Bitrounding and Compress

• Paper: Klöwer, M., Razinger, M., Dominguez, J. J., Düben, P. D., & Palmer, T. N. (2021). Compressing atmospheric data into its real information content. Nature Computational Science, 1(11), 713–724. https://doi.org/10.1038/s43588-021-00156-2
• Video: https://www.youtube.com/watch?v=kcbOdwfskmY
• Julia package BitInformation.jl: https://github.com/milankl/BitInformation.jl
• Python wrapper xbitinfo: https://github.com/observingClouds/xbitinfo
• Aaron's talk in OES meeting May 4th 2022 Slides
• Mattermost channel

Todo: Generate MPIM usecases:

• for domains:
  1. [✓ hernan.campos, 2022-09-20]Ocean: add link to notebook
  2. [✓ hernan.campos, 2022-09-20]Land: add link to notebook
  3. [✓ ann-kristin.naumann, 2024-03-13]Atmosphere: add link to notebook
  4. [✓ hernan.campos, 2022-09-20]Ocean Biogeochemistry: add link to notebook
  5. …
• with shared analysis notebooks
• using aligned, fair & comparable file size benchmarks
• Answering questions:
  1. Which analysis doesn't work after bitrounding?
  2. What are general recommendations for bitrounding? i.e. inflevel=99.99%?