f9e4de69-4f6f-471e-ac3c-4c7a8c4f4f79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>?</dd><dt><span>cell_measures :</span></dt><dd>area: cell_area</dd><dt><span>grid_mapping :</span></dt><dd>mercator</dd></dl></div><div class='xr-var-data'><pre>array([[[[0., ..., 0.],\n",
        "         ...,\n",
-       "         [0., ..., 0.]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cell_area</span></div><div class='xr-var-dims'>(time, lev, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4aade0f4-0d7b-49c6-8353-ec88999b8eb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4aade0f4-0d7b-49c6-8353-ec88999b8eb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6baa710-5c3f-4e3d-b03a-a9c19171d3e2' class='xr-var-data-in' type='checkbox'><label for='data-e6baa710-5c3f-4e3d-b03a-a9c19171d3e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>area of the grid cell</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>grid_mapping :</span></dt><dd>mercator</dd></dl></div><div class='xr-var-data'><pre>array([[[[1.315942e+09, ..., 1.315931e+09],\n",
+       "         [0., ..., 0.]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cell_area</span></div><div class='xr-var-dims'>(time, lev, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-06367769-29e3-454e-aab8-10b5a7fb6466' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06367769-29e3-454e-aab8-10b5a7fb6466' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c184663-aee0-46e5-acfa-420b17f7b7ad' class='xr-var-data-in' type='checkbox'><label for='data-6c184663-aee0-46e5-acfa-420b17f7b7ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>area of the grid cell</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>grid_mapping :</span></dt><dd>mercator</dd></dl></div><div class='xr-var-data'><pre>array([[[[1.315942e+09, ..., 1.315931e+09],\n",
        "         ...,\n",
-       "         [1.051047e+09, ..., 1.051038e+09]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mercator</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8ded48df-415d-4dd0-aeba-d41da7875484' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ded48df-415d-4dd0-aeba-d41da7875484' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7267bf1b-515f-4c5e-9e84-82525a1cb45e' class='xr-var-data-in' type='checkbox'><label for='data-7267bf1b-515f-4c5e-9e84-82525a1cb45e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping_name :</span></dt><dd>mercator</dd><dt><span>standard_parallel :</span></dt><dd>-1.5</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>-18.0</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;&#x27;, dtype=&#x27;|S1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ddd8644a-64b9-4752-8974-b07a37a1ac7d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ddd8644a-64b9-4752-8974-b07a37a1ac7d' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd></dl></div></li></ul></div></div>"
+       "         [1.051047e+09, ..., 1.051038e+09]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mercator</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2b21859f-e902-4dda-a0da-d11cd44a502a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b21859f-e902-4dda-a0da-d11cd44a502a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d00763a3-f790-4e17-a15c-3be2d99377d6' class='xr-var-data-in' type='checkbox'><label for='data-d00763a3-f790-4e17-a15c-3be2d99377d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping_name :</span></dt><dd>mercator</dd><dt><span>standard_parallel :</span></dt><dd>-1.5</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>-18.0</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;&#x27;, dtype=&#x27;|S1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4bc0cef5-87c2-4e8c-99f9-b96b3694c708' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4bc0cef5-87c2-4e8c-99f9-b96b3694c708' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
