DART LAB

tutorial-feature-image

An introduction to Data Assimilation using MATLAB

DART_LAB is a MATLAB®-based tutorial to demonstrate the principles of ensemble data assimilation.

This tutorial begins at a more introductory level than the materials in the tutorial directory, and includes hands-on exercises at several points. In a workshop setting, these materials and exercises took about 1.5 days to complete.

DART_LAB consists of PDF tutorial materials and MATLAB® exercises. See below for links to the PDF files and a list of the corresponding MATLAB scripts.

DART_LAB tutorial slides

1. Ensemble Data Assimilation Concepts in 1D.

2. How Should Observations Impact an Unobserved State Variable? Multivariate Assimilation.

3. Inflation and Localization to Improve Performance.

4. Nonlinear and Non-Gaussian Extensions.

5. Adaptive Inflation.

Hands-on Exercises

The DART_LAB materials are bundled with DART.

You can download DART from Github using

git clone https://github.com/NCAR/DART.git

In the guide/DART_LAB/matlab subdirectory are a set of MATLAB scripts and graphical user interface (GUI) programs which are exercises that go with the tutorial. Each is interactive with settings that can be changed and rerun to explore various options. A valid MATLAB license is needed to run these scripts.

The exercises use the following functions:

  • bounded_oned_ensemble
  • gaussian_product
  • oned_cycle
  • oned_ensemble
  • oned_model
  • oned_model_inf
  • run_lorenz_63
  • run_lorenz_96
  • run_lorenz_96_inf
  • twod_ensemble
  • twod_ppi_ensemble

To run these, cd into the DART_LAB/matlab directory, start matlab, and type the names at the prompt.