attribution, like consensus, should never be part of science
Patrick Brown, a courageous climate scientist who has previously blown the whistle on publication bias in climate science is out with a new essay blowing the whistle on the many layers of bias in “Extreme Event Attribution” (EEA) in science journals
Never heard of EEA? You will, because the scientist-activists who invented the field have intended all along to use it as a legal weapon to shut down the energy industry.
Wait, you cry. Don’t scientists invent new methods and new fields of study to discover the truth whatever it might be?
Pffff. As Brown points out, the EEA crowd makes no secret that what they’re after isn’t to discover the truth, it’s to win lawsuits.
And to do so they have come up with a winning formula that pumps out studies that get massive media attention and reliably give the impression that ‘climate change’ is making extreme weather worse.
The problem is the data shows the opposite, and even the IPCC don’t agree. So how does EEA science end up concluding the opposite of what the science is supposed to say? By supplementing publication bias with a very strong trick called selection bias.
Brown outlines a series of filters that help ensure EEA papers are having the intended effect on public perceptions.
The first is “occurrence bias”, in which EEA scientists only study climate events that happened, not ones that didn’t, so they have what looks like a 100 percent success rate connecting ‘climate change’ to extreme events.
Which might sound reasonable since science is about facts. But it is a fact that extreme events do not happen in some places, and a proper theory would explain why not instead of rushing to the places they did.
Second, “choice bias” means researchers may know in advance what types of events are more likely to have a ‘climate change’ connection, so if they lean towards studying those events they will be able to report such connections more often.
But if they then imply that all extreme events are increasing, or are climate-driven, they’re cheating.
Third, “publication bias” occurs when journals favour publication of papers that find big hazards from ‘climate change’ and scientists oblige by tilting their findings in that direction. Which is a phenomenon Brown knows all about from his own experience.
Finally there is “media bias“, in which the news media only writes about studies that promote the alarmist message. And EEA types know it, and lean on it.
Brown illustrates the first step, occurrence bias, with a remarkable map connecting EEA studies on drought to indications of changing drought frequency around the world:
This map shows, based on a climate model simulation, places where ‘climate change’ will increase drought occurrence (red) and places where it will decrease it (blue). And indeed on average, according to the study, droughts are expected to become a bit less likely for the world as a whole.
But now look where the dots are. They represent where EEA scientists chose to study drought events. Amazingly almost all the dots are in red areas. Brown explains the result (emphasis in original):
“The result is that the EEA sample is majorly biased: warming decreased the intensity of once-per-50-year droughts by about one percent overall, but it increased their intensity within the EEA sample by 18 percent!
Thus, if you just relied on the EEA sample, you would come away with an incorrect impression not only on the magnitude of change in extreme droughts but also on the sign of the direction of change!”
Brown also gives the example of a study that looked at a set of recent hurricanes and concluded that ‘climate change’ made all of them a full category more intense. Which of course got massive worldwide media attention.
Yet, Brown notes, hurricane experts have shown that ‘climate change’ will have contrasting effects on hurricanes, including making them less frequent overall. And large-scale data analyses show that total hurricane numbers are declining worldwide as is average intensity.
So how does the EEA crowd end up saying the opposite? Simple, Brown explains, they only examined hurricanes that happened, rather than also looking at ones that didn’t because in that region they had become less common.
Moreover, they only looked at the role of factors that are known to make hurricanes more intense.
They deliberately didn’t study the cases in which a hurricane might have happened but didn’t because the warming climate prevented it.
And they didn’t look at the influence of factors that have tended to weaken hurricanes. As a result their conclusions were baked in before the study even began.
Making them unscientific and worthless. And meaning that however much you mistrust “climate science”, it’s not enough.
See more here climatediscussionnexus
Bold and some italic emphasis added
Editor’s note: you can attribute any event to any cause, but that is an opinion, not a fact. I could attribute the fact I have one cat to the fact my neighbour has one child, but that doesn’t mean one caused the other.
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It all balances on public ignorance. Were the public to be interested enough obtain the real truth, the whole thing would collapse, but looking at graphs ia not love island, is it…
Even the climate change pushers just regurgitate what they were told without verification, and they are the messengers.
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