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NetCDF Multi-Variable Station File — Four Unit Systems (.nc)

Four physical quantities on one shared (time, station) grid, each with its own CF units string including the dimensionless '1' and the UDUNITS 'm s-1' spelling. It is the fixture for a unit-aware layer that has to keep four different unit systems straight in a single file.

Preview — schema + first 4 rowsnc
VariableUnitsstandard_nameNominal mean
air_temperatureKair_temperature285.0
air_pressurePaair_pressure101325.0
relative_humidity1relative_humidity0.62
wind_speedm s-1wind_speed5.4
Four quantities, four unit strings, one shared (time, station) grid — seeded, not observed.

Specifications

Variables
4
Units
K, Pa, 1 (dimensionless), m s-1
Feature Type
timeSeries
Stations
4
Times
6
Seed
20260807
Generator
numpy default_rng standard_normal

Testing contract

Expected to pass
Scenario
Read all four data variables and their units attributes, then convert air_temperature to degrees Celsius.
Expected result
All four variables have shape (6, 4), the units strings read back exactly as 'K', 'Pa', '1' and 'm s-1', and the Celsius conversion shifts values by -273.15 without touching the other three.

What is a .nc file?

NetCDF (.nc, Network Common Data Form) is a binary, self-describing format for array-oriented scientific data. It stores multidimensional variables (like temperature over latitude, longitude, and time) with named dimensions, units, and metadata attributes, and is a standard in climate, ocean, and geoscience.

How to use this file

Use an example .nc file to test NetCDF readers (netCDF4, xarray, Panoply), CF-convention validators, and gridded-data pipelines, or to verify dimension and variable extraction.

How to use this file for testing

“NetCDF Multi-Variable Station File — Four Unit Systems (.nc)” is a deterministic Novus Examples fixture for Scientific data, Serialization testing. Citation catalogs (BibTeX, RIS), chemistry structures (MDL Molfile, PDB), and gridded binary data (NetCDF, FITS) — for testing reference managers, molecule viewers, and scientific-data loaders.

Documented properties for this file: seed 20260807. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.

Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.

Scientific fixtures are small, valid, and fully synthetic — no real organism, patient, sample, or observation. Point your parser or loader at the file and check it reads the documented records, variables, or headers; binary formats ship a readable twin or metadata listing for comparison.

Generated by generation/scientific.py. Free for any use, no attribution required — license.