https://github.com/callumrollo/wod-plots
Make the world ocean data plot that you know and love
Science Score: 26.0%
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Low similarity (12.6%) to scientific vocabulary
Repository
Make the world ocean data plot that you know and love
Basic Info
- Host: GitHub
- Owner: callumrollo
- License: mit
- Language: Jupyter Notebook
- Default Branch: main
- Size: 336 KB
Statistics
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
World Ocean Data plot
The plot that has graced a thousand powerpoints
Rationale
I couldn't find code to make this plot so I wrote these Python scripts. Feel free to use and remix them. See below for references to other existing versions of this plot.
Usage
The script download_wod.py will download all the source data files from https://www.ncei.noaa.gov/data/oceans/ncei/wod to make the plot. By default it will only save the lon, lat and time columns to save space. It totals to less than 2 GB. If you choose to keep the full nc files it will take up around 180 GB of disk space. If interrupted, it will resume from the next file.
It took me several days for the download process to run. The script retry.py will re-run the abose script if it has crashed. Works well as a cron job. It might need some path tweaking to run on you machine. Best run on a remote server
shortcut you can download the processed dataset here http://callumrollo.com/files/wodbyyear.pqt. Last updated april 2024.
The notebook make-plot.ipynb makes the plot from the downloaded files.
Known Issues
- Various timestamp encoding issues can crash this, see above on retrying the script.
- I found that after downloading many files I started to get partial downloads. You may need to enable nc downloads to debug this
- The download takes days. Not sure if running it in parallel against the NCEI server would be appreciated though!
Other versions
I first saw a recreation of this at a conference ~ 2022. I think it was the figure "watched waters" from this paper by Bates et. al 2018:
Bates, A. E., Helmuth, B., Burrows, M. T., Duncan, M. I., Garrabou, J., Guy-Haim, T., et al. (2018). Biologists ignore ocean weather at their peril. Nature 560, 299–301. doi: 10.1038/d41586-018-05869-5
I recently saw a more up to date version presented by Alexey Mishonov at IMDIS 2024 in Bergen:
2023 release of World Ocean Database and World Ocean Atlas Alexey Mishonov, Tim Boyer, Ricardo Locarnini, Hernan Garcia, Dan Seidov, James Reagan, Christopher Paver, Olga Baranova, Scott Cross, Courtney Bouchard, Ebenez Nyadro, Alexandra Grodsky and Dmitry Dukhovsko https://imdis.seadatanet.org/content/download/171431/file/IMDIS2024programmeV4.pdf
References
This work uses data from NCEI Standard Product: World Ocean Database (WOD) https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.nodc:NCEI-WOD
Disclaimers
This plot only shows data from the World Ocean Database. This is not a comprehensive, or even necessarily representative view of all oceanographic profiles taken in a given year.
No data integrity checks have been made against the original datasets, some data may have been missed.
I make no claim to the original data shown in this plot, or the idea to create it. See the above sections for references to the orginal works.
Owner
- Name: Callum Rollo
- Login: callumrollo
- Kind: user
- Location: Gothenburg, Sweden
- Company: Voice of the Ocean Foundation
- Website: https://callumrollo.github.io/
- Repositories: 86
- Profile: https://github.com/callumrollo
Oceanographer, Pythonista and data science-ish. Breaks things on Fridays
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Dependencies
- cftime *
- netcdf4 *
- pandas *
- requests *
- xarray *