All Scientists are Sceptics ~Professor Bob Carter

Whenever someone asserts that a scientific question is “settled,” they tell me immediately that they don’t understand the first thing about science. Science is never settled. Dr David Deming

Perhaps the most frustrating aspect of the science of climate change is the lack of any real substance in attempts to justify the hypothesis ~Professor Stewart Franks

A lie told often enough becomes the truth.
-- Vladimir Ilyich Lenin - See more at:
A lie told often enough becomes the truth.
-- Vladimir Ilyich Lenin - See more at:
A lie told often enough becomes the truth.
-- Vladimir Ilyich Lenin - See more at:

Wednesday, 25 July 2012



by Vincent Gray

JULY 24th 2012


Teaching of science and mathematics is now in rapid decline in our schools. Science has been replaced by the pseudo subject "the environment" and you are lucky if you can get a school leaver or even a graduate  who can give exact change, let alone complete an income tax form.

As a chemist I deplore the current ignorance of basic chemistry.. All chemicals are "toxic". The whole universe, including all living things and all food substances, is  made out of  chemicals and toxicity is a matter of entirely dependent on concentration and degree of supposed harm   So for that matter, is radioactivity.

When I worked for the Forensic Division of the DSIR the police were always bringing in  unknown white powders for identification . If they were crystalline a quick look under the microscope would find common salt (cubic) and sugar (anorthic). A flame would tell you flour, chalk (red colour) and soap powder (yellow flame). A pH test would give citric acid. I do not recall any other. Yet today it takes weeks with sophisticated computerised machines to identify these. If they are spilled on the road it is a national emergency and a media event. You even have to put on goggles and protective gear to deal with ordinary salt.

Statistical mathematics has basic assumptions which render its use invalid if they are not met.

In order to obtain any sort of average there are several essential conditions before the result  should be believed.

The sample must be random. and representative. This requirement is built in to all industrial quality specifications.

I remember an occasion when I worked for the Coal Research Association when a shipment of coal from Lyttleton to Japan was rejected because the  Japanese got a different value for its analysis than we did, so it had to return. Getting a random, representative sample before analysing it was quite an exercise.

People doing public opinion surveys and medical experiments often fail to get a truly representative sample, so their predictions must always be questioned. TV polls are useless and I often wonder whether the few set-top boxes which enable the TV people to decide how many people view ads really work.

It is quite impossible to measure the average temperature of the earth's surface as we cannot put measuring devices in a random representative manner over the entire surface. 71% is ocean and there are large regions of desert, forest,, mountain and ice. the temperature is also strongly dependent on time and altitude so it would have to  be instantaneous. Since this is impossible, it is also impossible to claim that the average is increasing or decreasing. There is therefore no logical or scientific basis for the claim that there is "global warming", a steady increase in the average temperature of the earth's surface..

Temperature measurements at weather stations are a valuable guide to local weather. Efforts are made to reduce variability by the use of standard measuring equipment and screens, but these have changed over the years. but  no weather forecaster would ever claim figures more accurate than the nearest degree Celsius. They never use decimals of a degree.

Efforts to make use of these measurements to provide a very poor substitute for a global average are  not only defeated by the lack of representivity. No weather station ever measures a daily average temperature. Even the most modern automatic weather stations, which are capable of providing a daily average, have never done so

Instead , until recently, only the maximum and minimum are measured. The average of these two does not give a mathematically acceptable average.                                                                      

Then, the observations when plotted against value,  must be symmetrical; otherwise there is no recognisable average. Gary Kerkin recently plotted distribution curves for two sets of maximum and minimum measurements from New Zealand weather stations and found they were bimodal, that is to say there were two maxima. The arithmetic average therefore is not the most probable figure.

Even if they were symmetrical they have to mimic the Gaussian bell curve upon which the mathematics depend. Without that you cannot calculate the variability. It has become conventional to calculate the "standard deviation" or "standard error" which is performed readily from a "scientific" calculator. or a computer spreadsheet. It is common practice to regard two standard deviations from the mean as representing 95% of the observations; in other words  there is one chance in 20 that any individual measurement will fall outside it. This figure tends to be adopted even when the chance of falling outside this range is unacceptable, such as adverse reactions from a new drug..

