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ZONTEM (short for Zonal Temperatures) is a method for computing the change in global temperature over the recent period (1880 CE to present) from published records of monthly mean temperatures (GHCN-M V3).

ZONTEM aims to be as simple as possible while still giving a reasonable result.

Running ZONTEM

You will need to be able to run Python from the command line. We require Python version 2.


This downloads the GHCN-M dataset (of monthly average temperatures) as a compressed file, unpacks it, and runs the ZONTEM analysis.

The result, a CSV file, is placed in the output/ directory. It has a name based on the name of the input file used, which changes each month. Mine is called Zontem-ghcnm.tavg.v3.2.2.20140611.qca.csv.

Running ZONTEM again will not download the compressed GHCN-M file again if it sees it in the input/ directory. So if the file is there but broken (maybe due to an interrupted download), or you want a more recent version of GHCN-M (a new version is published roughly every month), then you should empty the input/ directory first.

The actual analysis is done by the program code/ and you can run that directly:

python code/


The input is a number of records, each record being a time series of monthly (air) temperature averages from a single station.

The input records are distributed into N (=20 by default) zones according to the latitude of the station. Each zone represents the surface of the globe between two circles of latitude; each zone covers an equal area.

All the station records in a zone are combined into one record by the Reference Station Method described in [HANSEN1987].

All the zone records are combined into a single global record using the same method.

The global record is converted to annual anomalies by first converting to monthly anomalies and then averaging into years where a year has all 12 monthly anomalies present.


The most obvious competing analyses of global temperature change are GISTEMP, CRUTEM4, NOAA (this is not an exhaustive list).

  • data sources. ZONTEM uses the GHCN-M product as its only data source. Other analyses use this supplemented with SCAR READER records, various priv comm records, or replace GHCN-M with a privately maintained database with similar coverage.

  • SSTs. Other analyses may have an optional procedure where Sea Surface Temperatures (SST) are used over the ocean. CRUTEM4 has a sister product, HadCRUT, that also incorporates SSTs. Whilst recognising that the Earth's surface is mostly ocean, ZONTEM does not incorporate SSTs.

  • gridding. Other analyses compute global temperature anomaly via a gridded product (the gridded product may be regarded as more essential than the global summary). ZONTEM dispenses with the grid, instead using a small number of zones (you could alternatively think of it as a 1x20 grid).

  • QC. Other analyses may have a QC step that rejects invalid station records. ZONTEM assumes that the input has been quality controlled.

  • inhomogeneity. Other analyses may have a step that adjusts or rejects inhomogeneous records. ZONTEM does not perform such a step (but usually uses the adjusted version of GHCN-M as input).


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