NZCLIMATE TRUTH NO 50
12th JUNE 2004
CERTAINTY AND UNCERTAINTY
Benjamin Franklin considered that the only certainties were death and taxes.
David Hume went even further, insisting that induction never led to certainty.
All future information is subject to uncertainty; to levels of probability.
While death and taxes might be fairly close to 100% certain, the public,
and scientists, still find it difficult to come to terms with the undoubted
truth of Hume's conclusion. Most statements and conclusions fail to mention
or admit that they are uncertain, or how much they are uncertain.
The advances in the science of statistics in the earlier years of the last
century provided the prospect of actually supplying measurements of uncertainty.
These procedures are, however, inadequately understood, even by scientists,
so that the "uncertainties" involved in using these measures are often neglected.
A recent article in the "Economist"
The Economist, 3 June 2004
"What is published in scientific journals may not be as true as it should
illustrates my point. It ends with the following,
"Far too many scientists have only a shaky grasp of the statistical techniques
they are using. They employ them as an amateur chef employs a cook book,
believing the recipes will work without understanding why. A more cordon
bleu attitude to the maths involved might lead to fewer statistical soufflés
failing to rise."
Most of us are familiar with the most widely practiced means of measuring
uncertainty by its use in public opinion surveys. A recent attempt by the
"New Zealand Listener" to describe this procedure was rather garbled.
The generally accepted way of determining an average, plus its uncertainty
is as follows. First, there must be a random sample, a sample truly
representative of the entire population to be studied. This is, in itself,
often the greatest source of error. For example, there has never been even
a slight approach to a representative sample of temperature measurements
from the earth's surface; yet the "Climate Change" people choose to ignore
this basic flaw in their reasoning.
In the past, when a set of measurements were made, the "range" of the results
was given. Although it is now regarded as an obsolete, unreliable measure
of uncertainty It is used by the IPCC to indicate the possible change
in global surface temperature by the year 2100 in "Climate Change 2001".
Another example is the IPCC opinion of the rate of global sea level rise
during the 20th century, said to be "in the range of 1.0 to 2.0 mm/yr with
a central value of 0.5mm/yr". This figure is based on tide-gauge data, which
are extremely unrepresentative of the world oceans, being mainly confined
to Northern Hemisphere port cities.
The more modern method of expressing uncertainty is to assume that the results
can be expressed by some form of distribution curve, which can hopefully
be given a mathematical form, so that the levels of uncertainty can be calculated.
If the curve is symmetrical, then the "average" will be close to the most
Although real life distribution curves can be quite varied, and may not be
symmetrical, it is usual to assume that they follow the simplest distribution
curve of all, called the "Gaussian curve". When this is so, it is possible
to calculate a quantity called the "standard deviation" or "standard error"
tells you the likelihood that a particular result might deviate from the
average. For the Gaussian curve, two observations in three are within one
standard deviation of the mean, nine out of ten are within two standard
deviations, and ninety nine out of a hundred are within three standard deviations.
One in three is pretty poor odds, but people who have shonky results often
use it to exaggerate the accuracy of their data. For example, the ocean temperature
data of Levitus et al (Science 2000 287 2225-2229) are given with only
one standard deviation, since they would look unconvincing if the conventional
two standard deviations were supplied.
Most working scientists, including public opinion gatherers and medical researchers,
choose two standard deviations as their measure of uncertainty. The public
may not realise that this assumes a one in twenty chance that an individual
result may be outside these limits. This is not really very long odds, and
three standard deviations may often be justified if you want to cover 99%
of the data.
Many of us possess a "Scientific" calculator, and others have computers with
an "Excel" spreadsheet which allow us to calculate "linear regression" This
uses a mathematical technique called the "method of least squares" which
enables you to draw the best straight line through a plot of one quantity
against another quantity, and to calculate the "correlation coefficient",
which is a measure of how good the line fits.
The procedure can only be justified if there is reason to suppose that the
quantities plotted really are related by means of a straight line. This requirement
is routinely ignored by climate change scientists.The plots of "globally
averaged temperature anomalies" against year, so frequently displayed, are
very far from conforming with a straight line behaviour, yet the linear regression
curves are drawn, and extrapolated to predict the future. Admittedly "Climate
Change 2001" in Chapter 2 goes so far as to break their graph up into sections,
each of which has its individual straight line. The Satellite global temperature
record from 1979 is so wobbly that it is really absurd to try and fit a straight
line to it, but the scientists still do it.
Strangely, the one climate change quantity which actually does appear to
conform with a straight line function is the global atmospheric carbon dioxide
concentration, which has increased in a linear fashion since 1976. Since
there is no theory that can explain this the fact is ignored.
Much of the work of the IPCC is based on guesswork (called by them "judgmental
estimates"), without any scientifically valid measures of uncertainty. They
feel awfully guilty about this, so they try to apply quantitative figures
to their guesses.
Thus "virtually certain" means "greater than 99% chance that it is
true"; "very likely" , 90-99% chance; "likely" , 66-95% chance; "medium likelihood",
33-66% chance;"unlikely, 10-30% chance; very unlikely 1-10% chance and "Exceptionally
unlikely", less than 1% chance. It is no surprise to find that there are
no results below the "likely" level. The "judgmental estimates" are always
made by those who originate the calculation.
The masterpiece of statistical uncertainty from the IPCC is their Figure
which summarises the factors involved in global mean radiative forcing since
1750. This figure appears no less than three times in "Climate Change 2001",
and is the fundamental basis of the entire claim that there is "global warming"
based on an increase in net radiative forcing.
This figure, to begin with, omits the most important components of "radiative
forcing", which are water vapour and clouds, which are tucked under
the carpet as merely "feedbacks"..If they were included they would overwhelm
the quantities pictured.
Then each quantity has "error bars", which, according to the caption of Figure 6.6 in "Climate Change 2001" "have no
statistical basis". They are ""judgmental estimates". Then, note that all
the quantities have increased uncertainties, above the "judgmental" values"
shown because of "Levels of Scientific Understanding" which is"Very Low"
for most of them. Even the figures characterised as "High" levels of
scientific understanding attract some controversy in the scientific literature.
The IPCC warn that you cannot just add and subtract these quantities, since
they interact with one another, but it is surely obvious that the net value
of "radiative forcing", the additional radiation at the troposphere since
1750, is simply unknown. It is not known whether it is going up or down.
The climate models, are, if this is possible, even worse. No estimates of
uncertainty are ever given, apart from the "judgmental estimates (i.e. guesses).
All future projections of the IPCC are given without scientifically justified
measures of uncertainty. All evidence indicates that if these were available
they would be so great that the projections are meaningless and no basis
for promoting the economic disruptions.involved in the proposed controls
75 Silverstream Road
Phone/Fax (064) 4 9735939
"It's not the things you don't know that fool you.
It's the things you do know that ain't so"