The processing of individual maximum and minimum temperatures into what is termed the "annual global temperature anomaly" consists of the averaging  of a whole year of individual figures. subtracting the average minimum from the average maximum., carrying out this procedure for every weather station in a 5ºx5º box on a map,  averaging all the boxes, and then subtracting them from the average of all the boxes for a reference period. Each of these procedures incurs large inaccuracies for each average, which when added up must surely amount to several degrees, yet the figures obtained are regarded as constants without any inaccuracy for each year in a time series. These unexpected constants are called "data" and many people seem to think that they are accurate representations of global temperature. A nominal inaccuracy is sometimes claimed, but is far below what it should be.

 This sequence is then subjected to a statistical procedure called "linear regression", again, a calculation available  on every "scientific" calculator and every computer spreadsheet. The objective is to seek to determine a "trend" which can be of value in future temperature prediction..

However the mathematics behind the theory of linear regression mean that it can only be used if all the samples are obtained in identical circumstances, with only one  variable as the argument. It should only be used for short period time series where identical samples can be guaranteed. It is quite unsuitable for annual climate time series since conditions always change over time, and any "trend" exaggerates the importance of the least known and least reliable earliest measurements. Its use for "trends" of "Global temperature anomalies" is quite illegitimate, as it  tends to identify past bias but not trends of the temperature variable. It is also unsuitable for long-term sea level trends, since earlier sea level measurements are prone to downward bias from the action of storms, local ground subsidence and dredging of harbours. ""Trends" should be based on recent, most reliable measurements in both cases.

 Not only are weather stations  not representative, the extent that this is  so changes  every second as stations are removed, added, or altered somewhere in the world. A genuine "temperature anomaly" is impossible.

This is so obvious that even  the scientists who have the effrontery to claim validity for this system consider that it needs to be "corrected" for "uncertainties. The process by which they do this is called "HOMOGENIZATION". At last I have got round to the title of this Newsletter..

The procedures used for "homogenization" are difficult to discover and seem to be largely intended to cause the "trend" in the "temperature anomaly" to rise. The success in this objective is modest, less than one degree per century and even this has petered out during the past ten years. These "corrections" can only concern a very few of the differences between the many non standardized weather station observations.

There have been very few attempts to check whether their assumptions  can be justified. Anthony Watts found that such a simple matter as changing the screen treatment from whitewash to latex paint made a difference of about half a degree, but this correction is never done. There are many studies which show that weather stations are affected by increases in local buildings, the use of concrete or local traffic, but no "correction" is applied. Since glass is a cooled liquid, liquid in glass thermometers read high if not regularly calibrated, but calibration certificates do not seem to be part of the archives,. No study has ever been done to find out whether changing the location of a site makes a difference by parallel studies with both sites. Gaps in the record are "guessed" by taking the average of "neighbouring" sites, which are sometimes far away. Recently it was found that when Bolivia failed to supply measurements for two years in a row, they took the average of the nearest sites, on the warmer coast of South America, and compounded the  error by adding an amount to compensate for the high elevation of the country of Bolivia. This made Bolivia the warmest place in the world for two years.

The most recent scandal has arisen because two Greek scientists Steirou and Kotsoyannis  (attached) have uncovered another error in "homogenization" which should be obvious.

It is assumed, not only that all the "mean daily" temperatures were obtained under identical circumstances, but that they are independent of one another. Well, all of us know that this is not true. The temperature one day not independent of the next day or the one before. They found that if you assume wrongly that they are independent and put it into the "homogenization" it automatically reduces the older figures and increases the more recent figure. so you get an increased "trend" which helps you "prove" global warming.

Another "homogenization" procedure that is dubious is that it is assumed that "Outliers" of more than three times the standard deviation should be eliminated. Now it happens to be true that the Gaussian Bell curve is often useful near the average, but rarely so at the outliers, which usually occur much more frequently than the maths assume. This why we are always getting "hundred year" extreme events such as floods or heat waves that occur more frequently. To eliminate outliers altogether seriously damages the result.

S and K found that important changes in thermometers and screens were not allowed for.

Weather stations have recently changed to automatic measurement, but there has been no comparison on the same site, between the automatic equipment and the previous system to see whether it makes a difference. Automatic measurement means that there there is not even an observer at the site at all so anything that goes wrong may not be known.

This half-baked unscientific system is helping to justify stopping the building power stations, running cars or prospecting for oil and gas.


Vincent Gray
Wellington 6035

"It's not what you don't know that fools you. It's what you do know that ain't so."  ~ Josh Billings

Sustainability is impossible. There are only two directions; forward and backward.

1 comment:

  1. Good for you. This is the best news story I’ve seen in a while.


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