CDAT is a powerful and complete front-end to a rich set of visual-data exploration and analysis capabilities well suited for data analysis problems.
Warning The CDAT library is now in maintenance-only mode, with plans for deprecation and cease of support around the end of calendar year 2023. Until this time, the dependencies for specific CDAT packages (`cdms2`, `cdat_info`, `cdutil`, `cdtime`, `genutil`, `libcdms`) will be monitored to ensure they build and install in Conda environments. We currently support Python versions 3.7, 3.8, 3.9, and 3.10. Unfortunately, feature requests and bug fixes will no longer be addressed.
If you are interested in an alternative solution, please check out the xarray and xCDAT - Xarray Extended With Climate Data Analysis Tools projects.
New here? Don’t worry! We’ll help you get started. If you’re interested in what you can do with CDAT, you can take a look at our gallery. If you’re interested in anything you see there, you can look into getting our application installed. Once CDAT has been installed, check out our Getting Started guide.
Having trouble with something? We’ve got a great community of people who can give you a hand on our support email list.
If you want to get to know us, you can come chat with us on our developer mail list. If you want to get up to speed with the project, our wiki is kept up-to-date with what you need to get going.
CDAT builds on the following key technologies:
These combined tools, along with others such as the R open-source statistical analysis and plotting software and custom packages (e.g. DV3D), form CDAT and provide a synergistic approach to climate modeling, allowing researchers to advance scientific visualization of large-scale climate data sets. The CDAT framework couples powerful software infrastructures through two primary means:
Within both paradigms, CDAT will provide data-provenance capture and mechanisms to support data analysis.
CDAT is licensed under the BSD-3 license.