aospy: automated climate data analysis and management

aospy is an open source Python package for automating your computations that use gridded climate and weather data (namely data stored as netCDF files) and the management of the results of those computations.

aospy enables firing off multiple calculations in parallel using the permutation of an arbitrary number of climate models, simulations, variables to be computed, date ranges, sub-annual-sampling, and many other parameters. In other words, it is possible using aospy to submit and execute all calculations for a particular project (e.g. paper, class project, or thesis chapter) with a single command!

The results get saved in a highly organized directory tree as netCDF files, making it easy to subsequently find and use the data (e.g. for plotting) and preventing “orphan” files with vague filenames and insufficient metadata to remember what they are and/or how they were computed.

The eventual goal is for aospy to become the community standard for gridded climate data analysis and, in so doing, accelerate progress in climate science and make the results of climate research more easily reproducible and shareable.

See also

  • Spencer Hill’s talk on aospy (slides, recorded talk) at the Seventh Symposium on Advances in Modeling and Analysis Using Python, recorded 2017 January 24 as part of the 2017 American Meteorological Society Annual Meeting.
  • The xarray package, upon which aospy relies heavily.

Get in touch

  • Troubleshooting: We are actively seeking new users and are eager to help you get started with aospy! Usage questions, bug reports, and any other correspondence are all welcome and best placed as Issues on our Github repo.
  • Our mailing list: join it! Questions, bug reports, and comments are welcome there also.
  • Contributing: We are also actively seeking new developers! Please get in touch by opening an Issue or submitting a Pull Request.


aospy is freely available under the open source Apache License.


aospy was originally created by Spencer Hill as a means of automating calculations required for his Ph.D. work across many climate models and simulations. Starting in 2014, Spencer Clark became aospy’s second user and developer. The first official release on PyPI was v0.1 on January 24, 2017.