To the question, “How many …. does it take to change a light bulb?”, there are innumerable answers, a few of them even good ones.
Recent events prompt me to paraphrase:
“How many climate models does it take to get it right?”
After all, the last 15-20 years have seen almost no global warming despite continuing increase in what is supposed to be the primary influence, the concentration of carbon dioxide in the atmosphere; see for instance “Climate scientist: 73 UN climate models wrong, no global warming in 17 years”.
Unsurprisingly, gurus and groupies of the hypothesis of human-caused global warming (AGW, anthropogenic global warming) have come up with all sorts of reasons why this recent lack of warming doesn’t disprove their hypothesis, for example :
“The biggest mystery in climate science today may have begun, unbeknownst to anybody at the time, with a subtle weakening of the tropical trade winds blowing across the Pacific Ocean in late 1997. …. average atmospheric temperatures have risen little since 1998, in seeming defiance of projections of climate models and the ever-increasing emissions of greenhouse gases. . . . Climate sceptics have seized on the temperature trends as evidence that global warming has ground to a halt. . . . Climate scientists, meanwhile, know that heat must still be building up somewhere in the climate system, but they have struggled to explain where it is going, if not into the atmosphere. Some have begun to wonder whether there is something amiss in their models…. That has led sceptics — and some scientists — to the controversial conclusion that the models might be overestimating the effect of greenhouse gases” .
The only correct answer, of course, to “How many climate models does it take to get it right?”, is that it takes either none or an infinite number of climate models to get it right, because it is impossible for any number or array of computers to take into account all the variables and their interactions including feedbacks both positive and negative.
Models are research tools. Modelers try to find variables that combine to deliver results that mimic what is actually observed. The only test is against the real world. The only available data are what has happened up to the present. But it is elementary that the past is no guarantee of the future when it comes to human knowledge: not when it comes to believing that all swans are white, or that any given mutual fund outperforms all others, or anything else, including climate models — there is no guarantee that unknown or neglected variables will not become significant in the future. The past can be a fairly reliable guide only empirically, extrapolating actual real-world events, not merely human interpretation of or theories about those events: we can be fairly confident that the sun will (appear to) rise regularly in the east every 24 hours (or so), and that the succession of ice ages and warm periods experienced by the Earth will continue their cycles at about the same intervals (~150,000 years during the most recent million years).
Climate models are no more than research tools. They are inherently, inevitably, incapable of making reliable forecasts (recall always Michael Crichton’s wise words on consensus and prophecy .
Most of the arguing over the significance of the lack of atmospheric warming in the last couple of decades has been beside the point, arguments over whether it shows that long-term human-caused global warming (AGW, anthropogenic global warming) is actually occurring or not. Few moments of thought are needed to concluded that a couple of decades is insufficient to decide that. A mere smidgeon of knowledge of uncontroversial historical data suffices to recognize that global warming of about 5-6oC in the next 75,000 years or so is predictable since the Earth is just emerging from the last Ice Age, of which there have been 7 or 8 in the last million years. One of the obvious points against all current climate models is that the causes of these cycles are not understood and are therefore missing from the models.
The real point is that, since all the models have been wrong for the last couple of decades, therefore the models are faulty: “the most important point: the climate models that governments base policy decisions on have failed miserably” .
All official climate models have been definitively discredited. It follows that their predictions are not worth attending to.
How many Internet pundits does it take before one finds a reliable opinion?
I’ve remarked before on the pervasive unreliability of Internet stuff like Wikipedia  or Facebook . There are a few useful sources only among the mass of rants by people who don’t know what they’re talking about but who parrot mainstream views as though those were Gospel Truth. So, for example, “Skeptical Science” had this to say :
“Climate models have to be tested to find out if they work. We can’t wait for 30 years to see if a model is any good or not; models are tested against the past, against what we know happened. If a model can correctly predict trends from a starting point somewhere in the past, we could expect it to predict with reasonable certainty what might happen in the future”.
