Professor Nicola Scaffeta of the University of Naples Department of Earth Sciences has just published a detailed, peer-reviewed assessment of the latest generation of global climate models. He begins by noting that there are about 40 major climate models and their climate sensitivity levels vary by a factor of three, from 1.8 to 5.7 degrees C per doubling of carbon dioxide. Which right away tells you there is a lot of guesswork going on. He groups the models into low, medium and high sensitivity categories and asks a simple question: how well did the models do at reproducing the warming from 1980 to 2021? Specifically, he computes the average temperatures around the world from 1980 to 1990, and again from 2011 to 2021, and asks how well each model did reproducing the pattern of changes. Which is about as basic a task as we expect the models to be able to do since the scientists get to see the answer when they’re programming the computers. Even so, they get it badly wrong, though the low-sensitivity models come closest to reality.
There were two aspects to Scafetta’s assessment, which we will discuss this week and next. One test looked at how well the models could reproduce the spatial pattern. That is, instead of just being able to say how much global warming occurred (which they don’t do well at), could the models correctly say where the warming would be stronger and where it would be weaker. And the answer is no.
Among the high sensitivity models they got the pattern wrong over 80 percent of the Earth’s surface. As in, they predicted changes that were significantly different from the observed changes in over 80 percent of the land and ocean surfaces. The medium sensitivity models did better, but they were still wrong over 68 percent of the Earth’s surface. Finally the low sensitivity models did the best, but they were wrong in 60 percent of the Earth’s surface.
As we will discuss next week, Scafetta doesn’t shy away from pointing out the policy implications of his results. The climate panic is not based on projections from the low sensitivity models. Even under high emission scenarios those ones don’t predict much warming. The panic is based on the projections of the high sensitivity models, which get everything wrong. As we’ll see next week, they not only fail to get the spatial pattern correct, they are especially wrong at the global warming trend itself.
Alarming.....we can’t power EVs with current infrastructure limitations, yet we base the need gor EVs upon data empirically refutable. Are science degrees nowadays worth anything at all?
I'm curious why the study was split into two parts, and not equal parts at that. Does it change the results? I can't imagine how it would and yet I worry that it's partitioning might be used to discredit it...
Lee, you don't cast your net wide enough. You should be asking whether a university degree is worth anything anymore. (I have 4 of them, but most of my learning was done on my own.)
Again Lee percents a question that is paramount. Governments are making decisions that negatively affect their citizens on models that almost any thinking person know are ......false
I watch a young meteorologist on YouTube doing weather forecasts using several different models. I understand that climate and weather are not necessarily the same thing on a day to day basis; it’s his comments about the models I find interesting. The weather models he uses are typically accurate for the most part, yet he always stresses some unpredictably even with data streaming in from satellites, radar, balloons, ocean buoys, local observers, and all the rest, he still cannot be entirely sure about a weather event, especially an extreme event like a tornado, until it’s actually happening. And yet, somehow, climate models are actually predictive of global scale disasters a decade hence? So much rubbish, fortunately more rational scientists are starting to resist the climate alarmists, Trudeau’s virtue signaling may yet spiral into the infamy it deserves.