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