Previously on WUWT, I covered this contest. At that time, Doug J. Keenan stated:
There have been many claims of observational evidence for global-warming alarmism. I have argued that all such claims rely on invalid statistical analyses. Some people, though, have asserted that the analyses are valid. Those people assert, in particular, that they can determine, via statistical analysis, whether global temperatures are increasing more that would be reasonably expected by random natural variation. Those people do not present any counter to my argument, but they make their assertions anyway.
In response to that, I am sponsoring a contest: the prize is $100 000. In essence, the prize will be awarded to anyone who can demonstrate, via statistical analysis, that the increase in global temperatures is probably not due to random natural variation.
Doug J. Keenan writes today:
In November 2015, I launched a Contest, with a $100,000 prize: to spot trends in time series—series that were similar to the global temperature series. You blogged about it: “Spot the trend: $100,000 USD prize to show climate & temperature data is not random“.
Many people have claimed that the increase in global temperatures (since 1880) can be shown, statistically, to be more than just random noise. Such claims are wrong, as the Contest has effectively demonstrated. From the perspective of statistics, the increase in temperatures might well be random natural variation.
From his blog: http://www.informath.org/Contest1000.htm
18 August 2016
The paper is based on the assertion that the Contest “used a stochastic model with some realism”; the paper then argues that the Contest model has inadequate realism. The paper provides no evidence that I have claimed that the Contest model has adequate realism; indeed, I do not make such a claim. Moreover, my critique of the IPCC statistical analyses (discussed above) argues that no one can choose a model with adequate realism. Thus, the basis for the paper is invalid. I pointed that out to lead author of the paper, Shaun Lovejoy, but Lovejoy published the paper anyway.
When doing statistical analysis, the first step is to choose a model of the process that generated the data. The IPCC did indeed choose a model. I have only claimed that the model used in the Contest is more realistic than the model chosen by the IPCC. Thus, if the Contest model is unrealistic (as it is), then the IPCC model is even more unrealistic. Hence, the IPCC model should not be used. Ergo, the statistical analyses in the IPCC Assessment Report are untenable, as the critique argues.
For an illustration, consider the following. Lovejoy et al. assert that the Contest model implies a typical temperature change of 4 °C every 6400 years—which is too large to be realistic. Yet the IPCC model implies a temperature change of about 41 °C every 6400 years. (To confirm this, see Section 8 of the critique and note that 0.85×6400/133 = 41.) Thus, the IPCC model is far more unrealistic than the Contest model, according to the test advocated by Lovejoy et al. Hence, if the test advocated by Lovejoy et al. were adopted, then the IPCC statistical analyses are untenable.
I expect to have more to say about this in the future.
01 December 2016
Regarding the 1000 series that were generated with the weak PRNG (prior to 22 November 2015), the ANSWER, the PROGRAM (Maple worksheet), and the function to produce the file Answers1000.txt (with the random seed being the seventh perfect number minus one) are now available.
Cowpertwait P.S.P., Metcalfe A.V. (2009), Introductory Time Series with R(Springer). [The analysis of Southern Hemisphere temperatures is in §7.4.6.]
Shumway R.H., Stoffer D.S. (2011), Time Series Analysis and Its Applications(Springer). [Example 2.5 considers the annual changes in global temperatures and argues that the average of those changes is not significantly different from zero; set Problem 5.3 elaborates on that.]