NOT SO GREEN  |  " Modeled " versus Reality

By Steven Keeler | Jun 29, 2017


Pronounced differences - 2017 : A key quote

Our results are also broadly consistent with recent analyses of Cheung et al. [2017], who documented substantial mismatches between their estimated internal components of the observed and CMIP5-simulated AMO **, PMO **, and NMO ** variability. However, these authors used subtraction of the scaled CMIP5 **  MMEM ** signal to deduce the internal variability in historical simulations of individual CMIP5 models. Kravtsov et al. [2015] and Kravtsov and Callicutt [2017] showed that the residual variability so defined misrepresents the true internal variability in CMIP5 simulations and is, in fact, dominated by model error, that is, the differences between the true forced response of individual models and the MMEM response. The magnitude of the CMIP5 “internal” variability estimated by this method is, hence, much larger than that of the true simulated internal variability, and the spectral characteristics of the true and estimated internal variability are entirely different.





** Atlantic Multi decadel Oscillation,  Pacific Multi Decadel Oscilliation,  Northern Multi decadel Oscilliation,  Coupled Model Intercomparison Project phase 5Multi-Model Ensemble Mean


The paradigm of postmodern  " Science.Inc "  considers climate model outputs to be superior to physical facts.

If there was ever a point of real evidence for calling global warming a scam it is these climate models. It is an inherent part of developing computer math models that you correlate to real measured data when it becomes available. The fact that these models are not correlated to real data makes them a joke in the minds of anybody with common sense, but the fact that predictions of these models are quoted as part of justification for generating climate study related income through grants and book publishing on the subject, etc, makes many of us think of global warming as a scam. A scam in that people are deliberately trying to fool others into thinking they need to spend more money on global warming related studies and policies than is necessary. Like a pest control company deliberately showing you data that exaggerates the amount of pests in your neighborhood and the consequences of not buying their pest control services. It is completely unethical and a scam. The proof is right in our face, but the media never talks about it. In all the hundreds of news media stories on global warming I have NEVER seen a graph showing measured global temperatures ( UAH, RSS )  plotted versus time, much less against climate model predictions, but I have heard the vacated 97% consensus study mentioned in almost all of such articles.


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