DART Tutorial

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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 [pdf]   Filtering For a One Variable System
Section 2 [pdf] The DART Directory Tree
Section 3 [pdf] DART Runtime Control and Documentation
Section 4 [pdf] How should observations of a state variable impact an unobserved state variable? Multivariate assimilation.
Section 5 [pdf] Comprehensive Filtering Theory: Non-Identity Observations and the Joint Phase Space
Section 6 [pdf] Other Updates for An Observed Variable
Section 7 [pdf] Some Additional Low-Order Models
Section 8 [pdf] Dealing with Sampling Error
Section 9 [pdf] More on Dealing with Error; Inflation
Section 10 [pdf] Regression and Nonlinear Effects
Section 11 [pdf] Creating DART Executables
Section 12 [pdf] Adaptive Inflation
Section 13 [pdf] Hierarchical Group Filters and Localization
Section 14 [pdf] Observation Quality Control
Section 15 [pdf] DART Experiments: Control and Design
Section 16 [pdf] Diagnostic Output
Section 17 [pdf] Creating Observation Sequences
Section 18 [pdf] Lost in Phase Space: The Challenge of Not Knowing the Truth
Section 19 [pdf] DART-Compliant Models and Making Models Compliant: Coming Soon
Section 20 [pdf] Model Parameter Estimation
Section 21 [pdf] Observation Types and Observing System Design
Section 22 [pdf] Parallel Algorithm Implementation: Coming Soon
Section 23 [pdf] Location Module Design
Section 24 Fixed Lag Smoother (not available yet)
Section 25 [pdf] A Simple 1D Advection Model: Tracer Data Assimilation

Terms of Use

DART software - Copyright 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

Contact: DART core group
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