Was the use of the Bayesian approach merely climatologists’ way of improving communication between experts and the public? Or, was it a way to undermine the public’s confidence in the usefulness of the scientific method?
We can see very clearly that when it comes to having an intelligent discussion about global warming cum climate change cum disastrous climate disruption (and now ‘global weirding’) that it is communication itself that has been the most undermined. And, just how was it ever to be believed by anyone that simply abandoning the scientific method was ever going to further inspire humanity’s hope of overcoming fear, superstition and ignorance through knowledge?
Certainly no one really believes that a hope for improved communication lies behind a desire to rebrand ‘global warming’ to ‘climate change’ to ‘disastrous global climate disruption.’ We’re actually seeing a desire on the part of climatologists to gin-up hysterics over short-term weather-related events to take advantage of superstition and ignorance, right? God forbid the global warmng alarmists would ever be held accountable and just say what they believe–i.e., give us control of your economic future and you will get weather that is same old same old and not weird.
AGW True Believers simply assume global warming is manmade. There are no peer-reviewed studies that rule out ‘natural, internal climate cycles’ — i.e.,‘natural, internal variability’ — as the real cause of 20th century warming.
And, that is the ‘null hypothesis’ of global warming. The ‘null hypothesis,’ according to Dr. Spencer, has never been rejected, i.e., “THAT NATURAL CLIMATE VARIABILITY CAN EXPLAIN EVERYTHING WE SEE IN THE CLIMATE SYSTEM.” ~Dr. Roy Spencer, 2-Feb-2011 [Emphasis added]
Natural climate variability is the null hypothesis. No one has ever ruled it out. They have only come up with a potential alternative explanation, which is fine. But it is being advertised as some sort of ‘proof’, which it is not. (Ibid.)
It is insanity to believe otherwise. Just during the lifetimes of most of us here, how can anyone simply rule out the AMO (Atlantic Multidecadal Oscillation) as a primary driver in the climate system since 1979?
Whether it is global warming or global cooling circulation changes are always happening. “All I am saying is it can also occur on multi-decadal time scales. How do YOU explain the Medieval Warm Period? Too many SUVs? Or the Little Ice Age? Too few SUVs? Or just deny they ever happened?” (Ibid.)
It makes no sense that we can increase the precision of current information by augmenting it with prior information in a Bayesian analysis when we know that all of the information, past and present, has been corrupted. Whereas some of the corruption is result of demonstrable fraud and incompetence the ubiquitous UHI (Urban Heat Island) effect is pervasive across the land-based temperature record and very telling of a wilful and purposeful deception on the part of the climate mechanics. A Bayesian analysis cannot make bad data relevant. God-in-garbage-out–GIGO–i.e., you can’t turn a pig’s ear into Flammkuchen. And, the most recent and most accurate data we have ever had–based on information gathered using satellites–shows that the oceans have been cooling for more than a decade.
Moreover, it is the Likelihood Principle that is embodied in the Bayesian approach that flips the science of global warming on its head to begin with. “The inconvenient truth remains,” according to Philip Stott, that “climate is the most complex, coupled, nonlinear, chaotic system known.” Like flipping a coin it will not matter if we devise a mathematical model to combine the data of the last 100 flips with a dataset reflecting the 100 flips before that — or even if you want to consider how many tails you got on the previous 1,000 flips — the odds for the next flip still will be 50-50.
Unless we are purposefully trying to deceive the public the Bayesian approach will never be useful in the field of climatology. It will never provide us anything more than perhaps some insight into the probability that an exceedingly unlikely event may happen. But, how much help is that? For example, while it may not seem very likely that we at this very moment are on the precipice of the next Ice Age, it nevertheless is very likely that all life on Earth will someday face just such an event. However, whether or not Bayesian statistics may help us appreciate that fact when it actually does happen, we still will be left with this conundrum: when it happens there will be nothing any living thing on Earth can likely do about it.