-       "Dimensions:    (time: 1, lev: 1, y: 236, x: 210)\n",
+       "Dimensions:    (time: 1, lev: 1, y: 236, x: 210, spatial_nv: 4)\n",
        "Coordinates:\n",
        "  * time       (time) datetime64[ns] 2000-01-01\n",
        "  * lev        (lev) float64 0.0\n",
@@ -1361,7 +1757,10 @@
        "    lon        (y, x) float64 ...\n",
        "  * y          (y) float64 -5.382e+06 -5.332e+06 ... 6.318e+06 6.368e+06\n",
        "  * x          (x) float64 -1.01e+05 -5.101e+04 ... 1.03e+07 1.035e+07\n",
+       "Dimensions without coordinates: spatial_nv\n",
        "Data variables:\n",
+       "    lat_bnds   (y, x, spatial_nv) float64 ...\n",
+       "    lon_bnds   (y, x, spatial_nv) float64 ...\n",
        "    var_aux    (time, lev, y, x) float32 ...\n",
        "    cell_area  (time, lev, y, x) float32 ...\n",
        "    mercator   |S1 ...\n",
@@ -1369,7 +1768,7 @@
        "    Conventions:  CF-1.7"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/tutorials/4.Interpolation/4.3.Providentia_Interpolation.ipynb b/tutorials/4.Interpolation/4.3.Providentia_Interpolation.ipynb
index 070e36d09d51b21e085e8674daf519251d7d73db..683bba0e3fa998b0e1387d5db139897624dd597b 100644
--- a/tutorials/4.Interpolation/4.3.Providentia_Interpolation.ipynb
+++ b/tutorials/4.Interpolation/4.3.Providentia_Interpolation.ipynb
@@ -422,7 +422,9 @@
    "source": [
     "interpolated_source_grid = source_grid.interpolate_horizontal(dst_grid, weight_matrix_path=None, \n",
     "                                                              kind='NearestNeighbour', n_neighbours=4,\n",
-    "                                                              info=True, to_providentia=True)"
+    "                                                              info=True, to_providentia=True)\n",
+    "# Bilinear to use n_neighbours (weighted average)\n",
+    "# n_neighbours = 1 for kind='NearestNeighbour'"
    ]
   },
   {
diff --git a/tutorials/5.Others/5.1.Add_Time_Bounds.ipynb b/tutorials/5.Others/5.1.Add_Time_Bounds.ipynb
index 9c08016b91387c8db5d3efaeef8d56d2edbd04be..1ed4e2f29a02d9a7b08cc645a9cb39a2d8606e5a 100644
--- a/tutorials/5.Others/5.1.Add_Time_Bounds.ipynb
+++ b/tutorials/5.Others/5.1.Add_Time_Bounds.ipynb
@@ -40,24 +40,11 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[datetime.datetime(2020, 2, 20, 0, 0),\n",
-       "        datetime.datetime(2020, 2, 15, 0, 0)]], dtype=object)"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "array = np.array([[datetime.datetime(year=2020, month=2, day=20), \n",
     "                   datetime.datetime(year=2020, month=2, day=15)]])\n",
-    "nessy.set_time_bnds(array)\n",
-    "nessy.time_bnds"
+    "nessy.set_time_bnds(array)"
    ]
   },
   {
@@ -78,15 +65,6 @@
     "nessy.load()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "nessy.to_netcdf('nc_serial_test.nc')"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/tutorials/5.Others/5.2.Add_Coordinates_Bounds.ipynb b/tutorials/5.Others/5.2.Add_Coordinates_Bounds.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..5b70186d28465713d58c475f85af2e62e4a51f77
--- /dev/null
+++ b/tutorials/5.Others/5.2.Add_Coordinates_Bounds.ipynb
@@ -0,0 +1,250 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# How to add time bounds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import datetime\n",
+    "import numpy as np\n",
+    "from nes import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. Set time bounds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_path = \"/gpfs/scratch/bsc32/bsc32538/mr_multiplyby/OUT/stats_bnds/monarch/a45g/regional/daily_max/O3_all/O3_all-000_2021080300.nc\"\n",
