diff --git a/docs/user_guide/examples/explanation_kernelloop.md b/docs/user_guide/examples/explanation_kernelloop.md
index e415e3250..cfde89724 100644
--- a/docs/user_guide/examples/explanation_kernelloop.md
+++ b/docs/user_guide/examples/explanation_kernelloop.md
@@ -57,7 +57,6 @@ import parcels.tutorial
 
 # Load the CopernicusMarine data in the Agulhas region from the example_datasets
 ds_fields = parcels.tutorial.open_dataset("CopernicusMarine_data_for_Argo_tutorial/data")
-ds_fields.load()  # load the dataset into memory
 
 # Create an idealised wind field and add it to the dataset
 tdim, ydim, xdim = (len(ds_fields.time),len(ds_fields.latitude), len(ds_fields.longitude))
@@ -83,6 +82,9 @@ fieldset = parcels.FieldSet.from_sgrid_conventions(
         "Wind": ("UWind", "VWind")
     }
 )
+
+# Convert the FieldSet to windowed arrays for better performance
+fieldset = fieldset.to_windowed_arrays()
 ```
 
 Now we define a wind Kernel that uses a forward Euler method to apply the wind forcing. Note that we update the `particles.dx` and `particles.dy` variables, rather than `particles.x` and `particles.y` directly.
diff --git a/docs/user_guide/examples/tutorial_delaystart.ipynb b/docs/user_guide/examples/tutorial_delaystart.ipynb
index 6ec8bb296..d8dfa2ce3 100644
--- a/docs/user_guide/examples/tutorial_delaystart.ipynb
+++ b/docs/user_guide/examples/tutorial_delaystart.ipynb
@@ -56,12 +56,14 @@
     "ds_fields = parcels.tutorial.open_dataset(\n",
     "    \"CopernicusMarine_data_for_Argo_tutorial/data\"\n",
     ")\n",
-    "ds_fields.load()  # load the dataset into memory\n",
     "\n",
     "# Convert to SGRID-compliant dataset and create FieldSet\n",
     "fields = {\"U\": ds_fields[\"uo\"], \"V\": ds_fields[\"vo\"]}\n",
     "ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
-    "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)"
+    "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
+    "\n",
+    "# Convert the FieldSet to windowed arrays for better performance\n",
+    "fieldset = fieldset.to_windowed_arrays()"
    ]
   },
   {
@@ -398,7 +400,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Parcels:docs (3.14.6)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
diff --git a/docs/user_guide/examples/tutorial_diffusion.ipynb b/docs/user_guide/examples/tutorial_diffusion.ipynb
index 79fe4018c..b0314fbfb 100644
--- a/docs/user_guide/examples/tutorial_diffusion.ipynb
+++ b/docs/user_guide/examples/tutorial_diffusion.ipynb
@@ -472,8 +472,7 @@
     "# Load the CopernicusMarine data in the Agulhas region from the example_datasets\n",
     "ds_fields = parcels.tutorial.open_dataset(\n",
     "    \"CopernicusMarine_data_for_Argo_tutorial/data\"\n",
-    ").isel(depth=slice(0, 1))\n",
-    "ds_fields.load()  # load the dataset into memory"
+    ").isel(depth=slice(0, 1))"
    ]
   },
   {
@@ -528,7 +527,10 @@
     "ds_cell_areas[\"cell_areas\"] = ([\"lat\", \"lon\"], calc_cell_areas(ds_fields))\n",
     "fset2 = parcels.FieldSet.from_sgrid_conventions(ds_cell_areas)\n",
     "\n",
-    "fieldset += fset2"
+    "fieldset += fset2\n",
+    "\n",
+    "# Convert the FieldSet to windowed arrays for better performance\n",
+    "fieldset = fieldset.to_windowed_arrays()"
    ]
   },
   {
diff --git a/docs/user_guide/examples/tutorial_dt_integrators.ipynb b/docs/user_guide/examples/tutorial_dt_integrators.ipynb
index 9fe32fa76..9ca44604d 100644
--- a/docs/user_guide/examples/tutorial_dt_integrators.ipynb
+++ b/docs/user_guide/examples/tutorial_dt_integrators.ipynb
@@ -67,7 +67,6 @@
     "ds_fields = parcels.tutorial.open_dataset(\n",
     "    \"CopernicusMarine_data_for_Argo_tutorial/data\"\n",
     ")\n",
-    "ds_fields.load()  # load the dataset into memory\n",
     "\n",
     "OUTPUT_FOLDER = Path(\"output\")\n",
     "OUTPUT_FOLDER.mkdir(exist_ok=True)\n",
