Satisfaction comes from wherever you can get it. An issue I filed on Github in 2021 and which users gradually piled onto to say, oh yeah, we need that? It's resolved!
New release of my software coming in the next couple days.
#netcdf
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𝗖𝗙 𝗠𝗲𝘁𝗮𝗱𝗮𝘁𝗮 𝗖𝗼𝗻𝘃𝗲𝗻𝘁𝗶𝗼𝗻𝘀 support #OpenScience by automating processes via metadata in #NetCDF and #Zarr files. They establish a unified language for the #weather, #climate, #ocean, and #EO community. https://buff.ly/rGPuoku
#remotesensing #EarthObs
ZenodoSupporting Open Science with the CF Metadata Conventions for NetCDFSlides for the presentation given on 11 December 2024 at the AGU Annual Meeting to the session for the AGU Open Science Recognition Prize. Abstact:The CF (Climate and Forecast) Conventions are a community-developed standard that promotes the sharing and automated processing of Earth systems science data in the netCDF data format (and in Zarr/GeoZarr). The CF conventions define metadata that can be used to describe the coordinate systems, data structure, and geophysical meaning and units of each variable. This enables users of data from different sources to decide which quantities are comparable and facilitates building applications with powerful extraction, analysis, and display capabilities. There is a mature and growing ecosystem of FOSS (Free and Open Source Software) and commercial software tools which work with CF. The CF standard has been essential to the success of high-profile internationally-coordinated modeling activities (e.g, the Coupled Model Intercomparison Project, which hosts more than 30 million files and more than 15 petabytes of data, all compliant with CF). CF is widely used by weather, climate, ocean and Earth observation scientists, and is gaining traction among others, such as the biogeochemistry and atmospheric chemistry communities.
Greg Cocks GSPy - A New Toolbox And Data Standard For Geophysical Datasets
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https://doi.org/10.3389/feart.2022.907614 <-- shared paper
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https://doi.org/10.5066/P9XNQVGQ | https://code.usgs.gov/g3sc/gspy <-- shared code repository
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[an older paper, but code is in active and ongoing development/evolution]
#GIS #spatial #mapping #geophysics #geophysical #NetCDF #datatypes #code #opensource #library #dataformats #standardisation #standardization #openstandard #portable #metadata #Python #package #GSPy #methods #workflows #xarray #CRS #opendata #architecture #toolbox
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.
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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.
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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. 5.3.4) 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.
Has anyone managed to use the #Copernicus #dataspace catalogue to access any #netcdf files? I can search for things, but ultimately, these are ungridded datasets, so I don't know how they work with #STAC friendly libraries like #stackstack or #odc....
#DYK?
One can now open #netCDF files having groups with #python #xarray-datatree !
> datatree.open_datatree('file.nc')
-> https://xarray-datatree.readthedocs.io/en/latest/index.html
So far I had to handle dict() of xarray datasets and it was a pain. Looking forward to giving this a try with actual satellite data files!
DatatreeDatatreeDatatree is a prototype implementation of a tree-like hierarchical data structure for xarray. Why Datatree?: Datatree was born after the xarray team recognised a need for a new hierarchical data st...
The Belgian Climate Centre is looking for a "senior data scientist" combining technical (e.g. #bash #rstats #python #sql #netcdf), analytical, communication, and management skills, preferably with knowledge of #climate science The job is in Uccle (Brussels).
https://www.climatecentre.be/post/now-hiring-senior-data-scientist
I have just discovered that #xarray has a weighted DataArray and this is an absolute game changer! The more I use xarray the more I appreciate what an awesome library it is.
Public service announcement
As of a month ago, Conda Forge has a #NetCDF #Fortran package for #Windows! Historically this package has only been available on Linux and Mac. This is big for us folk who (are forced to) work on Windows! https://anaconda.org/conda-forge/netcdf-fortran
anaconda.orgNetcdf Fortran :: Anaconda.org
Argos is a GUI for viewing and exploring scientific data, written in #Python and #Qt. It has a plug-in architecture that allows it to be extended to read new data formats. At the moment plug-ins are included to read #HDF-5, #NetCDF-4, WAV, Exdir, #numpy binary files and various image formats, but a plug-in could be written for any data that can be expressed as a Numpy array.
GitHubGitHub - titusjan/argos: Argos: a data viewer that can read HDF5, NetCDF4, and other file formats.Argos: a data viewer that can read HDF5, NetCDF4, and other file formats. - GitHub - titusjan/argos: Argos: a data viewer that can read HDF5, NetCDF4, and other file formats.
I still miss some #NetCDF #zarr #GeoTIFF #COG #geoparquet #HDF5 #OGC #geospatial people.
Anyone out there? :)
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So here comes a little challenge:
Step 1) install #ncmaps (https://github.com/TomLav/ncmaps). Really easy.
Step 2) make a #ncview screenshot of a #NetCDF file using one of the ncmaps colormaps.
Step 3) Post it here below, explaining what the image shows, and naming the colormap used.
I'll #boost your contribution 
!
GitHubGitHub - TomLav/ncmaps: ncmaps brings scientific colormaps to ncviewncmaps brings scientific colormaps to ncview. Contribute to TomLav/ncmaps development by creating an account on GitHub.
rainbows 
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