Quote:
Originally Posted by Sundancefisher
You don’t see that the computer models self test and fail everytime. So in the end you don’t need to prove them false.
Problem is each one gets media airtime and adsorbs to human brain assumptions. Then the false mental impression is hard to erase.
Plus they generate new variations constantly so no one can keep up.
As for the later comment. Not a single scientist who wants funding dares to come right out to declare man is safe.
The tight circle of believer peer reviewers also fix that worry.
Yes. Funding is very political and I don’t blame them for adding a last minute comment how they’re a believer.
Do what you need to be paid. Peer bashing and bullying is well documented in this area of study.
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How does a mathematical equation self test?
if I have a (grossly oversimplified) climate model that states the average temperature (T) = Solar radiation (r) / thermal emission potential of the earth (e), how can it fail itself?
That model would allow me to predict changes in temperature based on changes in solar radiation or thermal emissions. the only way I can find out if it's accurate is to calculate it and compare it to actual observed data.
I've only read observational comparison papers on CMIP5, and they tend to broadly support it, though it doesn't seem to do seasonal changes well. (A study of Argentinian rainfall, for example, found that CMIP5 under/over predicited based on season, but predicited average annual rainfall relatively accurately).
As for the fear of publishing dissenting data, I've never really bought that argument. Science can be vicious, and bullying definitely happens. It hasn't, however, stopped funding and publishing of dissenting papers in other branches - it just means that dissenting papers need to have stronger data to weather attacks. A garbage paper could get by a soft peer review, but good data still leaves hostile peer reviewers pretty much helpless.