Feature 9 release (#13)

* Per #9, testing menu addition of release notes * Per #9, add NSF to NCAR references, updated release notes, and modified dates in conf.py * Per #9, fixed typo in year * Replacing new doi links with zenodo links and rewording NSF NCAR language based on https://sundog.ucar.edu/page/7480#Interim-Guidance-on--11 * Per #9, updating release date * Corrected NSF NCAR reference * Per #9, reworded based on Jeremy's suggestions. * Per #9, fixing broken link and surrounding text * Per #9, attempting to fix 'no title' problem * Per #9, reformatting menu to resolve 'no title' problem * Per #9, moving release date forward to 4/22 * Per #9, modified Zenodo link reference * Added text with hyperlink formatting to zenodo record in MBL tutorial case. * Fixed typo for hyperlink in MBL.rst * Add U.S. in front of Nat'l Science Foundation Based on this guidance: https://sundog.ucar.edu/page/7480#Interim-Guidance-on--11 --------- Co-authored-by: Jeremy Sauer <[email protected]>
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diff --git a/README.md b/README.md
@@ -15,24 +15,24 @@ See the License for the specific language governing permissions and
 limitations under the License.
 
 # Description
-FastEddy® (FE) is a large-eddy simulation (LES) model developed by the Research Applications Laboratory (RAL) at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, USA. The fundamental premise of FastEddy model development is to leverage the accelerated and more power efficient computing capacity of graphics processing units (GPU)s to enable not only more widespread use of LES in research activities but also to pursue the adoption of microscale and multiscale, turbulence-resolving, atmospheric boundary layer modeling into local scale weather prediction or actionable science and engineering applications.
+FastEddy® (FE) is a large-eddy simulation (LES) model developed by the Research Applications Laboratory (RAL) at the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) in Boulder, Colorado, USA. The fundamental premise of FastEddy model development is to leverage the accelerated and more power efficient computing capacity of graphics processing units (GPU)s to enable not only more widespread use of LES in research activities but also to pursue the adoption of microscale and multiscale, turbulence-resolving, atmospheric boundary layer modeling into local scale weather prediction or actionable science and engineering applications.
 
 ## Contact
-Please submit all comments, feedback, suggestions, or questions by email to the NCAR FastEddy team at [[email protected]]([email protected]). Further information about FastEddy applications and research is available via the [RAL website](https://ral.ucar.edu/solutions/products/fasteddy). 
+Please submit all comments, feedback, suggestions, or questions by email to the NSF NCAR FastEddy team at [[email protected]]([email protected]). Further information about FastEddy applications and research is available via the [RAL website](https://ral.ucar.edu/solutions/products/fasteddy). 
 
 # Getting Started
-To get started using FastEddy on NCAR's Casper architecture simple instructions are provided below. These include a brief explanation of how to compile FastEddy, an example PBS job submission script, and a pointer to tutorial documentation for idealized test cases. Finally, reference publications for model formulation are provided.
+To get started using FastEddy on NSF NCAR's Casper architecture simple instructions are provided below. These include a brief explanation of how to compile FastEddy, an example PBS job submission script, and a pointer to tutorial documentation for idealized test cases. Finally, reference publications for model formulation are provided.
 
 ## Beta-build
-The Makefile-based build system included here assumes deployment on the NCAR Casper system https://arc.ucar.edu/knowledge_base/70549550. FastEddy requires a C-compiler, MPI, and CUDA. On Casper ensure modules are loaded for openmpi, netcdf, and cuda with module -t list, and e.g. module load [intel or gnu/openmpi/cuda] as necessary. Currently, the default modules of intel, openMPI, and CUDA are loaded at login and suffice.
+The Makefile-based build system included here assumes deployment on the NSF NCAR Casper system https://arc.ucar.edu/knowledge_base/70549550. FastEddy requires a C-compiler, MPI, and CUDA. On Casper ensure modules are loaded for openmpi, netcdf, and cuda with module -t list, and e.g. module load [intel or gnu/openmpi/cuda] as necessary. Currently, the default modules of intel, openMPI, and CUDA are loaded at login and suffice.
 
 1. Navigate to SRC/FEMAIN
 2. To build the FastEddy executable run make (optionally run make clean first if appropriate).
 
 To build on other HPC systems with NVIDIA GPUs, check for availability of the aformentioned modules/dependencies. Successful compilation may require modifications to shell environment variable include or library paths, or alternatively minor adjustments to the include or library flags in SRC/FEMAIN/Makefile.    
 
