On the ordinality of temperature
As noted in another post [4], the non existence of a global mean surface temperature follows from the fact that temperature is an ordinal random and not interval as claimed in some statistics texts. As illustrated in [5] the same data set can consistent with both warming and cooling. The purpose of this post is review some of the mathematics governing changes of scale and in passing to deduce the ordinality of temperature.
The Stevens’ taxonomy
Although well known, restrictions on changes of scale are often not given sufficient importance in science education. It, indeed is, ironic to find more discussion of this matter in Philosophy, Psychology, and Sociology texts than in Natural Science texts. In fact, it was a Harvard
psychologist, S. S. Stevens [1], who produced a well known taxonomy of measurement scales based on the classes of transformation admissible under a change of scale. For the convenience of the reader, we include a brief outline of Stevens’ taxonomy. In this classification a variable is called ratio, interval, ordinal or nominal according to the class of transformations permitted under a change of scale. The classes of admissible transformations are summarized in Table 1.

By means of examples from Physics we illustrate how each of these categories arises. We begin by briefly examining the transformation of random variables in general.
Transformations of Random Variables
Let be the set of all outcomes of a random experiment and let
be a random variable defined for each outcome
. If
is a real-valued function, then the composition
defines a new random variable
often referred to as the transformed random variable.

Such transformations have important mathematical and physical applications. Common statistical applications include standardization, grouping of data, changing the form of a distribution, and changes of frame and scale. For example, if is a random variable with mean
and variance
, then
transforms
to a “standardized” random variable
with mean 0 and variance 1. Geometrically,
is just the signed distance between
and the mean
measured in standard deviations.
If , then
is a random variable whose mean
is just the variance of
. If
is a continuous random variable and
a step function approximating the identity function, then the transformed variable
will be a discrete variable with parameters and characteristics not too different from those of
, a fact useful in the grouping of experimental data and its depiction by, say, a histogram. In Physics,
can represent a Galilean or Lorentzian change of frame or a change of scale — say from feet to inches. What mainly concerns us here are changes of scale.
Linear Changes of Scale
When the transformation of a random variable represents a change of scale of some quantity, then the axioms governing that quantity can impose restrictions on the functions that may be used to transform the given variable. For example, if
represents the length in feet of a body B and
, then
is the length in inches. However, if
then the variable
is not admissible as a measure of length. We now show, subject to a continuity requirement, that if the length of a concatenation
of two bodies
and
is equal to the sum of their lengths, i.e.,
then the only admissible changes of scale for length are linear functions with slope
. In the previous equation, the binary operation
of concatenation does not combine numbers but rather
represents the new body formed by the juxtaposition of the two objects
and
. Now, if
is a new measure of length (in the rest frame) of a body , we require that in the new scale:
That is,
From (1) and (2) we have
If this is to hold for bodies and
of arbitrary length, then the function
must satisfy:
for all . As is well known, the additivity condition (3) is not quite enough to ensure the linearity of
. However, if the lengths of a sequence of bodies tend to zero in one scale, then they tend to zero in any scale. This additional physical axiom leads us to impose upon
the additional condition that
i.e., that is continuous from the right at the origin. As is well known, see for example Truesdell [3], this additional assumption is sufficient to prove that
must be linear
. Moreover, since length is non negative
This proves that length is a ratio variable in Stevens’ taxonomy.
Ratio variables arise whenever objects can be concatenated in such a way that equation \ref{concat} holds. Examples of such variables in Physics are time intervals, angle, mass, etc. However, variables such as position on a time scale and position on a length scale are not ratio variables since their admissible class of changes of scale is larger.
Affine Changes of Scale
A random variable is called interval if it admits only changes of scale where
is affine:
For example, if is the coordinate of a point
on a length scale and
is a fixed point on that scale, then
is a length which we already know to be a ratio variable. It follows that if
and
are the corresponding points after a change of scale, then
where
. Thus,
where
is affine of the form of equation (5). This proves that position
on a length scale is an interval variable in Stevens’ taxonomy. Physically, the change of scale
corresponds to a change of unit of length
followed by a change of origin
.
In general, if the distance of a point from the origin of some scale is a variable of ratio type, then the corresponding position of that object on the scale will be a variable of interval type. Thus, for example, the time of occurrence of an event is an interval variable whereas the time elapsed during some process is a ratio variable.
Ordinal Changes of Scale
In classical thermodynamics, the only restriction on a change of temperature scale is that it must preserve the order relation “hotter than” on the class of homogeneous fluid bodies. Since temperature
is a measure of degree of hotness, this implies that for any two such bodies
and
,
Moreover, if it be demanded that this hold in any other temperature scale
and so
If this is to hold for fluid bodies and
of arbitrary temperature, the change of scale
must be a strictly increasing function. Since there are no other restrictions implied by the usual thermodynamic axioms, it follows that temperature is an ordinal random variable and not, as frequently claimed, interval. In particular, average temperature becomes a scale dependent object.
Arbitrary Changes of Scale
Finally, consider a quantity such as particle type

in which no particular order relation is specified on the set of particles. The variable is now merely an indicator of category and the values of
are completely arbitrary. A change of scale such as
,
which transposes the types
and
is perfectly admissible as indeed would any arbitrary bijection. Thus, in Stevens’ taxonomy,
would be nominal.
Bibliography
- S. S. Stevens. On the theory of scales of measurement.
Science, 103:677–680, 1946. - C. Truesdell. Rational Thermodynamics. Springer-
Verlag, 1984. - C. Truesdell and S. Bharatha. Classical Thermodynamics
as a Theory of Heat Engines. Springer Verlag, 1977. - Philip Pennance, On the Non Existence of Global Warming, 2005
- Philip Pennance, A Fable of Global Warming, 2005
- Philip Pennance, On the Non Existence of Global Warming II, 2005