Friday, January 22, 2010

Climategate: CRU Was But the Tip of the Iceberg

January 22, 2010  By Marc Sheppard

Not surprisingly, the blatant corruption exposed at Britain’s premiere climate institute was not contained within the nation’s borders. Just months after the Climategate scandal broke, a new study has uncovered compelling evidence that our government’s principal climate centers have also been manipulating worldwide temperature data in order to fraudulently advance the global warming political agenda.

Not only does the preliminary report [PDF] indict a broader network of conspirators, but it also challenges the very mechanism by which global temperatures are measured, published, and historically ranked. 

Last Thursday, Certified Consulting Meteorologist Joseph D’Aleo and computer expert E. Michael Smith appeared together on KUSI TV [Video] to discuss the Climategate -- American Style scandal they had discovered. This time out, the alleged perpetrators are the National Oceanic and Atmospheric Administration (NOAA) and the NASA Goddard Institute for Space Studies (GISS).  

NOAA stands accused by the two researchers of strategically deleting cherry-picked, cooler-reporting weather observation stations from the temperature data it provides the world through its National Climatic Data Center (NCDC). D’Aleo explained to show host and Weather Channel founder John Coleman that while the Hadley Center in the U.K. has been the subject of recent scrutiny, “[w]e think NOAA is complicit, if not the real ground zero for the issue.”

And their primary accomplices are the scientists at GISS, who put the altered data through an even more biased regimen of alterations, including intentionally replacing the dropped NOAA readings with those of stations located in much warmer locales.

As you’ll soon see, the ultimate effects of these statistical transgressions on the reports which influence climate alarm and subsequently world energy policy are nothing short of staggering.

NOAA – Data In / Garbage Out

Although satellite temperature measurements have been available since 1978, most global temperature analyses still rely on data captured from land-based thermometers, scattered more or less about the planet. It is that data which NOAA receives and disseminates – although not before performing some sleight-of-hand on it.

Smith has done much of the heavy lifting involved in analyzing the NOAA/GISS data and software, and he chronicles his often frustrating experiences at his fascinating website. There, detail-seekers will find plenty to satisfy, divided into easily-navigated sections -- some designed specifically for us “geeks,” but most readily approachable to readers of all technical strata.

Perhaps the key point discovered by Smith was that by 1990, NOAA had deleted from its datasets all but 1,500 of the 6,000 thermometers in service around the globe.

Now, 75% represents quite a drop in sampling population, particularly considering that these stations provide the readings used to compile both the Global Historical Climatology Network (GHCN) and United States Historical Climatology Network (USHCN) datasets. These are the same datasets, incidentally, which serve as primary sources of temperature data not only for climate researchers and universities worldwide, but also for the many international agencies using the data to create analytical temperature anomaly maps and charts. 

Yet as disturbing as the number of dropped stations was, it is the nature of NOAA’s “selection bias” that Smith found infinitely more troubling.

It seems that stations placed in historically cooler, rural areas of higher latitude and elevation were scrapped from the data series in favor of more urban locales at lower latitudes and elevations. Consequently, post-1990 readings have been biased to the warm side not only by selective geographic location, but also by the anthropogenic heating influence of a phenomenon known as the Urban Heat Island Effect (UHI).   

For example, Canada’s reporting stations dropped from 496 in 1989 to 44 in 1991, with the percentage of stations at lower elevations tripling while the numbers of those at higher elevations dropped to one. That’s right: As Smith wrote in his blog, they left “one thermometer for everything north of LAT 65.” And that one resides in a place called Eureka, which has been described as “The Garden Spot of the Arctic” due to its unusually moderate summers.

Smith also discovered that in California, only four stations remain – one in San Francisco and three in Southern L.A. near the beach – and he rightly observed that

It is certainly impossible to compare it with the past record that had thermometers in the snowy mountains. So we can have no idea if California is warming or cooling by looking at the USHCN data set or the GHCN data set.

That’s because the baseline temperatures to which current readings are compared were a true averaging of both warmer and cooler locations. And comparing these historic true averages to contemporary false averages – which have had the lower end of their numbers intentionally stripped out – will always yield a warming trend, even when temperatures have actually dropped.

Overall, U.S. online stations have dropped from a peak of 1,850 in 1963 to a low of 136 as of 2007. In his blog, Smith wittily observed that “the Thermometer Langoliers have eaten 9/10 of the thermometers in the USA[,] including all the cold ones in California.” But he was deadly serious after comparing current to previous versions of USHCN data and discovering that this “selection bias” creates a +0.6°C warming in U.S. temperature history.

And no wonder -- imagine the accuracy of campaign tracking polls were Gallup to include only the replies of Democrats in their statistics.  But it gets worse.

Prior to publication, NOAA effects a number of “adjustments” to the cherry-picked stations’ data, supposedly to eliminate flagrant outliers, adjust for time of day heat variance, and “homogenize” stations with their neighbors in order to compensate for discontinuities. This last one, they state, is accomplished by essentially adjusting each to jive closely with the mean of its five closest “neighbors.” But given the plummeting number of stations, and the likely disregard for the latitude, elevation, or UHI of such neighbors, it’s no surprise that such “homogenizing” seems to always result in warmer readings…