GISTEMP

Our currently active project is ccc-gistemp, a reimplementation of GISTEMP in Python. GISTEMP is a reconstruction of historical temperatures using the instrumental record (records taken and kept at temperature monitoring stations around the world), it’s produced by the NASA Goddard Institute for Space Studies (GISS). It’s a computer program, mostly written in Fortran. One of the outputs of GISTEMP is a graph of the historical temperature anomaly, such as the graphs that you see on the banner of this blog.

The “all Python” milestone was achieved with ccc-gistemp release 0.2.0 on 2010-01-11. Naturally we have found (minor) bugs while doing this, but nothing else. Since 0.2.0 we have made major simplifications, chiefly by removing dependencies, and generally processing data internally (by avoiding writing it to intermediate files, which was only necessary on computers that would be considered extremely memory constrained by today’s standards).

Work continue on further simplification, clarification, generalisation, and extension.

It is our opinion that the GISTEMP code performs substantially as documented in Hansen, J.E., and S. Lebedeff, 1987: Global trends of measured surface air temperature. J. Geophys. Res., 92, 13345-13372., the GISTEMP documentation, and other papers describing updates to the procedure.

Currently the ccc-gistemp code produces results that are almost identical to the GISS code. As we emulate the exact GISS algorithm more closely, our results get closer.

Our ccc-gistemp code is available at googlecode.

Why GISTEMP?

  1. The instrumental record is a key indicator of global warming;
  2. NASA had already published the source code, we didn’t have to ask anyone for it;
  3. The lack of clarity in the code was disrupting the public debate.

GISTEMP is not the only analysis of the instrumental record, the UK’s meteorological office and the UEA’s Climate Research Unit maintain HadCRUT3, JMA’s Tokyo Climate Center maintain a global series of temperature anomalies, The US NOAA National Climatic Data Center also provide global surface temperature anomalies.

5 Responses to “GISTEMP”

  1. steven mosher Says:

    Cool your doing a re write in Python. A few of us who have worked with OPC ( other peoples code) have argued that a rewrite is the best way to understand what the code does. Looking forward to updates

  2. JS Says:

    The link to the google code is invalid (but the source is there).

    [ed: it works for me – NB]

  3. jkeyes Says:

    I updated the link on this page.

  4. Open Questions about Open Source for Open Science | Serendipity Says:

    […] does have a long list of existing initiatives, and a couple of major successes, most notably, a re-implementation of GISTEMP as open source Python, which helped to validate the original GISTEMP work, and provide an open […]

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