Welcome to the DASH Docs!
DASH is a Matlab toolbox that implements paleoclimate data assimilation. The toolbox is not designed around any particular assimilation or reconstruction. Rather, DASH provides tools that implement common tasks for paleoclimate DA workflows. The toolbox is intended for use from both the console, and within scripts/functions.
Getting Started
If you have not installed the toolbox, you can find installation instructions here: Installing DASH
If you are new to DASH, we strongly recommend checking out the DASH Tutorial. The tutorial introduces each component of DASH step-by-step, and includes several demo datasets for practicing using DASH commands. We recommend setting aside several hours to complete the tutorial.
Accessing the docs
You can use the dash.doc command to load these docs at any time. After installing DASH, enter dash.doc in the Matlab console to open the documentation to this page.
To open the documentation for a specific item in the DASH toolbox, enter dash.doc('<item name>'). For example, dash.doc('kalmanFilter') will open the documentation for the Kalman filter class, and dash.doc('kalmanFilter.run') will open the documentation for the kalmanFilter.run method.
Alternatively, you can use the Matlab help browser to access the documentation for an item by entering help <item name> in the Matlab console, and then clicking on the Documentation Page link at the bottom of the help text.
Reference Guide
This documentation includes a complete reference guide to the DASH toolbox. This reference guide includes usage information for every class, package, function, and method in the DASH toolbox. If you like, you can learn about the toolbox by reading through the reference guide (but we strongly recommend the tutorial for first-time users).
This list describes the major components of DASH in a suggested reading order:
- gridMetadata
Helps define human-readable metadata to describe climate datasets.
- gridfile
Catalogues climate data sets and provides a common interface for accessing data stored in diverse formats.
- stateVector
Design and build state vector ensembles.
- ensemble
Manipulate state vector ensembles in a memory-efficient manner. Also includes tools for designing evolving ensembles.
- ensembleMetadata
Locate specific data elements within a state vector ensemble. Also includes tools for regridding variables from a state vector.
- PSM
Implement external proxy system modeling codes.
- kalmanFilter
Implement ensemble Kalman filter algorithms.
- particleFilter
Implement particle filter algorithms.
- optimalSensor
Implement optimal sensor algorithms.
- dash
A collection of utilities that help the toolbox run. Users may be interested in the
dash.localizeanddash.closestsubpackages.