Utterly, fundamentally, indubitably wrong on one of the most elementary points about models and what past performance cannot with assurance say about the future. Models are constructed by using past data, so of course they “predict” what happened in the past.
This particular pundit flaunts apparently expert status — “Skeptical Science is maintained by . . . the Climate Communication Fellow for the Global Change Institute at the University of Queensland” — while also disclaiming any authoritative knowledge: “There is no funding to maintain Skeptical Science other than Paypal donations — it’s run at personal expense. . . . [and] has no affiliations with any organisations or political groups. Skeptical Science is strictly a labour of love”.
The correct answer, of course, to “How many Internet pundits does it take before one finds a reliable opinion?”, is that unless one already knows a lot about a subject, the Internet is far more likely to mislead than to give reliable guidance.
How many Science Advisers does it take to deliver reliable advice?
It takes only one, provided it’s someone who understands what they’re doing.
Unfortunately, Presidential Science Advisers have so far always been scientists  with inadequate understanding of history of science and the nature of scientific activity and who therefore characteristically overestimate the trustworthiness of whatever the prevailing mainstream consensus happens to be. History is perfectly clear that science has always progressed by finding flaws in the mainstream consensus, modifying it or even overturning it completely . The greatest achievements that we honor in retrospect were contrary to their contemporary mainstream consensus and were resisted, often fiercely and sometimes viciously, when they were first proposed . To be potentially effective, science policy would need to be deeply informed by the maturing body of scholarship in Science & Technology Studies (see The progress of science and implications for Science Studies and for science policy; and A consumer’s guide to Science Studies [large file, takes a minute or more to download]).
Roger Pielke, Jr., has written soundly and sensibly of the proper role of scientists toward policy making: they should be honest brokers , delivering to decision makers the most unbiased, well informed, judicious summary of all the understanding and insight reflected in the various and often differing views of competent researchers.
The current Presidential Science Advisor is scandalously lacking in those desiderata: John Holdren’s epic fail.
How much contradictory data does it take to change a mainstream consensus?
It takes a lot more now even than it used to in the past. Max Planck, Nobel Prize for Physics (1918, quantum theory) is inevitably cited in this connection for the insight that new theories do not become accepted by convincing the mainstream but only as the old-timers pass away and a new generation takes over; science advances, in other words, one mainstreamer funeral at a time. Nowadays, outside interests have become so vested in scientific issues that it will take something like a social or political revolution to displace hypotheses like human-caused global warming .
 Jeff Tollefson, Climate change: The case of the missing heat — Sixteen years into the mysterious ‘global-warming hiatus’, scientists are piecing together an explanation, 15 January 2014; Nature 505: 276-8 ; doi:10.1038/505276a
 Michael Crichton, Aliens cause global warming, Caltech Michelin Lecture, 17 January 2003; also in Three speeches by Michael Crichton
 95% of Climate models agree: The observations must be wrong
 Beware the Internet: Amazon.com “reviews”, Wikipedia, and other sources of misinformation; The Fairy-Tale Cult of Wikipedia; Another horror story about Wikipedia; The unqualified (= without qualifications) gurus of Wikipedia; Lowest common denominator — Wikipedia and its ilk
 Facebook: As bad as Wikipedia, or worse?
 Getting Skeptical about global warming skepticism — How reliable are climate models?
 Pp. 37-8 in Henry H. Bauer, Scientific Literacy and Myth of the Scientific Method, 1992
 Thomas S. Kuhn, The Structure of Scientific Revolutions, 1970
 Bernard Barber, Resistance by scientists to scientific discovery, Science, 134 (1961) 596-602
 Roger A. Pielke, Jr., The Honest Broker: Making Sense of Science in Policy and Politics, Cambridge : Cambridge University Press, 2007
 Henry H. Bauer, Dogmatism in Science and Medicine: How Dominant Theories Monopolize Research and Stifle the Search for Truth, 2012