Saturday 12 August 2017

MANIPULATING SURFACE TEMPERATURE DATA MAY HAVE ADDED 0.4 DEGREES C

Data Quality – Surface Temperatures: Writing in Energy Matters, Roger Andrews has begun an examination of efforts to adjust measurements to a preconceived idea. His first part deals with land-based, surface-air temperatures (SAT). Ideally, these are taken roughly at 5 feet +/- one foot (1.5 to 2 meters) above the ground, in the shade, over a grassy or dirt field, 100 feet from pavement, buildings, trees, etc. A Stevenson screen is the standard to provide shade and protection from precipitation. As research by Anthony Watts has shown, relatively few official measuring devises in the US meet these criteria, which have not been moved.

Adding to the difficulty of maintaining a database of proper measurements, NOAA (National Centers for Environmental Information (NCEI) in Ashville, NC, (formerly the National Climatic Data Center), which is entrusted to keep records, has frequently changed them. Thus, their database and the databases of other entities using them, such as NASA-GISS and Climatic Research Unit (CRU), are questionable.

Andrews explains that he has spent about 20 years reconstructing and analysing the SAT data, He has addressed a number of individual examples where it appears that data were adjusted to match theory. In this systematic effort, he focuses on the SAT from NASA’s Goddard Institute for Space Studies (NASA-GISS, on Broadway). He compares the old GISS with the new GISS temperatures globally, and by northern and southern hemisphere. Subtracting the old from the new produces a warming trend – indicating a bias. He found that a large part of this trend came from elaborate procedures under the guise of homogeneity adjustments. Even the Berkeley Earth Surface Temperature (BEST) dataset was infected, as Andrews shows for South America where cooling areas became warming areas.

The conclusions by Andrews give pause for any value of the use of the NOAA, NASA, CRU datasets in establishing climate models for predictions / forecasts. Andrews writes:

“The conclusions? In previous posts and comments I had said that adjustments had added only about 0.2°C of spurious warming to the global SAT record over the last 100 years or so – not enough to make much difference. But after further review it now appears that they may have added as much as 0.4°C.”

“…and that global surface air temperatures have increased by only about 0.7°C over this period, not by the ~1.1°C shown by the published SAT series.”

None of this is new. Joe D’Aleo has been sounding the alarm for years, alienating colleagues at the American Meteorological Society, where he is a fellow. However, it is important to have different people familiar with high standards of data quality to review the work of others. No doubt some will challenge this analysis stating that Andrews is not a climate scientist. That approach is used against Steve McIntyre who is a consultant for mining companies. McIntyre along with Ross McKitrick exposed Mr. Mann’s faulty “hockey-stick.”

Andrews has a response to such criticisms.

“In my previous incarnation as a consultant in the mining industry I spent a lot of time verifying assay data bases (copper, gold, silver, lead, zinc etc.), and in doing so I learned all about the sanctity of raw data. You don’t adjust your raw data unless you have ironclad reasons for doing so. You either verify them or throw them out. Too many widows and orphans have been ruined by unscrupulous miners peddling bogus assays to do it any other way. The stock exchange regulators who ride herd on the public announcements of mining companies are very insistent about this, and woe betide anyone who tries to put one across on them and gets caught doing it.” [Boldface added.]

There are no penalties for manipulating climate data; perhaps there should be. From the attitudes expressed by Andrews and McIntyre, mining consultants are very scrupulous about details – data. Since many are concerned about climate change, it should be so for all climate scientists. If those who build mathematical models describing climate use poor data, then the models will describe the climate poorly.

That said, Andrews tests whether the warming trend is a result of the urban heat island effect (UHI). He concludes it is not. Though, in part it may be due to a shift in location of instruments to airports, as Fred Singer has suggested. Andrews writes further:

“There is no grand conspiracy to foist non-existent global warming onto a gullible public. The reason some think there is one is that the data adjusters are under intense pressure to come up with the “right” results, which inevitably makes their findings somewhat less than objective. Global warming, AKA climate change, is a major growth industry that already gives employment to hundreds of thousands of people, including some very influential ones, and the bandwagon has to be kept rolling.”

No doubt, the bandwagon effect is highly influential among national scientific organizations. But, if carbon dioxide emissions are causing dangerous global warming / climate change, we need credible data. It appears that by their data manipulations, NOAA and NASA-GISS are undermining their own credibility.

The difference of 0.4°C between the old and new data that Andrews calculates, is significant when one considers that NOAA, NASA, etc. recently proclaimed that 2016 was the hottest year ever – by 0.04°C.

Amazingly, in addition to its National Centers for Environmental Information, NOAA has “National Centers for Environmental Prediction” which proclaims its core values are Personal Accountability, Scientific Integrity, Honesty, and Trust.

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