The data to which I refer comes from a recently published report from the Heartland Institute here in the Windy City in which several relevant sets of data converge, leading to the above conclusion.

First, there is surprising results of a study of the effect of paint changes on the thermometer shelters, known as Stevenson Screens, used by the National Oceanic and Atmospheric Administration’s National Weather Service (NOAA/NWS) to track changes in the climate of the U.S. From about 1890 to 1979, these weather stations were coated with “whitewash (slaked lime in water), which was a common outdoor coating of that era. When dried, it leaves a pure white coating of calcium carbonate on the wood surface.” Then in 1979, the National Weather Service (NWS), now an arm of the National Oceanic and Atmospheric Administration (NOAA), made a specification change to switch the surface coating from whitewash to semigloss latex paint. So what’s the big deal? Well, latex paints have significantly different infrared properties due to the pigment, titanium dioxide, which differs from the calcium carbonate-based whitewash. The change was made without regard to any possible effect on the temperature monitoring ability of the thermometer shelters. To be honest, this is most likely a lack of critical thinking on the part of the NWS and not part of some conspiracy initiated by Al Gore. Yes, our public school system does churn out some real winners!

At any rate, the aforementioned report did the experiment that should have been done prior to implementing this coating change, and found that, lo and behold, there was a 0.3º F difference in maximum temperature and a 0.8º F difference in minimum temperature between the whitewash and latex-painted screens. So big deal, you say? That would be my response as well, except consider that the concern over anthropogenic global warming was triggered by what these stations reported was an increase of about 1.2º F over the entire twentieth century. Yes, dear readers, one of the key techniques of lying with statistics is to expand or shrink axes as necessary to show the trend you have decided a priori is there. The next time you see one of those globaloney warming plots, look carefully at the y axis for the temperature scale.

Ste-rike one!

The second set of data comes from how data is “adjusted” to “homogenize” the data by comparing to surrounding stations and adjusting the numbers. I know of no justification for such a data transformation. The temperature is what it is, not what you want it to be. Now consider the difference between what NOAA publishes and what NASA Goddard Institute for Space Studies (GISS) publishes after NASA “homogenized” the Lampasas (Texas) USHCN (U.S. Historical Climate Network) station data, shown in the figure below. The revised data (shown in red) are made to appear cooler than the original data (shown in blue) in the past, making the positive slope of the trend in the last century even steeper.

 
Oh, and that upward spike about 2000? The temperature monitoring station was moved to a parking lot of a downtown radio station in violation of NOAA specifications, the third point we will examine in a moment.

 

But it gets even better! As illustrated in the graph below, in simplest terms, Even the NOAA adds a positive bias by its own “adjustment” methodology.  It is important to note that the graph below shows a positive adjustment of 0.5º F from 1940 to 1999.  The generally agreed-upon “global warming signal” is said to be about 1.2º F (0.7ºC) over the last century.[1]  NOAA’s “adjustments,” in other words, account for nearly one-half of the agreed-upon rise in temperature in the twentieth century. Man-made globaloney warming indeed!

Nor is this concern a fabrication of globaloney warming skeptics. Other scientists have published in peer-reviewed journals on this issue.[2]

Ste-rike two!

Which brings us to the third category alluded to above, station location.

The NOAA’s National Climatic Data Center set up the Climate Reference Network (CRN) with the following specifications for the site location of these stations.  According to Section 2.2 of the Climate Reference Network (CRN) Site Information Handbook, “the most desirable local surrounding landscape is a relatively large and flat open area with low local vegetation in order that the sky view is unobstructed in all directions except at the lower angles of altitude above the horizon.”  Five classes of sites – ranging from most reliable to least – are defined by NOAA itself:

Class 1:  Flat and horizontal ground surrounded by a clear surface with a slope below 1/3 (less than 19º).  Grass/low vegetation ground cover less than 10 centimeters high.  Sensors located at least 100 meters from artificial heating or reflecting surfaces, such as buildings, concrete surfaces, and parking lots.  Far from large bodies of water, except if it is representative of the area, and then located at least 100 meters away.  No shading for a sun elevation greater than 3 degrees.

Class 2:  Same as Class 1 with the following differences.  Surrounding vegetation less than 25 centimeters.  Artificial heating sources within 30 meters.  No shading for a sun elevation greater than 5º.

Class 3:  (error 1ºC)  Same as Class 2, except no artificial heating sources within 10 meters.

Class 4:  (error greater than 2ºC)  Artificial heating sources less than 10 meters.

Class 5:  (error greater than 5ºC)  Temperature sensor located next to/above an artificial heating source, such as a building, roof top, parking lot, or concrete surface.

The bulk of this current report consists of the results of more than 650 volunteer surveyors registering, and as of February 2009, surveying 865 of the 1,221 USHCN climate-monitoring stations, representing more than 70 percent of the operational climate-monitoring network in the continental United States. Their simple goal was to see what percentage of these climate-monitoring stations were installed per the agency’s own instructions, which would make their temperature readings reliable if followed (i.e., how many fall into Class 1 and 2 above).

The results? In the report’s own words:

We found stations located next to the exhaust fans of air conditioning units, surrounded by asphalt parking lots and roads, on blistering-hot rooftops, and near sidewalks and buildings that absorb and radiate heat. We found 68 stations located at wastewater treatment plants, where the process of waste digestion causes temperatures to be higher than in surrounding areas.

In fact, we found that 89 percent of the stations – nearly 9 of every 10 – fail to meet the National Weather Service’s own siting requirements that stations must be 30 meters (about 100 feet) or more away from an artificial heating or radiating/reflecting heat source.

In other words, 9 of every 10 stations are likely reporting higher or rising temperatures because they are badly sited.

For verification of these results, pictures of many of these stations are included, some with the infra-red counterpart to make the point:

Ste-rike three! You’re out!

And we haven’t even touched on the major gaps found in the data record that were filled in with data from nearby sites, a practice that propagates and compounds errors.

Based on the above, it is not hard for any reasonably intelligent individual to come to the same conclusion as this investigation (emphasis added):

The conclusion is inescapable:  The U.S. temperature record is unreliable. The errors in the record exceed by a wide margin the purported rise in temperature of 0.7º C (about 1.2º F) during the twentieth century.  Consequently, this record should not be cited as evidence of any trend in temperature that may have occurred across the U.S. during the past century.  Since the U.S. record is thought to be “the best in the world,” it follows that the global database is likely similarly compromised and unreliable.

And thus I conclude, globaloney warming is, indeed, man-made, in the sense that man has manipulated the data, intentionally or stupidly, you decide, to create the appearance of an upward trend in temperatures. As the above evidence indicates, the corruption of the underlying data falsifies any conclusions based thereon.

Those in the computer sciences are well aware of the meaning of the acronym, G.I.G.O., and this is an outstanding example of what we clearly have here.

Garbage In, Garbage Out!