+    "nessy = open_netcdf(path=test_path, info=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inc_lat = np.abs(np.mean(np.diff(nessy.lat['data'])))\n",
+    "lat_bnds = nessy.create_bounds(nessy.lat['data'], inc_lat, spatial_nv=4)\n",
+    "nessy.set_lat_bnds(lat_bnds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inc_lon = np.abs(np.mean(np.diff(nessy.lon['data'])))\n",
+    "lon_bnds = nessy.create_bounds(nessy.lon['data'], inc_lon, spatial_nv=4)\n",
+    "nessy.set_lon_bnds(lon_bnds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Rank 000: Loading O3_all var (1/1)\n",
+      "Rank 000: Loaded O3_all var ((1, 24, 271, 351))\n"
+     ]
+    }
+   ],
+   "source": [
+    "nessy.load()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Explore variables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "masked_array(\n",
+       "  data=[[[16.35033798, 16.35033798, 16.35033798, 16.35033798],\n",
+       "         [16.43292999, 16.43292999, 16.43292999, 16.43292999],\n",
+       "         [16.51514626, 16.51514626, 16.51514626, 16.51514626],\n",
+       "         ...,\n",
+       "         [16.51514626, 16.51514626, 16.51514626, 16.51514626],\n",
+       "         [16.43292999, 16.43292999, 16.43292999, 16.43292999],\n",
+       "         [16.35033798, 16.35033798, 16.35033798, 16.35033798]],\n",
+       "\n",
+       "        [[16.52742577, 16.52742577, 16.52742577, 16.52742577],\n",
+       "         [16.61023903, 16.61023903, 16.61023903, 16.61023903],\n",
+       "         [16.69267654, 16.69267654, 16.69267654, 16.69267654],\n",
+       "         ...,\n",
+       "         [16.69267654, 16.69267654, 16.69267654, 16.69267654],\n",
+       "         [16.61024284, 16.61024284, 16.61024284, 16.61024284],\n",
+       "         [16.52742577, 16.52742577, 16.52742577, 16.52742577]],\n",
+       "\n",
+       "        [[16.70447159, 16.70447159, 16.70447159, 16.70447159],\n",
+       "         [16.78750801, 16.78750801, 16.78750801, 16.78750801],\n",
+       "         [16.87016678, 16.87016678, 16.87016678, 16.87016678],\n",
+       "         ...,\n",
+       "         [16.87016678, 16.87016678, 16.87016678, 16.87016678],\n",
+       "         [16.78750992, 16.78750992, 16.78750992, 16.78750992],\n",
+       "         [16.70447159, 16.70447159, 16.70447159, 16.70447159]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[58.32094955, 58.32094955, 58.32094955, 58.32094955],\n",
+       "         [58.47268295, 58.47268295, 58.47268295, 58.47268295],\n",
+       "         [58.62430954, 58.62430954, 58.62430954, 58.62430954],\n",
+       "         ...,\n",
+       "         [58.62430954, 58.62430954, 58.62430954, 58.62430954],\n",
+       "         [58.47268295, 58.47268295, 58.47268295, 58.47268295],\n",
+       "         [58.32094955, 58.32094955, 58.32094955, 58.32094955]],\n",
+       "\n",
+       "        [[58.42628479, 58.42628479, 58.42628479, 58.42628479],\n",
+       "         [58.57820129, 58.57820129, 58.57820129, 58.57820129],\n",
+       "         [58.73002625, 58.73002625, 58.73002625, 58.73002625],\n",
+       "         ...,\n",
+       "         [58.73002625, 58.73002625, 58.73002625, 58.73002625],\n",
+       "         [58.57820129, 58.57820129, 58.57820129, 58.57820129],\n",
+       "         [58.42628479, 58.42628479, 58.42628479, 58.42628479]],\n",
+       "\n",
+       "        [[58.53079224, 58.53079224, 58.53079224, 58.53079224],\n",
+       "         [58.68289948, 58.68289948, 58.68289948, 58.68289948],\n",
+       "         [58.83491898, 58.83491898, 58.83491898, 58.83491898],\n",
+       "         ...,\n",