 ## Example PBS job script
-A bash-based PBS job submission script for running the model on NCAR's Casper machine. This script assumes you have cloned this repository into a /glade/work/$USER/FastEddy directory you created.
+A bash-based PBS job submission script for running the model on NSF NCAR's Casper machine. This script assumes you have cloned this repository into a /glade/work/$USER/FastEddy directory you created.
 ```
 #!/bin/bash
 #

diff --git a/docs/.DS_Store b/docs/.DS_Store
diff --git a/docs/Tutorial/cases.rst b/docs/Tutorial/cases.rst
@@ -9,7 +9,7 @@ Four test cases are described:
 * Dry stable boundary layer
 * Moist cloud-topped boundary layer
 
-Required tutorial resources including python utilities and Jupyter Notebooks are provided in https://github.com/NCAR/FastEddy-model/tutorials with required data for the moist dynamics example available at https://doi.org/10.5281/zenodo.10982246. All test cases are idealized setups over flat terrain. For each case, the user will set up the input parameter file, execute FastEddy, visualize the output using a Jupyter notebook, and perform some basic analysis of the output. After examining the test cases, the user will carry out some sensitivity tests by changing various input parameters. The purpose of these tests are for the user to become more familiar with the input parameters, and how changes to those parameters affect the output. After the tutorial, the user is expected to have basic knowledge to carry out LES using FastEddy.
+Required tutorial resources including python utilities and Jupyter Notebooks are provided in the tutorials directory of the `FastEddy-model GitHub repository <https://github.com/NCAR/FastEddy-model>`_ with required data for the moist dynamics example available at this `Zenodo record <https://zenodo.org/records/10982246>`_. All test cases are idealized setups over flat terrain. For each case, the user will set up the input parameter file, execute FastEddy, visualize the output using a Jupyter notebook, and perform some basic analysis of the output. After examining the test cases, the user will carry out some sensitivity tests by changing various input parameters. The purpose of these tests are for the user to become more familiar with the input parameters, and how changes to those parameters affect the output. After the tutorial, the user is expected to have basic knowledge to carry out LES using FastEddy.
 
 .. toctree::
 

diff --git a/docs/Tutorial/cases/MBL.rst b/docs/Tutorial/cases/MBL.rst
@@ -31,7 +31,7 @@ Input parameters
 Execute FastEddy
 ----------------
 
-Note that this example moist dynamics validation case example requires an additional dataset available as a gzip compressed tape archive file at https://doi.org/10.5281/zenodo.10982246. The contents of the archive incude an initial conditions file BOMEX_IC/FE_BOMEX.0 which is needed to run FastEddy for this case. The archive dataset also contains results from the 11 models that participated in the original Siebesma et al. 2003 model intercomparison as NetCDF files under BOMEX_Siebesma2003_models/\*.nc. Run FastEddy using the input parameters file /tutorials/examples/Example04_BOMEX.in. Be sure to copy the extracted initial conditions file from the archived dataset into the initial subdirectory of your case run directory.
+Note that this example moist dynamics validation case example requires an additional dataset available as a gzip compressed tape archive file at `Zenodo record <https://zenodo.org/records/10982246>`_. The contents of the archive incude an initial conditions file BOMEX_IC/FE_BOMEX.0 which is needed to run FastEddy for this case. The archive dataset also contains results from the 11 models that participated in the original Siebesma et al. 2003 model intercomparison as NetCDF files under BOMEX_Siebesma2003_models/\*.nc. Run FastEddy using the input parameters file /tutorials/examples/Example04_BOMEX.in. Be sure to copy the extracted initial conditions file from the archived dataset into the initial subdirectory of your case run directory.
 
 Visualize the output
 --------------------

diff --git a/docs/Tutorial/getting_started.rst b/docs/Tutorial/getting_started.rst
@@ -5,10 +5,9 @@ Getting Started
 Introduction
 ============
 
-`FastEddy`_ is a resident-GPU large eddy simulation (LES) model owned by the National Center for Atmospheric Research (`NCAR`_) Research Applications Laboratory (`RAL`_). It is designed for future turbulence-resolving numerical weather prediction. 
+`FastEddy`_ is a resident-GPU large eddy simulation (LES) model owned by the U.S. National Science Foundation National Center for Atmospheric Research (`NSF NCAR <https://ncar.ucar.edu>`_) Research Applications Laboratory (`RAL`_). It is designed for future turbulence-resolving numerical weather prediction. 
 
