New study finds the poor weather stations have a slight cool bias, not a warm one

Maybe we should call this the “Watts bias.”

… a proper analysis of the impact of these poorly-sited surface stations on the U.S. historical temperature record has now been done by Dr. Matthew Menne and co-authors at NOAA’s National Climatic Data Center (NCDC). In a talk at last week’s 90th Annual Meeting of the American Meteorological Society, Dr. Menne reported the results of their new paper just accepted for publication in the Journal of Geophysical Research titled, On the reliability of the U.S. Surface Temperature Record. Dr. Menne’s study split the U.S. surface stations into two categories: good (rating 1 or 2) and bad (ratings 3, 4 or 5). They performed the analysis using both the rating provided by surfacestations.org, and from an independent rating provided by NOAA personnel. In general, the NOAA-provided ratings coincided with the ratings given by surfacestations.org. Of the NOAA-rated stations, only 71 stations fell into the “good” siting category, while 454 fell into the “bad” category. According to the authors, though, “the sites with good exposure, though small in number, are reasonably well distributed across the country and, as shown by Vose and Menne [2004], are of sufficient density to obtain a robust estimate of the CONUS average”. Dr. Menne’s study computed the average daily minimum and maximum temperatures from the good sites and poor sites. The results were surprising. While the poor sites had a slightly warmer average minimum temperature than the good sites (by 0.03°C), the average maximum temperature measured at the poor sites was significantly cooler (by 0.14°C) than the good sites. As a result, overall average temperatures measured at the poor sites were cooler than the good sites. This is the opposite of the conclusion reached by Anthony Watts in his 2009 Heartland Institute publication. …

Watts not to love: New study finds the poor weather stations tend to have a slight COOL bias, not a warm one - Analysis of actual U.S. data disagrees with Anthony Watts' primary conclusion.

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