Changing temperature anomaly baselines

I wanted to check whether the choice of baseline can affect the calculation of  global temperature anomalies from station data. Each temperature index (GISS, Berkeley, CRU) uses different normalisation periods for calculating weather station temperature anomalies. I was surprised to discover that this choice makes no difference whatsoever to the results.

I used the new GHCN V4 which contains 27315 weather stations, and calculated the global average temperature anomaly relative to 5 different 30-year baseline periods using Spherical triangulation. Selecting different baselines restricts the analysis to those stations with sufficient data falling within those periods. Here are the results.

Global Land temperature anomalies calculated relative to 5 different baselines. The numbers in brackets are the number of stations contributing for each baseline period.

All the trends are very similar despite a factor of up to 8 difference in the number of stations used.  We can compare them all directly by offsetting each onto the same 1961-1990 baseline. To do this I simply scale each one by the offset difference between 1961-1990 (shown in ‘calc’ brackets).

All 5 baselines offset to the same 1961-1990 normalisation. The offsets are shown as Calc.

The results are surprisingly similar.  This means that the choice of baseline period is essentially arbitrary and does not affect the end result.

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3 Responses to Changing temperature anomaly baselines

  1. Bryce F Payne says:

    “All the trends are very similar despite a factor of up to 8 difference in the number of stations used….The results are surprisingly similar. This means that the choice of baseline period is essentially arbitrary and does not affect the end result.”
    Central Value Theorem still stands.
    There are enough stations in the available data to provide a statistically consistent picture.
    Appear to be two periods of falling and two periods of rising temp.
    Falling T periods are roughly half as long and half as steep as rising T periods, i.e., climate is warming.
    Pattern suggests may be an upcoming period of falling T.
    If not, then………
    Unfortunately the whole data set includes only two falling/rising T cycles, and no longer term cycles.

  2. Pingback: Changing temperature anomaly baselines – Climate Collections

  3. oz4caster says:

    For annual temperature anomalies, changing baselines simply shifts all the annual values up or down by a constant amount and does not effect trends. However, for monthly or daily temperature anomalies I have found that changing baselines can effect seasonal patterns, but does not effect long-term trends. Here is an example looking at daily NCEP/NCAR Reanalysis 1 temperature anomalies:
    https://oz4caster.wordpress.com/2019/02/15/global-temperature-reanalysis-baseline-comparisons/

    I am planning to post some additional results in the near future.

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