Label NASA temperature anomalies with the correct baseline

A temperature anomaly is a difference from a reference-period average.

Label NASA temperature anomalies with the correct baseline. Explore the public-data example; methods and data notes are below.
Explore the public-data example; methods and data notes are below.Download chart SVG

The direct answer

A temperature anomaly is a difference from a reference-period average. The GISTEMP Land–Ocean table used here is relative to 1951–1980. A value of +1°C means one degree above that reference, not a global absolute temperature of 1°C.

Prepare the observation table

Remove the descriptive line above the CSV header and keep Year and J-D for complete years through 2023. Rename them year and anomaly_c. Use year as X and anomaly_c as Y; include “relative to 1951–1980” in the subtitle and source note.

Public dataset and a reproducible example

The download is a prepared extract, not a live data connection. The source links below include the original query, observation period and reuse policy. Keep an original copy when you update the data; revised source values can change the result.

NASA GISTEMP v4 Land–Ocean Temperature Index, complete annual J-D values through 2023, in °C relative to 1951–1980. The CSV description row was removed; no baseline conversion was applied. Cite GISTEMP Team and the source link.

Snapshot retrieved: 2026-10-26. Prepared rows: 144.

Download the prepared CSVDownload the reference SVG

First five rows from the prepared public-data extract; blank cells remain missing.
yearanomaly_c
1880-0.17
1881-0.09
1882-0.11
1883-0.18
1884-0.28

Build it in Datamon

Sign in with Google to create an editable visualization. Public articles and examples can be read without an account. The prepared CSV already contains the joins, filters or aggregations described above; do those steps in a spreadsheet first when using your own data.

  1. Open Data and choose a file, or paste the table with its header row. Check the detected numeric columns, decimal separator and dates. The current importer accepts files below 20 MB; these examples are smaller. Keep blanks distinct from recorded zeros.
  2. In Visualize, select Line chart. Connect the roles exactly as listed below. Review the preview against at least two rows in the example table rather than relying only on automatic mapping.
  3. In Refine, add a title that states the question, the unit, observation period and source. Check labels and contrast at the size your reader will see. Keep a table when exact values matter.
  4. Use the export controls for SVG, PNG, PDF or PowerPoint, then inspect the actual file. Save an editable project backup. Publish only after checking the underlying values: a public link makes the published data available to anyone possessing the URL.

Calculation and column mapping

The rule below is pseudocode. The downloadable CSV already contains the prepared values; spreadsheet functions and cell references depend on your sheet layout.

NASA J-D annual anomaly (°C), relative to 1951–1980; complete years <= 2023
X
year
Y
anomaly_c

Read the result

The 2023 annual anomaly is +1.17 °C relative to 1951–1980.

Use the preview to check the structure and the CSV to check exact values. Its styling is a reference; your Datamon rendering can look different. Follow the mapping and preparation above to reproduce the analytical meaning.

Mistakes that change the meaning

Do not relabel these values as warming since 1850–1900 without an explicit baseline conversion. Different baselines shift the level. This table alone does not determine whether a long-term climate target has been crossed.

Questions before sharing

Do these calculations require an AI service?

No. The prepared CSV and reference calculation are deterministic. Optional AI can help draft an explanation when configured, but it does not replace checking source values or choosing a valid comparison.

Can I use this example with my own spreadsheet?

Yes. Keep the same observation unit, column types and calculation. Replace the source attribution and time period, recompute derived columns, then compare several output values with your original sheet before sharing.

What is free and what needs an account?

Reading this guide and downloading its CSV and chart images are free. Datamon currently has no paid checkout or subscription plans in this deployment. Creating and saving an editable visualization requires Google sign-in. Provider-backed AI, cloud analysis, publishing and video depend on configured services; this guide does not promise unlimited free connected services.

Sources and further reading

Report a correction or an access barrier: Email the editorial contact.

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