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Gridded Air Temperature — CSV Ground Truth (.csv)

Every value from the CF-1.8 NetCDF grid flattened to one row per cell, with the axis values spelled out in full. Diff a NetCDF-to-table export against this file to prove the reader walked the dimensions in (time, lat, lon) order and did not silently transpose the array.

Preview — first 50 linescsv
time_hours,lat_degrees_north,lon_degrees_east,tas_kelvin
0,-60.0,0.0,270.000
0,-60.0,60.0,268.500
0,-60.0,120.0,265.500
0,-60.0,180.0,264.000
0,-60.0,240.0,265.500
0,-60.0,300.0,268.500
0,-30.0,0.0,280.500
0,-30.0,60.0,279.000
0,-30.0,120.0,276.000
0,-30.0,180.0,274.500
0,-30.0,240.0,276.000
0,-30.0,300.0,279.000
0,0.0,0.0,291.000
0,0.0,60.0,289.500
0,0.0,120.0,286.500
0,0.0,180.0,285.000
0,0.0,240.0,286.500
0,0.0,300.0,289.500
0,30.0,0.0,280.500
0,30.0,60.0,279.000
0,30.0,120.0,276.000
0,30.0,180.0,274.500
0,30.0,240.0,276.000
0,30.0,300.0,279.000
0,60.0,0.0,270.000
0,60.0,60.0,268.500
0,60.0,120.0,265.500
0,60.0,180.0,264.000
0,60.0,240.0,265.500
0,60.0,300.0,268.500
6,-60.0,0.0,271.500
6,-60.0,60.0,270.000
6,-60.0,120.0,267.000
6,-60.0,180.0,265.500
6,-60.0,240.0,267.000
6,-60.0,300.0,270.000
6,-30.0,0.0,282.000
6,-30.0,60.0,280.500
6,-30.0,120.0,277.500
6,-30.0,180.0,276.000
6,-30.0,240.0,277.500
6,-30.0,300.0,280.500
6,0.0,0.0,292.500
6,0.0,60.0,291.000
6,0.0,120.0,288.000
6,0.0,180.0,286.500
6,0.0,240.0,288.000
6,0.0,300.0,291.000
6,30.0,0.0,282.000
122 lines total — download for the full file.

Specifications

Rows
120
Columns
4
Layout
long (one row per grid cell)
Units
hours, degrees_north, degrees_east, K
Precision
3 decimals

Testing contract

Reference control
Scenario
Flatten the paired NetCDF grid to long format with a reader of your choice and diff the result against this file.
Expected result
All 120 rows match to three decimal places with time varying slowest and lon fastest; any transposition of the lat/lon axes produces a mismatch on row 2.

What is a .csv file?

CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.

How to use this file

Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.

How to use this file for testing

“Gridded Air Temperature — CSV Ground Truth (.csv)” is a deterministic Novus Examples fixture for Scientific data, Conversion testing, Editor 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: 120 rows · 4 columns. 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.

Code examples

import pandas as pd

df = pd.read_csv("gridded-temperature-cf.csv")
print(df.head())
print(df.dtypes)

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