New paper shows why climate models cannot be relied upon to determine climate sensitivity to CO2

A new paper published in the Quarterly Journal of the Royal Meteorological Society demonstrates why state-of-the-art climate models are a travesty of "parameterizations," a fancy word for "fudge factors," and are not based upon basic physics as commonly believed. Not only are the models not comprised of 'basic physics', they have been found to violate the 2nd Law of Thermodynamics! 

This new paper finds that various combinations and permutations of the four basic parameterizations/fudge factors that govern convection [which is only one of many poorly-understood major climate variables] result in an astonishing range of climate sensitivity estimates to doubled CO2 levels, ranging from 3C to more than 10C - essentially a range varying by a factor of 3.3 times or more, and of no practical use to anyone including policymakers. And this is only with various fudge factors for convection only, not to mention infinite other combinations and permutations of parameterizations/fudge factors for clouds, ocean and atmospheric oscillations, mixing, gravity waves, etc. etc. that make climate models "close to useless" and "can get any result one desires."

This is why several papers have called for abandoning the very expensive dead end of conventional numeric modeling in favor of statistical approaches and stochastic models, which have demonstrated far superior performance, and at much less cost of computer power. 

Indeed, even a "no change" climate model outperforms IPCC climate models by a factor of seven times!

And even the IPCC itself admits in the fine print that the "parameterizations" in the models are bogus and produce a huge range of climate sensitivities just by changing the cloud fudge factors alone:

IPCC Report (AR4) Box TS.8 : “Although the large-scale dynamics of these models are comprehensive, parametrizations are still used to represent unresolved physical processes such as the formation of clouds and precipitation, ocean mixing due to wave processes and the formation of water masses, etc. Uncertainty in parametrizations is the primary reason why climate projections differ between different AOGCMs [Atmospheric Oscillation Global Climate Models].”

IPCC Report (AR4) 1.5.2 “[Senior and Mitchell (1993)] produced global average surface temperature changes (due to doubled atmospheric CO2 concentration) ranging from 1.9°C to 5.4°C, simply by altering the way that cloud radiative properties were treated in the model. It is somewhat unsettling that the results of a complex climate model can be so drastically altered by substituting one reasonable cloud parametrization for another, thereby approximately replicating the overall intermodel range of sensitivities.

Lastly, here's what esteemed Princeton Professor of Physics and climate scam skeptic Freeman Dyson has to say about climate models:

"I have studied the climate models and I know what they can do. The models solve the equations of fluid dynamics, and they do a very good job of describing the fluid motions of the atmosphere and the oceans. They do a very poor job of describing the clouds, the dust, the chemistry and the biology of fields and farms and forests. They do not begin to describe the real world that we live in. The real world is muddy and messy and full of things that we do not yet understand. It is much easier for a scientist to sit in an air-conditioned building and run computer models, than to put on winter clothes and measure what is really happening outside in the swamps and the clouds. That is why the climate model experts end up believing their own models."

On the connection between tropical circulation, convective mixing, and climate sensitivity

L. Tomassini, A. Voigt and B. Stevens

DOI: 10.1002/qj.2450

Keywords: tropical circulation; convection parameterization; convective mixing; climate sensitivity

The connection between the large-scale tropical circulation of the atmosphere, convective mixing, and climate sensitivity is explored in a wide range of climates through a perturbed-parameter ensemble of a comprehensive Earth-System Model. Four parameters related to the representation of atmospheric moist convection are found to dominate the response of the model. Their values govern the strength of the tropical circulation, the surface temperature, atmospheric humidity, and the strength of the tropical overturning circulation, largely through their influence on the atmospheric stability. The same convective parameters, albeit in different combinations, also have a strong influence on the equilibrium climate sensitivity of the model, which ranges from a little over 3 ∘ C to more than 10 ∘ C. The importance of the most poorly represented processes in determining important aspects of the behavior of the model argues for the need to move beyond statistical approaches to estimating climate sensitivity and focusing on the development of a better understanding and representation of convective mixing, particularly in the tropics.

Related papers demonstrating stochastic modeling outperforms conventional numeric climate models: 

Simple climate model outperforms IPCC models, demonstrates climate effect of CO2 is miniscule

Paper: Global 'warming since 1850 is mainly the result of natural climate variations' 

New paper seeks a grand "unification" of "quite different model physics" of convection

New paper finds sea surface temperatures were controlled by natural 60-year climate cycle during 20th century

How the journal Nature plays fast & loose with the facts about the "pause" in global warming

New paper finds models have a high rate of 'false alarms' in predicting drought

Natural Climate Change has been Hiding in Plain Sight

New paper finds the data do not support the theory of man-made global warming [AGW]

New paper finds a non-linear relationship between sunspots and global temperatures