@@ -34,32 +34,31 @@ Here are some of the many benefits of using DART:
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system provided that you maintain the license and copyright information. Of
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course, we also ask that you credit DART in your publications, and kindly ask
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that you contribute your modifications so that other users may benefit. See
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- `How should I cite DART? < #citeDart >`__ and `How can I contribute to
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- DART? <#ContributeToDart> `__ for more information.
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+ :ref: `How should I cite DART?<citeDART> ` and :ref: `How can I contribute to
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+ DART? <contributors-guide>` for more information.
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2. DART is **fully parallel and carefully engineered ** to run on systems ranging
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from single-core research computers to the top performing multicore
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supercomputers in the world. Writing scalable parallel code is arguably the
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most difficult and time-consuming task in scientific computing today, but
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DART has already carefully implemented and tested this project, and the code
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is available for you to use out-of-the-box. For more information on how DART
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- was written (and continues to be developed), see `DART’s design
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- philosophy <#dartDesign> `__.
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+ was written (and continues to be developed), see :ref: `dart-design-philosophy `.
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3. DART contains **numerous tools that accelerate getting started ** on both
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research and “real-world” problems. Multiple rigorously tested inflation,
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localization, perturbation, and other auxiliary data assimilation algorithms
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- are available for immediate use and testing. See ` Important capabilities of
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- DART <#dartCapabilities> `__ for more information.
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+ are available for immediate use and testing. See :ref: ` important- capabilities-dart `
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+ for more information.
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4. DART **makes adding a new model straightforward **. A new model only needs to
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implement a list of (at most) 18 core functions or use the default behavior
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- if applicable to take advantage of DART’ s mature and robust DA algorithms. A
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+ if applicable to take advantage of DART' s mature and robust DA algorithms. A
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basic data assimilation system for a large model can be built in
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person-weeks, and comprehensive systems have been built in a few months. See
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- ` How do I run DART with my model? < #RunWithMyModel >`__ for more information.
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+ :ref: ` Using new models ` for more information.
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5. DART **makes it easy to add new observations ** in order to test their
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potential beneficial impact. Incorporating new observation types only
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requires creating a forward operator that computes the expected value of an
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- observation given a model’ s state. See `How do I add my observations to
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- DART? <#RunWithMyObs> `__ for more information.
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+ observation given a model' s state. See :ref: `How do I add my observations to
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+ DART? <adding-your-observations-to-dart>` for more information.
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6. DART **can be used to test new DA algorithms **. Many such algorithms have
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been successfully implemented, tested, and published using DART. This is not
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covered in this getting started guide as this is an “advanced user”
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