The Great Narrative: Hot model and hot mess – The rapid decarbonization of our world.

Hot model and hot mess from bias climate scientists?

Some climate scientists have reacted to my previous video about climate sensitivity. In this video, Sabine Hossenfelder elaborates on my thoughts regarding the IPCC's projections and why it worries me how they are dealing with the uncertainty of the climate model outputs.

More in the Sabine Hossenfelder video.

Comments in the video:

@jeremywilliams5107: ""Typical behaviour associated with system accidents includes:

1) initial incomprehension about what was failing; 2) failures are hidden or masked; 3) concentrate on the minimum necessary explanation, and discount the worst case as being impossible; 4) business as usual if at all possible; 5) mistrust of measurements; 6) overconfidence in the function or later appearance of any safety device; 7) any ambiguous information is interpreted so as to confirm the minimum necessary explanation; 8) time constraints in the propagation of the problem and the availability of vital consumables consumables; 9) doing things in response that cannot be undone." Charles Perrow, Normal Accidents"

@Mystery_G: "The best thing about this century thus far has been how much the vastness of humanity has proven how easily propagandized, manipulated, and controlled we've been."

@docwhammo: "The system never sees itself... just like the fish never see the water they swim in."

@MM3Soapgoblin: "I think one issue with climate science is there is a cult following of fanatics and politicians using it for political agendas that don't really have anything to do with climate. My PhD is in physics, like Sabine, but I used to follow climate science research as a hobby and interest. I made the mistake of pointing out an error in the conclusion of a published paper a few years back and was personally attacked as a 'climate denier' and even had people calling my university and workplace trying to get me fired. That sort of hostility towards scrutiny and questioning of results is certain to corrupt and taint the field entirely."

@pirobot668beta: "I built apparatus for psychology research in the 1980's... 'publish or perish' dominated the field. It seemed that many researchers were more concerned with the attractiveness of a subject. If a News story about recovered memory was hot, suddenly 1/3 of the people in the department were trying to become memory experts... The 'penalty' for not winning a popularity contest was to lose your funding... so people chased silly things."

@johnjamesson6751: "It is so difficult to walk the line between: 'science is the best method we have for understanding the world' and 'science is carried out by human beings, and so it will always have flaws caused by selection bias, confirmation bias, perverse incentives and corruption.'"

@markdeffebach8112: "the difference between measurements and modelling is that one involves interpolation where as the involves extrapolation. Extrapolation is inherently unstable where as interpolation is stable. The hotter the model (prognosticator) the more unstable are its predictions."