DART Tutorial¶
The DART Tutorial is intended to aid in the understanding of ensemble data assimilation theory and consists of step-by-step concepts and companion exercises with DART. The diagnostics in the tutorial use Matlab® (to see how to configure your environment to use Matlab and the DART diagnostics, see the documentation for Configuring Matlab® for netCDF & DART).
Section 1 |
Filtering For a One Variable System |
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Section 2 |
The DART Directory Tree |
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Section 3 |
DART Runtime Control and Documentation |
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Section 4 |
How should observations of a state variable impact an unobserved state variable? Multivariate assimilation. |
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Section 5 |
Comprehensive Filtering Theory: Non-Identity Observations and the Joint Phase Space |
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Section 6 |
Other Updates for An Observed Variable |
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Section 7 |
Some Additional Low-Order Models |
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Section 8 |
Dealing with Sampling Error |
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Section 9 |
More on Dealing with Error; Inflation |
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Section 10 |
Regression and Nonlinear Effects |
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Section 11 |
Creating DART Executables |
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Section 12 |
Adaptive Inflation |
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Section 13 |
Hierarchical Group Filters and Localization |
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Section 14 |
Observation Quality Control |
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Section 15 |
DART Experiments: Control and Design |
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Section 16 |
Diagnostic Output |
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Section 17 |
Creating Observation Sequences |
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Section 18 |
Lost in Phase Space: The Challenge of Not Knowing the Truth |
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Section 19 |
DART-Compliant Models and Making Models Compliant: Coming Soon |
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Section 20 |
Model Parameter Estimation |
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Section 21 |
Observation Types and Observing System Design |
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Section 22 |
Parallel Algorithm Implementation: Coming Soon |
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Section 23 |
Location Module Design |
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Section 24 |
Fixed Lag Smoother (not available yet) |
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Section 25 |
A Simple 1D Advection Model: Tracer Data Assimilation |