@@ -77,6 +76,9 @@
     "ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
     "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
     "\n",
+    "# Convert the FieldSet to windowed arrays for better performance\n",
+    "fieldset = fieldset.to_windowed_arrays()\n",
+    "\n",
     "# Check field resolution in time and space\n",
     "print(\n",
     "    f\"dt = {np.unique(np.diff(ds_fields.time.values).astype('timedelta64[h]'))} hours\"\n",
diff --git a/docs/user_guide/examples/tutorial_gsw_density.ipynb b/docs/user_guide/examples/tutorial_gsw_density.ipynb
index c94ce0549..2a2b267f5 100644
--- a/docs/user_guide/examples/tutorial_gsw_density.ipynb
+++ b/docs/user_guide/examples/tutorial_gsw_density.ipynb
@@ -43,9 +43,6 @@
     "    \"CopernicusMarine_data_for_Argo_tutorial/data\"\n",
     ")\n",
     "\n",
-    "# TODO check how we can get good performance without loading full dataset in memory\n",
-    "ds_fields.load()  # load the dataset into memory\n",
-    "\n",
     "# Convert to SGRID-compliant dataset and create FieldSet\n",
     "fields = {\n",
     "    \"U\": ds_fields[\"uo\"],\n",
@@ -54,7 +51,10 @@
     "    \"so\": ds_fields[\"so\"],\n",
     "}\n",
     "ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
-    "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)"
+    "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
+    "\n",
+    "# Convert the FieldSet to windowed arrays for better performance\n",
+    "fieldset = fieldset.to_windowed_arrays()"
    ]
   },
   {
diff --git a/docs/user_guide/examples/tutorial_manipulating_field_data.ipynb b/docs/user_guide/examples/tutorial_manipulating_field_data.ipynb
index a5f9dd104..e536de38b 100644
--- a/docs/user_guide/examples/tutorial_manipulating_field_data.ipynb
+++ b/docs/user_guide/examples/tutorial_manipulating_field_data.ipynb
@@ -49,7 +49,6 @@
     "ds_fields = parcels.tutorial.open_dataset(\n",
     "    \"CopernicusMarine_data_for_Argo_tutorial/data\"\n",
     ")\n",
-    "ds_fields.load()  # load the dataset into memory\n",
     "\n",
     "# Create an idealised wind field and add it to the dataset\n",
     "ydim, xdim = len(ds_fields.latitude), len(ds_fields.longitude)\n",
@@ -122,6 +121,9 @@
     "ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
     "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
     "\n",
+    "# Convert the FieldSet to windowed arrays for better performance\n",
+    "fieldset = fieldset.to_windowed_arrays()\n",
+    "\n",
     "npart = 10\n",
     "z = np.repeat(ds_fields.depth[0].values, npart)\n",
     "lons = np.repeat(32.2, npart)\n",
diff --git a/docs/user_guide/examples/tutorial_sampling.ipynb b/docs/user_guide/examples/tutorial_sampling.ipynb
index f80c49104..70752e5e8 100644
--- a/docs/user_guide/examples/tutorial_sampling.ipynb
+++ b/docs/user_guide/examples/tutorial_sampling.ipynb
@@ -60,12 +60,14 @@
     "ds_fields = parcels.tutorial.open_dataset(\n",
     "    \"CopernicusMarine_data_for_Argo_tutorial/data\"\n",
     ")\n",
-    "ds_fields.load()  # load the dataset into memory\n",
     "\n",
     "# Convert to SGRID-compliant dataset and create FieldSet\n",
     "fields = {\"U\": ds_fields[\"uo\"], \"V\": ds_fields[\"vo\"], \"thetao\": ds_fields[\"thetao\"]}\n",
     "ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
-    "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)"
+    "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
+    "\n",
+    "# Convert the FieldSet to windowed arrays for better performance\n",
+    "fieldset = fieldset.to_windowed_arrays()"
    ]
   },
   {
diff --git a/docs/user_guide/examples/tutorial_write_in_kernel.ipynb b/docs/user_guide/examples/tutorial_write_in_kernel.ipynb
index 4f6ea2ad6..ede2c0823 100644
--- a/docs/user_guide/examples/tutorial_write_in_kernel.ipynb
