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Data Assimilation Research Testbed
This project forked from jhendric/dart
Data Assimilation Research Testbed
# 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.
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