Silly challenge to silly statement

There is a new Challenge to Global Warming Skeptics by the FiveThirtyEight statisticians, who did such a good job with the Obama-McCain forecasts. The challenge is summed up by:

“For each day that the high temperature in your hometown is at least 1 degree Fahrenheit above average, as listed by Weather Underground, you owe me $25. For each day that it is at least 1 degree Fahrenheit below average, I owe you $25.”

He’s trying to address recent statements by some conservatives, paraphrased as “It’s cold this summer here in Minneapolis, so global warming must be wrong.” That’s a bit of a strawman, but from the Power Line blog post, there really is this sense of local vs global perspective.

Well, it’s actually a pretty silly challenge to a pretty silly statement. No serious GW skeptic I’ve heard contests that their is warming on a global scale, but argues against the magnitude or, more commonly, the cause of the warming (human vs not). The statistical challenge here only addresses whether there is warming, and even there is rigged to win even if there were no real global warming, because of the urban heat island effect. Most of the thermometers started out in rural areas, or in fields outside of towns, and cities were built around them. Areas around pavement are warmer than the surrounding areas, so there would be a measured warming trend due to development, not due to atmospherics.

A better bet would involve predicting the global temperature for, say, 5 years from now (along with the uncertainty). Each side puts in their prediction, and pays $1 times the ratio of the posterior probabilities for the two models, P(M1)/P(M2). Would anyone take a bet like that?


About brianblais

I am a professor of Science and Technology at Bryant University in Smithfield, RI, and a research professor in the Institute for Brain and Neural Systems, Brown University. My research is in computational neuroscience and statistics. I teach physics, meteorology, astonomy, theoretical neuroscience, systems dynamics, artificial intelligence and robotics. My book, "Theory of Cortical Plasticity" (World Scientific, 2004), details a theory of learning and memory in the cortex, and presents the consequences and predictions of the theory. I am an avid python enthusiast, and a Bayesian (a la E. T. Jaynes), and love music.
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