Why Climate Models Lie
It has come to light that a number of climate scientists have been less than truthful with regard to climate data. As shocking and embarrassing as this has been to the scientific community, it serves only to emphasize the huge blind spot that scientists have for their computer models. It is a career ending offense to knowingly falsify data, yet the entire climate science community engages in even worse deception without a second thought. This is because lies are generated for them wholesale by their faithful yet duplicitous servants: computer climate models.
In a guest post on Roger Pielke Sr.'s web site, Hiroshi L. Tanaka of the University of the University of Tsukuba in Japan, reported on the results of a new paper he published with his student, Masahiro Ohashi (see “Data Analysis of Recent Warming Pattern in the Arctic”). In it they state “it is shown that both of decadal variabilities before and after 1989 in the Arctic can be mostly explained by the natural variability of the AO not by the external response due to the human activity.” While this is an important finding in and of itself, that is not what caught my attention.
The implications of Ohashi and Tanaka's finding for climate modeling are even more dramatic, and even more damaging, for the climate alarmist cause. Why this new finding is so damaging goes to the heart of how modeling is done and how models are calibrated to reflect previously “known” conditions. Here is how Dr. Tanaka stated the implications of their research:
According to our result, the rapid warming during 1970-1990 contains a large fraction of unpredictable natural variability due to the AO. The subsequent period of 1990-2010 indicates a clear trend of the AO to be negative. The global warming has been stopped by natural variability superimposed on the gentle anthropogenic global warming. The important point is that the IPCC models have been tuned perfectly to fit the rapid warming during 1970-1990 by means of the ice-albedo feedback (anthropogenic forcing) which is not actually observed. IPCC models are justified with this wrong scientific basis and are applied to project the future global warming for 100 years in the future. Hence, we warn that the IPCC models overestimate the warming trend due to the mislead Arctic Oscillation.
This mildly worded warning belies the theory shattering implications it contains for all climate modelers who have depended on a strong ice-albedo feedback to calibrate their models. As the old computer programming saying goes, “garbage in, garbage out.” Tanaka has just informed the world's climate modelers that that have been basing their models on garbage. More specifically, what the modelers and climate scientists took for a strong anthropogenically influenced feedback, albedo change due to changes in ice cover, has been shown to be mostly attributable to natural variability.
Comparison of trends in surface albedo from satellite observations and climate models.
In an interview with the UK's Guardian, green guru James Lovelock took the climate science community to task for over reliance on models. As he explained, this blind belief in models, even in the face of contradictory empirical evidence, has been going on for some time now:
I remember when the Americans sent up a satellite to measure ozone and it started saying that a hole was developing over the South Pole. But the damn fool scientists were so mad on the models that they said the satellite must have a fault. We tend to now get carried away by our giant computer models. But they're not complete models...
If you make a model, after a while you get suckered into it. You begin to forget that it's a model and think of it as the real world. You really start to believe it.
As I explained in “Seven Climate Models, Seven Different Answers,” computer models are touchy, cantankerous tools at best. Even the smallest changes in configuration can cause wild changes in model output. Still, we are asked to trust them implicitly.
In 1997, two researchers from Argon National Laboratory published a paper that compared 108 studies of global climate change, each projecting a quantitative impact on global surface-air temperature due to a doubling of atmospheric CO2 levels. These predictions, documented between 1980 and 1995, were based primarily on climate modeling. Writing in Climatic Change, Kavita Kacholia & Ruth A. Reck, found: “[O]ver the past 15 years, the average (mean) temperature change projection due to doubled CO2 is +2.62°C, with a range of 0.16–8.7°C. General circulation models tend to estimate slightly higher values (2.98°C), compared with radiative-convective models (1.98°C) and energy balance models (2.54°C).”
Basically, 108 models yielded 108 different predictions, ranging from almost no change to almost 9°C, a much wider range than the current IPCC projections. Which, if any of them, was the correct? The answer is none of them. And climate models have not improved significantly since then despite a string of discoveries finding new factors or correcting old ones (see “Atmospheric Solar Heat Amplifier Discovered,” “Climate Models Blown Away By Water Vapor,” “New "Jelly Pump" Rewrites Carbon Cycle”and “Conveyor Belt Model Broken” for a start).
It has taken a public scandal—the revelations regarding data from CRU—to alert the media to the use of bad data in making climate change predictions. It should not have been surprising that some at the IPCC have played fast and loose with the data included in their reports (Himalayan glaciers melting, sea-levels rising, etc.). But more pernicious are the lies generated by climate models, models held up to be oracles of scientific truth—and nothing could be farther from the truth. The models lie because they are built on faulty assumptions, calibrated with inaccurate data and are, by their very nature, incapable of calculating “correct” answers.
If the lies being told by climate science were not threatening to cause major disruptions to environmental and economic policy world wide, most people would not care about the self delusional approach taken by climate scientists. This all comes back to the lack of professional integrity among many climate science practitioners, a sloth induced lack of ethical behavior. Letting a model do your lying for you is no excuse. Deception by proxy does not absolve those spreading the untruths anymore than saying “I didn't kill that person, the gun did!” With so much at stake, any sensible person would be skeptical of climate science's computer generated predictions.
Yet those brave enough to speak out about the incomplete theory, the questionable data, and the error prone computer models are called “climate criminals” and “sociopaths.” If the skeptics' response has seemed like denial it is because fools like James Cameron, who know little or nothing of the science yet are in the public eye, threaten to “call those deniers out into the street at high noon and shoot it out with those boneheads.” Rolling Stone magazine published a headline article identifying the 17 worst “Climate Killers” in the US. Fortunately, there are signs that the public has grown tired of these people, the aggressively ignorant, whose inability to explain why they believe in global warming only strengthens their conviction that they are right.
“We do need scepticism about the predictions about what will happen to the climate in 50 years, or whatever,” said Lovelock. “It's almost naive, scientifically speaking, to think we can give relatively accurate predictions for future climate. There are so many unknowns that it's wrong to do it.” Not just an error, not just a mistake, but actually morally wrong. I say morally wrong because there are consequences to these actions—real harm can be done to real people. The whole anthropogenic global warming scare is based on a foundation of computer generated lies. With apologies to NotEvilJustWrong.com, knowingly passing computer predictions off as science fact is not just wrong, it is evil.
Be safe, enjoy the interglacial and stay skeptical.