Learning how to work with datasets from climate models can be a daunting process when getting started, even for those with existing technical expertise. Climate DataLab provides "end-to-end" training on all aspects of the process:
- Understanding the fundamentals of how climate models are set up
- Basics of file formats used for storing climate model output (netCDF)
- Coordinate systems and dealing with 1D vs. 2D latitude and longitude information
- Calendar systems employed by climate models
- Scenarios of future climate change
- Naming schemes for both climate models and model experiments: from scenarios t o MIPs
- Climate model large ensembles
- Model "parameterizations" and inter-model physical differences
Also check out our main website at http://www.climate-datalab.org/ for much more information!
The goals of our project are:
- To increase usability of climate model output by the broader environmental science community as well as other interested groups
- To foster learning across demographics historically underrepresented in climate science
The tutorial exercises in these repositories are written in either Python or R. Some of them are configured to run using a Binder environment, but for others you'll need to download your own copy of the appropriate language.
Python installation instructions can be found here: https://realpython.com/installing-python/
R installation instructions (specifically, RStudio) are here: https://posit.co/products/open-source/rstudio/
note: if you like the RStudio interface, it can be used to execute either R or Python codes!