Excited to share that I'm now a member of the CF Conventions Committee! 
CF (Climate and Forecast) conventions standardise how scientific data and metadata are stored in NetCDF files, ensuring consistency and machine readability. Looking forward to contributing and collaborating with the community to shape its future! 
Excited to share my new FREE video tutorial on creating CF-NetCDF files using R! 
In this video, you'll learn to:
• Ensure compliance with CF and ACDD conventions
• Work with 1D, 2D, and 3D data
• Manage irregular grids and moving instruments
Watch it here: https://youtu.be/IZDygRjfMIg
Plus, check out the accompanying Jupyter book for code and explanations: https://nordatanet.github.io/NetCDF_in_R_from_beginner_to_pro/04_creating_a_cfnetcdf_file.html
I’m pleased to share that my NetCDF in Python and R tutorials are now available on NorDataNet.
Access them here:
Python: https://www.nordatanet.no/NetCDF-in-Python-from-beginner-to-pro
R: https://www.nordatanet.no/NetCDF-in-R-from-beginner-to-pro
These tutorials cover everything from basic data extraction to creating your own NetCDF files, ensuring they meet CF and ACDD standards for FAIR data.
NorDataNet enhances access to environmental datasets, supporting long-term preservation and interoperability. 
Want to work with NetCDF files in Python? My tutorial series covers everything from opening and plotting NetCDF data to creating CF-compliant files for FAIR data publication.
Whether you're new to NetCDF or looking to enhance your skills, I've got you covered! Check it out: https://lhmarsden.github.io/NetCDF_in_Python_from_beginner_to_pro
Topics include:
Extracting data 
Plotting 
Creating CF-compliant files 
Granularity 
CF & ACDD
Suggestions? Let me know! #Python #DataScience #NetCDF #xarray #FAIRData #ClimateData
New Video Alert!
I’ve just released a tutorial on how to convert NetCDF data to CSV or XLSX using R. Whether you’re dealing with 1D, 2D, or 3D variables, this video will guide you through the process step-by-step.
Day six of the sixth eruption near #Svartsengi and the town of #Grindavík This eruption is the largest one yet. Here is a 4-day series of #Sentinel5p satellite data from the #TROPOMI instrument showing the mean amount of SO₂ in a vertical column of atmosphere (Dobson units). With time this will turn into sulfate particles forming volcanic smog.
This level 3 data is made available by The German Aerospace Center as #NetCDF files and can easily be opend in #QGIS and visualized with MDAL library.
The person who pinged me about this won't look too good dealing with the data product developers on his end if he keeps arguing for standards that, e.g., mean my software can read and plot the data. But forget moi, CF rules!
Otherwise. Ooof. My bad.
Meanwhile, other software packages apparently can plot this stuff? I guess they have multiple coders, and funding to pay them all?
Otherwise, crud. The data grid mapping issue is a pain, but I figured that out. But… the data are in a structure, which… the library doesn't handle well (cough, gag) and disaster ensues.
There could be a career in sci software dev here. If one had the funding.
Spent some time the last few days examining whether I need to blow up and rewrite code in order to plot a satellite data product. Seemed from perusing a very necessary library API that it wouldn't need much work. On re-read, maybe more work. Sigh, now realizing that the API itself would need refactoring. Which, 1) their developers might say no, or 2) worse, they might say yes but they have SO many other demands.
The user who pinged me about this will probably be less than surprised. F!
Belatedly remembering to announce a new release of the Panoply data visualization app (v. 5.4.3) has been posted. Now handles data on an ellipsoidal Mercator grid (per CF conventions!). Some fixes to the open-file dialog. Further ability to plot UGRID data was added a few weeks ago.
A new release of the Panoply data visualization app (v. 5.4) has been posted. The big change in this update is some ability to handle the UGRID 1.0 convention. We emphasize the "some" because OMG there are sure to be variants. Thus, more UGRID examples are needed.
Edit: Oh good grue, you might need a URL? See https://bit.ly/46QhhBW
Anyone knows of an open source software to make a diagram of the hierarchical structure of groups and variables in a #netcdf file? Doesn't need to be pretty, just to get a sense of files with many groups and sub-groups.
A new release of the Panoply data visualization app (v. 5.3.4) has been posted. Minor feature updates and bug fixes, plus some tinkering under the hood that could lead to major new features in the future.
From my colleague, Luke, on #Twitter and #linkedin so far:
" I am trying to expand my network. I have a #YouTube channel where I share tutorials on #FAIR #OpenData, #NetCDF files +Darwin Core Archives
https://youtube.com/@LukeDataManager
More subscribers/followers -> More people see my videos -> More people learn about FAIR data!
Consider helping me out! "
I really like his videos, check them out.
of oslo.town 
