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260 changes: 152 additions & 108 deletions readme.rst → README.rst
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Welcome to the Data Assimilation Research Testbed (DART)
========================================================

Extensive on-line documentation is available at the GitHub project web pages:
https://dart.ucar.edu/ or in the GitHub `repository <guide/>`__. Quick-start
instructions for the impatient can be found `below <#QuickStart>`__, while more
detailed setup instructions and other topics such as a brief introduction to
data assimilation, the history of DART, etc. are covered in the `DART Getting
Started Guide <https://dart.ucar.edu/pages/Getting_Started.html>`__.

+--------------------+--------------+
| |spaghetti_square| | |assim_anim| |
+--------------------+--------------+

.. |spaghetti_square| image:: ./guide/images/DARTspaghettiSquare.gif
.. |assim_anim| image:: ./guide/images/science_nuggets/AssimAnim.gif


A Matlab-based introduction is in the ``guide/DART_LAB`` directory.
There are a set of PDF presentations along with hands-on Matlab exercises.
This starts with a very basic introduction to data assimilation and covers
several fundamental algorithms in the system. A more exhaustive tutorial for
data assimilation with DART is in PDF format at
`guide/tutorial <guide/tutorial/index.html>`__.

The DART Manhattan release documentation is on the web:
http://www.image.ucar.edu/DAReS/DART/Manhattan/documentation/html/Manhattan_release.html
and in the repository at:
`guide/html/Manhattan_release.html <guide/html/Manhattan_release.html>`__

There is a mailing list where we summarize updates to the DART repository and
notify users about recent bug fixes. It is not generally used for discussion so
it’s a low-traffic list. To subscribe to the list, click on
`Dart-users <http://mailman.ucar.edu/mailman/listinfo/dart-users>`__. If you use
WRF, there is also a
`Wrfdart-users <http://mailman.ucar.edu/mailman/listinfo/wrfdart-users>`__.

The Manhattan release is new and currently supports only a subset of the models.
We will port over any requested model so contact us if yours is not on the list.
In the meantime, we suggest you check out our ‘classic’ release of DART which is
the Lanai release plus additional development features. All new development will
be based on the Manhattan release but the ‘classic’ release will remain for
those models which already have the necessary features.

For information on adding models and observation types or guidance on models
already using DART, contact DAReS staff by emailing dart@ucar.edu.

Thank you.

DART source code tree
---------------------

The top level DART source code tree contains the following directories and
files:

+------------------------+------------------------------------------------------------+
| Directory | Purpose |
+========================+============================================================+
| ``assimilation_code/`` | assimilation tools and programs |
+------------------------+------------------------------------------------------------+
| ``build_templates/`` | Configuration files for installation |
+------------------------+------------------------------------------------------------+
| ``developer_tests/`` | regression testing |
+------------------------+------------------------------------------------------------+
| ``diagnostics/`` | routines to diagnose assimilation performance |
+------------------------+------------------------------------------------------------+
| ``guide/`` | General documentation and DART_LAB tutorials |
+------------------------+------------------------------------------------------------+
| ``models/`` | the interface routines for the models |
+------------------------+------------------------------------------------------------+
| ``observations/`` | routines for converting observations and forward operators |
+------------------------+------------------------------------------------------------+
| ``theory/`` | pedagogical material discussing data assimilation theory |
+------------------------+------------------------------------------------------------+
| **Files** | **Purpose** |
+------------------------+------------------------------------------------------------+
| ``changelog.rst`` | Brief summary of recent changes |
+------------------------+------------------------------------------------------------+
| ``copyright.rst`` | terms of use and copyright information |
+------------------------+------------------------------------------------------------+
| ``readme.rst`` | Basic Information about DART |
+------------------------+------------------------------------------------------------+

Bug reports and feature requests
--------------------------------

Use the GitHub `issue tracker <https://github.com/NCAR/DART/issues>`__ to submit
a bug or request a feature.

Citing DART
Welcome to the Data Assimilation Research Testbed
=================================================

The Data Assimilation Research Testbed (DART) is an open-source, freely
available community facility for ensemble data assimilation (DA). [1]_ DART is
developed and maintained by the `Data Assimilation Research Section
(DAReS) <https://dart.ucar.edu/about/>`_ at the `National Center
for Atmospheric Research (NCAR) <https://ncar.ucar.edu>`_.

+------------------------------+------------------------------+
| |spaghetti_square| | |assim_anim| |
+------------------------------+------------------------------+

Ensemble Data Assimilation
--------------------------

Ensemble DA is a technique for combining observations with numerical models
to estimate the state of a physical system.

It enables modelers, observational scientists, and geophysicists to:

- Generate initial conditions for forecasts.
- Create a retrospective estimate of the state of a system, a practice known as
producing a *reanalysis*.
- Assess the relative value of specific observations on forecast skill, a
practice known as conducting an *observing system experiment (OSE)*.
- Estimate the value of hypothetical observations in order to inform the design
of an observing system, a practice known as conducting an *observing system
simulation experiment (OSSE)*.
- Determine a model's systematic bias in estimating the state of a system, a
practice known as diagnosing *model error*.

The DART software environment makes it easy to explore a variety of data
assimilation methods and observations with different numerical models. It
provides powerful, flexible DA tools that are easy to use and customize to
support efficient and reliable DA applications. While DART is primarily
oriented for DA research, it has also been used in operational settings.

