Added whatsnew notes on netcdf delayed saving and Distributed support. (#5322)

* Added whatsnew notes on netcdf delayed saving and Distributed support.

* Fix formatting.

* --amend

Review change.

* Fix formatting.

Author: pp-mo

docs/src/whatsnew/3.6.rst

@@ -8,28 +8,51 @@ This document explains the changes made to Iris for this release
 
 
 .. dropdown:: v3.6 Release Highlights
-   :color: primary
-   :icon: info
-   :animate: fade-in
-   :open:
-
-   We're so excited about our recent support for **delayed saving of lazy data
-   to netCDF** (:pull:`5191`) that we're celebrating this important step change
-   in behavour with its very own dedicated release 🥳
-
-   We're super keen for the community to leverage the benefit of this new
-   feature within Iris that we've brought this release forward several months.
-   As a result, this minor release of Iris is intentionally light in content.
-   However, there are some other goodies available for you to enjoy, such as:
-
-   * Performing lazy arithmetic with an Iris :class:`~iris.cube.Cube` and a
-     :class:`dask.array.Array`, and
-   * Various improvements to our documentation resulting from adoption of
-     `sphinx-design`_ and `sphinx-apidoc`_.
-
-   As always, get in touch with us on :issue:`GitHub<new/choose>`, particularly
-   if you have any feedback with regards to delayed saving, or have any issues
-   or feature requests for improving Iris. Enjoy!
+    :color: primary
+    :icon: info
+    :animate: fade-in
+    :open:
+
+    We're so excited about our recent support for **delayed saving of lazy data
+    to netCDF** (:pull:`5191`) that we're celebrating this important step change
+    in behavour with its very own dedicated release 🥳
+
+    By using ``iris.save(..., compute=False)`` you can now save to multiple netcdf files
+    in parallel.  See the new ``compute`` keyword in :func:`iris.fileformats.netcdf.save`.
+    This can share and re-use any common (lazy) result computations, and it makes much
+    better use of resources during any file-system waiting (i.e. it can use such periods to
+    progress the *other* saves).
+
+    Usage example::
+
+       # Create output files with delayed data saving.
+       delayeds = [
+           iris.save(cubes, filepath, compute=False)
+           for cubes, filepath in zip(output_cubesets, output_filepaths)
+       ]
+       # Complete saves in parallel.
+       dask.compute(*delayeds)
+
+    This advance also includes **another substantial benefit**, because netcdf saves can
+    now use a
+    `Dask.distributed scheduler <https://docs.dask.org/en/stable/scheduling.html>`_.
+    With `Distributed <https://distributed.dask.org/en/stable/>`_ you can parallelise the
+    saves across a whole cluster.  Whereas previously, the netcdf saving *only* worked with
+    a "threaded" scheduler, limiting it to a single CPU.
+
+    We're so super keen for the community to leverage the benefit of this new
+    feature within Iris that we've brought this release forward several months.
+    As a result, this minor release of Iris is intentionally light in content.
+    However, there are some other goodies available for you to enjoy, such as:
+
+    * Performing lazy arithmetic with an Iris :class:`~iris.cube.Cube` and a
+      :class:`dask.array.Array`, and
+    * Various improvements to our documentation resulting from adoption of
+      `sphinx-design`_ and `sphinx-apidoc`_.
+
+    As always, get in touch with us on :issue:`GitHub<new/choose>`, particularly
+    if you have any feedback with regards to delayed saving, or have any issues
+    or feature requests for improving Iris. Enjoy!
 
 
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