 .. _FastEddy: https://ral.ucar.edu/solutions/products/fasteddy
-.. _NCAR: https://ncar.ucar.edu
 .. _RAL: https://ral.ucar.edu
 
 This is a tutorial designed so that a user can learn how to execute FastEddy, using the four test cases described in this tutorial. 
@@ -19,4 +18,4 @@ Software and computing requirements
 
 Computing resources with at least four general purpose graphics processing units are recommended to carry out the test cases. System must be enabled with python and Jupyter notebook packages. Add other requirements (compilers, libraries, etc).
 
-Instructions on how to build and run FastEddy on NCAR's Casper architecture https://github.com/NCAR/FastEddy-model/blob/main/README.md.
+Instructions on how to build and run FastEddy on NSF NCAR's Casper architecture https://github.com/NCAR/FastEddy-model/blob/main/README.md.
diff --git a/docs/Tutorial/index.rst b/docs/Tutorial/index.rst
@@ -1,8 +1,13 @@
+########
+Tutorial
+########
+
 .. toctree::
+   :titlesonly:
    :numbered:
 
-   getting_started.rst
-   cases.rst
-   sensitivity.rst
+   getting_started
+   cases
+   sensitivity
 
 
diff --git a/docs/conf.py b/docs/conf.py
@@ -20,11 +20,11 @@
 project = 'FastEddy'
 author = 'UCAR/NCAR'
 author_list = 'Sauer, J., D. Muñoz-Esparza'
-version = 'main'
+version = '1.1.0'
 verinfo = version
 release = f'{version}'
-release_year = '2022'
-release_date = f'{release_year}-01-06'
+release_year = '2024'
+release_date = f'{release_year}-04-22'
 copyright = f'{release_year}, {author}'
 
 # -- General configuration ---------------------------------------------------

diff --git a/docs/index.rst b/docs/index.rst
@@ -5,18 +5,18 @@ FastEddy version |version|
 .. image:: _static/CoastalCase_u_y-32km_0440.png
 
 FastEddy® (FE) is a large-eddy simulation (LES) model developed by the
-Research Applications Laboratory (RAL) at the National Center for Atmospheric
-Research (NCAR) in Boulder, Colorado, USA. The fundamental premise of FastEddy
-model development is to leverage the accelerated and more power efficient
-computing capacity of graphics processing units (GPU)s to enable not only more
-widespread use of LES in research activities but also to pursue the adoption of
-microscale and multiscale, turbulence-resolving, atmospheric boundary layer
+Research Applications Laboratory (RAL) at the U.S. National Science
+Foundation National Center for Atmospheric Research (NSF NCAR) in Boulder,
+Colorado, USA. The fundamental premise of FastEddy model development is to
+leverage the accelerated and more power efficient computing capacity of
+graphics processing units (GPU)s to enable not only more widespread use of
+LES in research activities but also to pursue the adoption of microscale
+and multiscale, turbulence-resolving, atmospheric boundary layer
 modeling into local scale weather prediction or actionable science and
 engineering applications.
 
-
 .. toctree::
    :hidden:
-   :caption: TUTORIAL
 
+   release_notes.rst   
    Tutorial/index
diff --git a/docs/release_notes.rst b/docs/release_notes.rst
@@ -0,0 +1,35 @@
+*************
+Release Notes
+*************
+
+When applicable, release notes are followed by the GitHub issue number which
+describes the bugfix, enhancement, or new feature
+(`FastEddy-model GitHub issues <https://github.com/NCAR/FastEddy-model/issues>`_).
+
+FastEddy-model Version 1.1 Release Notes (20240422)
+===================================================
+
+This is the initial release of the FastEddy, an NSF NCAR developed parallelized
+and GPU-resident, large-eddy simulation code for accelerated modeling of the
+atmospheric boundary layer.
+
+In addition to the initial code, this release includes a patch for building
+the system in the current NSF NCAR high performance computing environment on the
+Casper and Derecho platforms, along with other changes as detailed below:
+
+  .. dropdown:: Repository, build, and test
+
+     * Add templates for Issues and Pull Requests (`#1 <https://github.com/NCAR/FastEddy-model/issues/1>`_)
+     * Set up the FastEddy Tutorial documentation (`#3 <https://github.com/NCAR/FastEddy-model/issues/3>`_)
+     * Consolidate FastEddy-tutorials content into FastEddy-model (`#8 <https://github.com/NCAR/FastEddy-model/issues/8>`_)
+     * Adjust FastEddy-tutorials BOMEX notebook & RTD Moist dynamics instructions for hosting datasets under new repo (`#10 <https://github.com/NCAR/FastEddy-model/issues/10>`_)  
+
+  .. dropdown:: Bugfixes
+
+     * None
+
+  .. dropdown:: Enhancements
+
+     * None
+
+