# DART software - Copyright 2004 - 2013 UCAR. This open source software is
# provided by UCAR, "as is", without charge, subject to all terms of use at
# http://www.image.ucar.edu/DAReS/DART/DART_download
#
# DART $Id$

Welcome to DART, the Data Assimilation Research Testbed.
See the bottom of this file for quick-start instructions.

Extensive on-line documentation is on the project web pages:
 http://www.image.ucar.edu/DAReS/DART

Extensive local documentation is included in the DART subversion
checkout.  Open 'index.html' in your browser to begin.

A Matlab/PDF introduction is in the 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 slightly more advanced tutorial in PDF format is in the tutorial
subdirectory.  Start with the index file which explains what each
subsection covers.

The DART Lanai release documentation is on the web:
 http://www.image.ucar.edu/DAReS/DART/Lanai_release.html

and also in the subversion tree here at:
 doc/html/Lanai_release.html

General documentation in HTML format is in the doc/html directory, plus
all parts of the DART system include HTML files in the respective model
and source directories.  There is an 'index.html' file in the top level
directory which references all the other doc files.

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 add yourself go here and
click on 'Dart-users', and if you use WRF see 'wrfdart-users' also:
 http://mailman.ucar.edu/mailman/listinfo/

Contact us for more help or for more information on other models already
using DART or for how to add your model or observation types.

Thank you -
The DART Development Team.
dart at ucar.edu


Quick-start for the impatient:

Go into the 'mkmf' directory and copy over the closest
mkmf.template.compiler.system file into 'mkmf.template'.

Edit it to set the NETCDF directory location if not in /usr/local,
or comment it out and set $NETCDF in your environment.  
*This NetCDF library must have been compiled with the same compiler
that you use to compile DART, and must include the F90 interfaces.*

Go into 'models/lorenz_63/work' and run './quickbuild.csh'.

If it compiles, hooray.  Run './perfect_model_obs' and then './filter'.
If it runs, hooray again.  Finally, if you have Matlab installed on
your system, add '$DART/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.

If you are planning to run one of the larger models and want to
test the MPI version of DART, run './quickbuild.csh -mpi'.  It will
first compile the Lorenz 63 model without MPI and then try to build
filter with MPI.  *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.