Added whatsnew notes on netcdf delayed saving and Distributed support.

docs/src/whatsnew/3.6.rst

@@ -13,14 +13,37 @@ This document explains the changes made to Iris for this release
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-   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:
+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