+++ b/docs/user_guide/examples/tutorial_write_in_kernel.ipynb
@@ -122,12 +122,12 @@
     "ds_fields = parcels.tutorial.open_dataset(\n",
     "    \"CopernicusMarine_data_for_Argo_tutorial/data\"\n",
     ")\n",
-    "ds_fields.load()  # load the dataset into memory\n",
     "\n",
     "# Convert to SGRID-compliant dataset and create FieldSet\n",
     "fields = {\"U\": ds_fields[\"uo\"], \"V\": ds_fields[\"vo\"]}\n",
     "ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
     "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
+    "fieldset = fieldset.to_windowed_arrays()\n",
     "\n",
     "pset = parcels.ParticleSet(fieldset=fieldset, x=[31, 32], y=[-32, -31], z=[1, 1])\n",
     "\n",
diff --git a/docs/user_guide/getting_started/tutorial_output.ipynb b/docs/user_guide/getting_started/tutorial_output.ipynb
index 1a0891cf2..e6444473d 100644
--- a/docs/user_guide/getting_started/tutorial_output.ipynb
+++ b/docs/user_guide/getting_started/tutorial_output.ipynb
@@ -58,12 +58,14 @@
     "ds_fields = parcels.tutorial.open_dataset(\n",
     "    \"CopernicusMarine_data_for_Argo_tutorial/data\"\n",
     ")\n",
-    "ds_fields.load()  # load the dataset into memory\n",
     "\n",
     "# Convert to SGRID-compliant dataset and create FieldSet\n",
     "fields = {\"U\": ds_fields[\"uo\"], \"V\": ds_fields[\"vo\"]}\n",
     "ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
-    "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)"
+    "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
+    "\n",
+    "# Convert the FieldSet to windowed arrays for better performance\n",
+    "fieldset = fieldset.to_windowed_arrays()"
    ]
   },
   {
diff --git a/docs/user_guide/getting_started/tutorial_quickstart.md b/docs/user_guide/getting_started/tutorial_quickstart.md
index 63196ab01..508ce6044 100644
--- a/docs/user_guide/getting_started/tutorial_quickstart.md
+++ b/docs/user_guide/getting_started/tutorial_quickstart.md
@@ -31,8 +31,6 @@ hydrodynamics fields in which the particles are tracked. Here we provide an exam
 
 ```{code-cell}
 ds_fields = parcels.tutorial.open_dataset("CopernicusMarine_data_for_Argo_tutorial/data")
-
-ds_fields.load()  # load the dataset into memory
 ds_fields
 ```
 
@@ -52,6 +50,15 @@ ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)
 fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)
 ```
 
+Now, in order to improve performance, we can convert the `parcels.FieldSet` to windowed arrays. This is especially useful for large datasets with many timeslices, as it allows Parcels to load only the necessary timeslices into memory during the simulation.
+
+#TODO add link to performance explanation notebook here.
+
+```{code-cell}
+# Convert the FieldSet to windowed arrays for better performance
+fieldset = fieldset.to_windowed_arrays()
+```
+
 You can inspect the `parcels.FieldSet` object with the `describe` method in order to see which `parcels.Field`s are included, and which grid and interpolation method is used for each field. This also gives information on the type of mesh and the time interval of the `parcels.FieldSet`:
 
 ```{code-cell}
diff --git a/tests/test_sigmagrids.py b/tests/test_sigmagrids.py
index ec05b81d0..fd37027a0 100644
--- a/tests/test_sigmagrids.py
+++ b/tests/test_sigmagrids.py
@@ -46,7 +46,6 @@ def test_conversion_3DCROCO():
 
 def test_advection_3DCROCO():
     ds_fields = parcels.tutorial.open_dataset("CROCOidealized_data/data")
-    ds_fields.load()
 
     fields = {
         "U": ds_fields["u"],
@@ -61,6 +60,7 @@ def test_advection_3DCROCO():
     ds_fset = parcels.convert.croco_to_sgrid(fields=fields, coords=ds_fields)
 
     fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)
+    fieldset = fieldset.to_windowed_arrays()
     fieldset.add_context("hc", ds_fields.hc.item())
 
     runtime = 10_000