DART includes:

- A comprehensive tutorial introducing the concepts of ensemble DA.
- Extensive documentation of its source code.
- Interfaces to a variety of models and observation sets that can be used to
introduce new users or graduate students to ensemble DA.

DART is also designed to facilitate the combination of assimilation algorithms,
models, and real or synthetic observations to allow increased
understanding of all three. It provides a framework for developing, testing,
and distributing advances in ensemble DA to a broad community of users by
removing the implementation-specific peculiarities of one-off DA systems.

These tools are intended for use by the full range of geosciencies community:
beginners and experts; students and teachers; national centers and university
research labs.

Organization of the documentation
---------------------------------

Because of DART's extensive scope, this documentation is detailed and
carefully organized, enabling you to easily find the information you need. If
you have any questions or suggestions for improvements, please contact DAReS
staff by emailing dart@ucar.edu.

The documentation is partitioned into three parts:

- a user guide that explains how to install DART and perform data assimilation
- source code documentation that provides a detailed description of the
programs and modules in the repository
- a comprehensive description of data assimilation theory

Manhattan Release
-----------------

The Manhattan release is new and currently supports only a subset of the
models. DAReS staff will port over any requested model. Email dart@ucar.edu
if yours is not on the list.

For more information on this release, see :doc:`guide/Manhattan_release`.

Quick-start
-----------

Cite DART using the following text:

The Data Assimilation Research Testbed (Version X.Y.Z) [Software]. (2019).
Boulder, Colorado: UCAR/NCAR/CISL/DAReS. http://doi.org/10.5065/D6WQ0202

Update the DART version and year as appropriate.

Quick-start for the impatient
-----------------------------

1. fork the NCAR/DART repo
2. clone your (new) fork to your machine - this will set up a remote named
‘origin’
Expand Down Expand Up @@ -151,28 +131,85 @@ Go into ``models/lorenz_63/work`` and run *quickbuild.csh*.
$ cd models/lorenz_63/work
$ ./quickbuild.csh
If it compiles, *:tada:*! Run this series of commands to do a very basic test:
If it compiles, run this series of commands to do a very basic test:

.. code-block::
$ ./perfect_model_obs
$ ./filter
If that runs, *:tada:* again! Finally, if you have Matlab installed on your
system add ‘$DART/diagnostics/matlab to your matlab search path and run the
plot_total_err diagnostic script while in the ``models/lorenz_63/work``
If that runs and you have Matlab installed on your system add
``DART/diagnostics/matlab`` to your matlab search path and run the
``plot_total_err`` diagnostic script while in the ``models/lorenz_63/work``
directory. If the output plots and looks reasonable (error level stays around 2
and doesn’t grow unbounded) you’re great! Congrats.
and doesn’t grow unbounded) you have successfully installed DART and completed
your first assimilation with it.

If you are planning to run one of the larger models and want to use the Lorenz
63 model as a test, run ``./quickbuild.csh -mpi``. It will build filter and any
other MPI-capable executables with MPI. *The* ``mpif90``
*command you use must have been built with the same version of the compiler as you are using.*
other MPI-capable executables with MPI.

.. important::

The ``mpif90`` command you use must have been built with the same version of
the compiler as you are using.

If any of these steps fail or you don’t know how to do them, go to the DART
project web page listed above for very detailed instructions that should get you
over any bumps in the process.

Citing DART
-----------

Cite DART using the following text:

The Data Assimilation Research Testbed (Version X.Y.Z) [Software]. (2019).
Boulder, Colorado: UCAR/NCAR/CISL/DAReS. http://doi.org/10.5065/D6WQ0202

Update the DART version and year as appropriate.

References
----------

.. [1] Anderson, J. L., T. Hoar, K. Raeder, H. Liu, N. Collins, R. Torn and A.
Arellano, 2009 The Data Assimilation Research Testbed: A Community
Facility. *Bulletin of the American Meteorological Society*, **90**,
1283-1296, `doi:10.1175/2009BAMS2618.1
<http://dx.doi.org/10.1175/2009BAMS2618.1>`_
.. |spaghetti_square| image:: ./guide/images/DARTspaghettiSquare.gif
:width: 100%

.. |assim_anim| image:: ./guide/images/science_nuggets/AssimAnim.gif
:width: 100%

.. toctree::
:maxdepth: 2
:caption: Getting started

guide/system-requirements
guide/fortran-compiler
guide/locating-netcdf-library
guide/downloading-dart
guide/compiling-dart
guide/verifying-installation

.. toctree::
:maxdepth: 2
:caption: Intermediate topics

guide/assimilation-complex-model
guide/mpi_intro
guide/filters
guide/inflation

.. toctree::
:maxdepth: 2
:caption: Diagnostics

guide/how-does-output-differ-from-input-increments
guide/matlab-observation-space

.. toctree::
:maxdepth: 2
:caption: Releases
Expand Down Expand Up @@ -227,6 +264,14 @@ over any bumps in the process.
models/wrf_hydro/readme
models/wrf/readme

.. toctree::
:maxdepth: 2
:caption: Contributing and Community

guide/contributors-guide
guide/requesting-features-reporting-bugs
guide/mailing-list

.. toctree::
:maxdepth: 2
:caption: Guide
Expand All @@ -239,7 +284,6 @@ over any bumps in the process.
guide/boilerplate/template
guide/vertical_conversion
guide/bitwise_considerations
guide/mpi_intro
guide/netcdf_inflation_files
guide/state_structure
guide/filter_async_modes
Expand Down

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