Uncertainty in Global Warming Science

Since the time of Kepler and Galileo there has been steady progress in the precision with which humans can predict the outcome of kinematic events.  As is well known, major advances were made by Newton and Einstein and today we can predict with extraordinary accuracy the trajectory of an object traveling with a known velocity under the influence of gravitational forces. 

This does not mean that the trajectory of a rocket traveling to Mars, for example, is known with absolute precision but is to some extent uncertain.  In part this uncertainty is introduced both by our inability to determine the velocity with perfect precision and by the perturbations of gravitational effects arising from  more distant objects.  

Therefore it is correct to say,  even in this very well understood case, that the results of the scientific calculation are “uncertain”.  Such uncertainty is a reality in all scientific calculations and those who depend upon the results of such calculations must be aware of this fact.  However in cases of the character of rocket trajectory calculations the uncertainties themselves are understood such that we can be very certain that a rocket meant to go to Mars will arrive there barring some unforeseen catastrophe such as an engine failure or a giant solar flare.

In the same fashion there are many areas in our lives (communication, GPS, air traffic control, cat scans, MRI, internal combustion, electric generation and transmission, radar, computer automation, etc.)  that depend upon the results of science and have associated with them uncertainties  that are both known and known to be negligible in terms of  the particular application to which the relevant science (electromagnetism, quantum mechanics, classical mechanics , etc.) is applied.  This is simply to state an obvious fact of our lives in the 21^st century. In this essay I will distinguish between three types of science,

• What I have briefly described above is a type of science that I will, for convenience, call Type A. I will take science to be of Type A if, in principal, the uncertainty in the result and the uncertainty in that uncertainty can be numerically calculated and the relative uncertainties in each can be determined to be less than some set percentage.

• For me, then, Type B science depends on equations that are less precisely constrained than in Type A science.  In the case of Type B science there is difficulty in defining quantities and boundary conditions.  The equations in Type B science  cannot be solved with the same precision as for Type A and, equally important, the uncertainty in the uncertainty is frequently unknown.  An example of a result of Type B science is the prediction of weather.  We may be told, for example, that  there is a 75% chance of rain in our area. This “prediction” is based upon the understanding that meteorologists have of the basic equations governing the movement of air masses , the changes of temperature and pressure with such movement and the condensation of water  vapor, however the conditions limiting the equations in this case, the boundary conditions, are not so precisely defined and  the objects to which the equations apply not so well defined as in the previous cases.
  
  The conclusions of Type B science have a much greater range of relative uncertainty than for Type A. The 25% uncertainty suggested by the 75% probability would of course be totally unacceptable in a Type A calculation of, say, the osmotic pressure of an injected serum or the probability of a mid-air collision. Furthermore, the uncertainty in that 25% uncertainty in the weather itself is, from everyday experience, quite a bit larger than would be acceptable for placing a lander on Mars or determining the locations of neighboring planes in the vicinity of an airport.  This, by the way, is not to demean meteorology – given the complexity of the problem the meteorologists do a marvelous job!

• Then there is Type C science.    A major tool of what I call Type C science is curve fitting.  One seeks to fit a curve  to data using parameters with no apriori physical meaning,  but that provide the smallest residual “error” .  In many cases it is the best that can be done, but the results are inevitably open to doubt.  An example is the growth of a population with time where an observer fits the data to a population vs. time curve and uses this to interpolate or extrapolate populations to times for which measurements are not available.  Such curves are always open to question even though in the hands of  skilled observers they may be used to reach significant conclusions (examples of Type C science are Malthus' population prediction and the Keeling Curve).

Now, finally, I will turn my attention to global warming.  My concern in this essay is that science of all three types is applied to global warming and frequently, when the validity of conclusions is under discussion, no distinction is made between the three types of science.  Taking the earth’s temperature as a function of time as an example, many deniers have focused on the uncertainties associated with the interpretation of tree ring or ice core data.  In my view this is acceptable to a certain extent.  Skepticism is a healthy component of scientific analysis and I believe that those who have made the measurements and compiled the data can and do adequately defend their conclusions.  But it is my personal view that global warming is based first and foremost upon the conclusion of Type A science (the interaction of the earth’s  Planck radiation with the rot-vib modes of atmospheric carbon dioxide and the experimental and theoretical determination of the extent of this interaction ). It is also my view that only upon the basis of Type A science is one able evaluate the Type C science inherent in fitting the earth’s temperature to time. 

A major problem, as I see it, is that when deniers question the Type C science without coming to grips with the underlying Type A science they can deceive themselves and others into believing that they are attacking the basic structure of global warming science whereas in reality they are just dealing with a detail in the superstructure. They may in fact be dealing with a detail within a detail, e.g. selecting for discussion a particular subset of data (“cherry picking”). On the other hand to deny the Type A science showing global warming without finding a flaw in the argument (see hfranzen.org for a basic discussion of the effect without feedbacks or interferences) is like saying , ”I accept almost all of mathematics but deny the validity of Euler’s Theorem”. Just as it would make sense to deny Euler’s Theorem only if one could disprove it, it makes no sense to deny global warming science without finding a logical flaw in the Type A science demonstrating GW while, as I claim almost everyone does, accepting the myriad results of Type A science that come into play in our daily lives. And further it makes no sense to attack the average earth temperature vs. time (hockey-stick) curve without first coming to grips with the Type A science of GW.  To my way of thinking the hockey stick is not the basis of GW science, it is derivative and confirmatory, and its basic correctness depends upon the fundamental Type A science underlying the temperature changes.

The gist of what I am saying is this – when deniers confront an issue dealing with Type C science they should be asked to first consider the question, “Do you accept the basic  conclusion of quantum mechanics and spectroscopy that global warming is occurring  right now?” If their answer is “no” than it seems to me that  it is Type A science that should be debated before tackling the Type C science.  If their answer is yes, then, importantly, it is not possible for them to take the fact of the debate as a demonstration that the major thrust of the science of global warming is basically flawed. Furthermore any discussion of some aspect of the Type C science can be meaningfully limited to the relevant issue without  trying to discuss the larger question of the validity of the underlying GW proposition.

In short, if a denier disputes the claims of the hockey stick and is unwilling to accept the basic science of absorption of infra-red radiation by carbon dioxide then it is fruitless to discuss the hockey stick with that denier.  On the other hand if they accept the basic science but deny the hockey stick then it can be worthwhile exploring  their concerns  and pointing out that the hockey stick result follows straightforwardly, if not rigorously, from the known increasing energy input into the earth.  In the discussion that follows they might  be able to present some basis for criticism of the hockey stick curve beyond the fact that they simply don’t want to believe in global warming, and if the criticism is valid this would be a win-win situation.

Posted by hfranzen on Sunday, 26 June, 2011

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