08-07-2019, 07:23 PM
(07-29-2019, 12:48 PM)Dill Wrote: 2. the foundation of the above debate rests upon one in the science community and their ongoing research. Here debate is minimal over the skeptical theses that drive #1. That is why it is so hard to find climate scientists who challenge the AGB thesis, though they may argue over how to measure it. But this debate is hard for the public to follow, and that will include most of us posting here.
I asked you to go google ECS and then look at where IPCC gets there values from. The IPCC takes those values primarily from the climate models. That's inherently problematic. The long and short of it is the science DOES NOT reject the default assumption of low climate sensitivity, which as I already pointed out is most likely between 1 and 1.5 based on the actual temperature data. But then the climate alarmism falls apart, and with it a giant deflation of a $2T+ industry (among other things).
Those models aren't validated. That's the hugely critical difference between data mining and science. If their models had actual power, if they could be validated, they would do so with out-of-sample testing. At a high-level, their model development has a computer chug thru different linear combinations for parameter estimates until it fits the data within the different constraints. There's not a unique solution, which is why the IPCC uses something like 70 different models. And there could be many more, so the range of ECS estimates is driven by assumptions and preferences of the modeler (or more deliberately, putting one's "thumb on the scale). Many, many ways to bias a model, unintentionally or not, which is why validation is critical.
In other fields, assumptions and forecasts that come from an unvalidated model are dismissed out of hand. The model is almost certainly wrong and certain to fail, so such research is a total non-starter. I'm sure you won't believe me, but check out pages 2&3 of this UChicago link - this is what I've always said when referring to the fundamental building block of this as junk science:
http://jtac.uchicago.edu/conferences/05/resources/V&V_macal_pres.pdf
I'm sure you can find a lot of justification and explaining away the need to validate climate models. But you need to pay very close attention to what is being said. That a model matches the observed data is meaningless - it was forced to fit the data. Plugging in new, observed values and getting an accurate forecast is a different model - the actual model had a wrong forecast/simulation for those variables because only CO2 is considered external forcing. Fitting the model to include the new data is a different model (i.e. "re-tuned").
So in summary climate alarmism is not based on science, but on data mining (likely to produce a pre-determined result).
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