Climate Change Weekly # 567—A Meaningless Number Drives Climate Policy
A recent study published in the Journal of American Physicians and Surgeons argues the trillions of dollars spent to fight climate change are being wasted in a vain and unnecessary effort driven in large part by the focus on an essentially meaningless and made-up metric: global mean surface temperature (GMST).
Study author Jonathan Cohler points out GMST is a made-up and poorly defined metric:
[T]he GMST does not have a precise regulatory definition, and is in fact physically meaningless based on fundamental principles of thermodynamics. Nevertheless, all IPCC climate models are tuned to reproduce historical GMST trends. This represents what Orwell presciently described: the systematic replacement of objective truth with politically convenient fiction
Cohler notes that the fundamental principles of thermodynamics were firmly established by the last quarter of the nineteenth century, defining warming as a transfer of energy into or within a system as measured by joules or watt-seconds, not changes in measured degrees Celsius.
A recent AI analysis of the claims of warming based on purported changes in temperatures confirmed the methodologies and assumptions used by the IPCC to designate and forecast temperatures are “fundamentally fraudulent” because the project of averaging temperatures is meaningless outside of an equilibrium system, which the Earth and its various climates are not. Also, to measure average temperature change, one must work within a common designated system of measurement, yet the IPCC contributors don’t do this. Per Cohler:
Temperature is an intensive property [a characteristic of a substance that does not change with the amount of matter present, such as density, temperature, color, or boiling point, etc.] that is defined only in equilibrium systems and cannot be meaningfully averaged across non-equilibrium systems. The Earth’s surface air and ocean water is a large non-equilibrium system with enormous spatial and temporal variations in temperature, pressure, humidity, and heat capacity, in addition to the more than 800-fold mass density difference between sea water and air. It is well understood that as an intensive thermodynamic property, temperature is neither additive nor meaningfully averageable across such a system, in contrast to extensive properties such as energy, mass, and volume, which scale directly with the amount of matter and can be summed over subsystems. As Essex et al. demonstrate, there is no physical principle that dictates how surface temperatures should be averaged globally to produce a meaningful statistic, making any such human-chosen averaging methodology arbitrary, resulting in a statistical artifact with no physical meaning.
This arbitrariness is not a minor technical detail. There are infinite ways to average temperatures—arithmetic mean, geometric mean, harmonic mean, root mean square, and the entire family of Hölder means, among infinitely many others. Each method produces different numerical results and different trends over time. Without a physical principle to select one averaging method over another, the choice becomes purely arbitrary. As the Essex paper conclusively demonstrates, “if the physics does not prescribe one averaging rule to be used over another, as it does not for temperature, we may use any rule. If one interpreter of the data chooses one rule while another chooses a different rule, there is no way to settle a disagreement as to whether the system is getting warmer or cooler with time.”
The computer and logic principle of Garbage In, Garbage Out applies to climate claims. As Cohler notes, since the GMST used to support the claim of dangerous global warming is unscientific and arbitrary, all the feedback mechanisms and outputs describing future states of the Earth’s climate that computer models project are equally ungrounded and arbitrary:
The implications extend far beyond academic thermodynamics. Every climate model used by the IPCC (CMIP models) is tuned to reproduce historical GMST trends. When models are calibrated to match a physically meaningless quantity, their outputs become equally meaningless—not just for temperature projections, but for all variables, since these are coupled global circulation models where all components interact. The fundamental principle of scientific modeling requires that models be validated against physically meaningful observables.
In short, Cohler argues, to “regain legitimacy and contribute meaningfully to understanding the Earth’s complex thermal systems,” climate science must stop using derivative metrics such as climate sensitivity and instead stick to fundamental physics.
Sources: Globe News Wire; Journal of American Physicians and Surgeons
