Climate Models Are Non-scientific Junk

Propagation of Error and the Reliability of Global Air Temperature Projections

Patrick Frank

SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA, United States

The reliability of general circulation climate model (GCM) global air temperature projections is evaluated for the first time, by way of propagation of model calibration error. An extensive series of demonstrations show that GCM air temperature projections are just linear extrapolations of fractional greenhouse gas (GHG) forcing. Linear projections are subject to linear propagation of error. A directly relevant GCM calibration metric is the annual average ±12.1% error in global annual average cloud fraction produced within CMIP5 climate models. This error is strongly pair-wise correlated across models, implying a source in deficient theory. The resulting long-wave cloud forcing (LWCF) error introduces an annual average ±4 Wm–2 uncertainty into the simulated tropospheric thermal energy flux. This annual ±4 Wm–2 simulation uncertainty is ±114 × larger than the annual average ∼0.035 Wm–2 change in tropospheric thermal energy flux produced by increasing GHG forcing since 1979. Tropospheric thermal energy flux is the determinant of global air temperature. Uncertainty in simulated tropospheric thermal energy flux imposes uncertainty on projected air temperature. Propagation of LWCF thermal energy flux error through the historically relevant 1988 projections of GISS Model II scenarios A, B, and C, the IPCC SRES scenarios CCC, B1, A1B, and A2, and the RCP scenarios of the 2013 IPCC Fifth Assessment Report, uncovers a ±15 C uncertainty in air temperature at the end of a centennial-scale projection. Analogously large but previously unrecognized uncertainties must therefore exist in all the past and present air temperature projections and hindcasts of even advanced climate models. The unavoidable conclusion is that an anthropogenic air temperature signal cannot have been, nor presently can be, evidenced in climate observables.

Full Paper is HERE.

Pat Frank makes the scientific argument that “climate models cannot predict future global air temperatures; not for one year and not for 100 years. Climate model air temperature projections are physically meaningless. They say nothing at all about the impact of CO₂ emissions, if any, on global air temperatures.

H/T to Watts Up With That

 

About Russ Steele

Freelance writer and climate change blogger. Russ spent twenty years in the Air Force as a navigator specializing in electronics warfare and digital systems. After his service he was employed for sixteen years as concept developer for TRW, an aerospace and automotive company, and then was CEO of a non-profit Internet provider for 18 months. Russ's articles have appeared in Comstock's Business, Capitol Journal, Trailer Life, Monitoring Times, and Idaho Magazine.
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4 Responses to Climate Models Are Non-scientific Junk

  1. tom0mason says:

    All too often conversations on the subject of climate fails because there is a failure to appreciate the essential differences between its science and mathematics.

    The discipline of Mathematics is a self-contained subject of itself. Mathematics as a subject is absolutely accurate, has its own rational logic, methods, and laws. Mathematics describes the various shapes of any given truth. Mathematics depends upon itself, it not about the physical universe about us.

    Science is about physical universe about us and the discovery of its truths. Science (aka mechanics) cannot be absolutely rationally reasoned because it (science) is based upon actual measurements which can never be made with absolute accuracy. Science does not depend on itself, for as well as depending on some mathematics, it is dependent on mechanics, material properties (electro-magnetic, chemical and/or biological, etc., physical properties), upon physical measurements (with errors), and the chaos evident at the atomic to cosmic levels. What this science system describes is the scientific reality that contains everything about the known universe so far. However what is less appreciated is that this science system is incomplete and has many errors. Thankfully, due to its continual review system, it is self correcting … eventually.

    In both science and mathematics descriptions of truth can only be translated, and never generated. Science and mathematics work together, and it’s truly great science when what is mathematically computed, or predicted to be, tallies with what is discovered. However all that is predicted from mathematics may not be physically possible, thus not seen in this universe.

    Like

  2. Bob Hobert says:

    This, and the referenced previous paper in 2001 by W. Soon, & Co, should shut down the entire CO2/AGM scam and expose it for what it is – a monumental scientific travesty. Should, except for politics.

    Like

  3. Russ Steele says:

    Reblogged this on The Next Grand Minimum and commented:

    This a bit off the topic of grand minimums but an important paper which could result in the reevaluation of the sun’s influence on climate.

    Like

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