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The PJ Tatler

by
Charlie Martin

Bio

July 29, 2012 - 5:44 pm
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Yesterday, Richard Mueller of UC Berkeley and the Berkeley Earth Surface Temperature (BEST) project published an op-ed in the New York Times headlined “The Conversion of a Climate-Change Skeptic.”  In it, he says:

Last year, following an intensive research effort involving a dozen scientists, I concluded that global warming was real and that the prior estimates of the rate of warming were correct. I’m now going a step further: Humans are almost entirely the cause.

My total turnaround, in such a short time, is the result of careful and objective analysis by the Berkeley Earth Surface Temperature project, which I founded with my daughter Elizabeth. Our results show that the average temperature of the earth’s land has risen by two and a half degrees Fahrenheit over the past 250 years, including an increase of one and a half degrees over the most recent 50 years. Moreover, it appears likely that essentially all of this increase results from the human emission of greenhouse gases.

Today, Anthony Watts of the Watts Up With That website announced and provided a paper (figures and tables here) in pre-print titled “An area and distance weighted analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends.”

Watts is listed as lead author, with co-authors Evan Jones of New York; Stephen McIntyre of Toronto, Canada; and Dr. John R. Christy from the Department of Atmospheric Science, University of Alabama, Huntsville. In it, they demonstrate a systematic bias of about 0.15 degrees Celsius per decade in the United States Historical Climatology Network (USHCN) temperature estimates.

That is, they show that according to their methods, which are drawn from new UN World Meteorological Organization guidelines, the total warming in USHCN data are overstated — in fact, nearly doubled.

(For our more excitable commenters: “systematic bias” aren’t the words of Watts et. al., and they don’t mean a purposeful bias. “Systematic bias” is a term in statistics for any procedure that leads to “systematic error,” a procedural error that moves an observed statistic consistently in one direction. Go read the Wikipedia article linked and restrain yourselves from conspiracy theories.)

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