+       "         [58.83491898, 58.83491898, 58.83491898, 58.83491898],\n",
+       "         [58.68290329, 58.68290329, 58.68290329, 58.68290329],\n",
+       "         [58.53079224, 58.53079224, 58.53079224, 58.53079224]]],\n",
+       "  mask=False,\n",
+       "  fill_value=1e+20)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nessy.lat_bnds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "masked_array(\n",
+       "  data=[[[-22.32515679, -22.03737297, -22.03737297, -22.32515679],\n",
+       "         [-22.16056404, -21.87278023, -21.87278023, -22.16056404],\n",
+       "         [-21.99569092, -21.7079071 , -21.7079071 , -21.99569092],\n",
+       "         ...,\n",
+       "         [ 41.70790329,  41.99568711,  41.99568711,  41.70790329],\n",
+       "         [ 41.8727745 ,  42.16055832,  42.16055832,  41.8727745 ],\n",
+       "         [ 42.03736725,  42.32515106,  42.32515106,  42.03736725]],\n",
+       "\n",
+       "        [[-22.42207108, -22.13428726, -22.13428726, -22.42207108],\n",
+       "         [-22.25707779, -21.96929397, -21.96929397, -22.25707779],\n",
+       "         [-22.0917965 , -21.80401268, -21.80401268, -22.0917965 ],\n",
+       "         ...,\n",
+       "         [ 41.80400696,  42.09179077,  42.09179077,  41.80400696],\n",
+       "         [ 41.96928253,  42.25706635,  42.25706635,  41.96928253],\n",
+       "         [ 42.13427963,  42.42206345,  42.42206345,  42.13427963]],\n",
+       "\n",
+       "        [[-22.51915894, -22.23137512, -22.23137512, -22.51915894],\n",
+       "         [-22.35376511, -22.06598129, -22.06598129, -22.35376511],\n",
+       "         [-22.18808136, -21.90029754, -21.90029754, -22.18808136],\n",
+       "         ...,\n",
+       "         [ 41.90029373,  42.18807755,  42.18807755,  41.90029373],\n",
+       "         [ 42.06598129,  42.35376511,  42.35376511,  42.06598129],\n",
+       "         [ 42.23137131,  42.51915512,  42.51915512,  42.23137131]],\n",
+       "\n",
+       "        ...,\n",
+       "\n",
+       "        [[-67.72155914, -67.43377533, -67.43377533, -67.72155914],\n",
+       "         [-67.54095612, -67.2531723 , -67.2531723 , -67.54095612],\n",
+       "         [-67.3592392 , -67.07145538, -67.07145538, -67.3592392 ],\n",
+       "         ...,\n",
+       "         [ 87.07144775,  87.35923157,  87.35923157,  87.07144775],\n",
+       "         [ 87.25316467,  87.54094849,  87.54094849,  87.25316467],\n",
+       "         [ 87.4337677 ,  87.72155152,  87.72155152,  87.4337677 ]],\n",
+       "\n",
+       "        [[-68.04577027, -67.75798645, -67.75798645, -68.04577027],\n",
+       "         [-67.86636505, -67.57858124, -67.57858124, -67.86636505],\n",
+       "         [-67.68583069, -67.39804687, -67.39804687, -67.68583069],\n",
+       "         ...,\n",
+       "         [ 87.39804687,  87.68583069,  87.68583069,  87.39804687],\n",
+       "         [ 87.57856598,  87.86634979,  87.86634979,  87.57856598],\n",
+       "         [ 87.75797882,  88.04576264,  88.04576264,  87.75797882]],\n",
+       "\n",
+       "        [[-68.37192688, -68.08414306, -68.08414306, -68.37192688],\n",
+       "         [-68.19371185, -67.90592804, -67.90592804, -68.19371185],\n",
+       "         [-68.01440582, -67.72662201, -67.72662201, -68.01440582],\n",
+       "         ...,\n",
+       "         [ 87.72661438,  88.0143982 ,  88.0143982 ,  87.72661438],\n",
+       "         [ 87.90592804,  88.19371185,  88.19371185,  87.90592804],\n",
+       "         [ 88.08414306,  88.37192688,  88.37192688,  88.08414306]]],\n",
+       "  mask=False,\n",
+       "  fill_value=1e+20)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nessy.lon_bnds"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}