Climate Science’s Dirtiest Secret
by Doug L. Hoffman, The Resilient Earth, 04/04/2010 [here]
With the climate science party-line case for global warming rapidly unwinding there is growing interest by researchers from outside the climate change community in applying advanced statistical techniques to climate data. It has long been recognized that statistical acumen has been lacking among mainstream climate scientists. This dirty little secret was first publicly disclosed during Congressional hearings regarding the 2006 Wegman Report. Even newer analyses have revealed that many of the predictions made by the IPCC reports and other global warming boosters are wrong, often because inappropriate statistical techniques were applied.
The Wegman Report was the result of an ad hoc committee of independent statisticians who were asked by a congressional committee to assess the statistical information presented in the Michael Mann “Hockey Stick” papers. Dr. Edward Wegman, a prominent statistics professor at George Mason University and chairman of the National Academy of Sciences’ (NAS) Committee on Applied and Theoretical Statistics, headed the panel of experts who examined the use of statistics in climate science. They found the climate science community was far too insular and did not consult with experts in statistics outside of their own field.
This self imposed isolation led, in the opinion of the committee, to misuse of statistics and a peer review process that only included the close-knit circle of researchers at the center of the global warming controversy. Wegman stated in testimony before the energy and commerce committee: “I am baffled by the claim that the incorrect method doesn’t matter because the answer is correct anyway. Method Wrong + Answer Correct = Bad Science.” More on the Wegman Report can be found in Chapter 13 of The Resilient Earth.
Nowhere is this “dirty secret” more prevalent than in climate science. I have already reviewed two recent statistical analyses of climate change that find much different answers and draw radically different conclusions than mainstream climate science. This post is the third in the series of articles on statistical analysis and global warming. In this article I will discuss another data analysis technique that is used to deal with non-stationary data of the type often associated with Earth’s climate system -— empirical mode decomposition. …
It could also be that some climate scientists are simply hedging their bets with this cooling trend stuff. Given that the misapplication and misinterpretation of statistics are climate science’s dirtiest secret, little credence can be given to any predictions about future climatic conditions. They may as well be casting horoscopes and reading the entrails of sheep. … [more]