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NetCDF Gridded Data (.nc)

A NetCDF-3 (classic) file holding a small CF-convention gridded temperature field over latitude, longitude, and time, with named dimensions and units — for testing NetCDF readers like netCDF4 and xarray.

Preview — schema + first 6 rowsnc
FieldValue
FormatNetCDF-3 classic (CDF-1)
ConventionsCF-1.6
Dimensionstime=3, lat=4, lon=5
Variableslat, lon, time, temperature
temperaturefloat32 (time, lat, lon), units K
TitleSample gridded surface temperature
Binary self-describing scientific data — decode with netCDF4 or xarray.

Specifications

Format
NetCDF-3 classic
Conventions
CF-1.6
Dims
time=3, lat=4, lon=5
Variables
lat, lon, time, temperature (K)

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 Gridded Data (.nc)” is a deterministic Novus Examples fixture for Scientific data. 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: NetCDF-3 classic. 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.

Data fixtures document their exact quirks — delimiters, encodings, null handling, schema, and row counts — in the spec table. Point your parser or importer at the file and assert it handles the documented edge cases; clean and deliberately-messy siblings make before/after diffs straightforward.

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