It isn't if you aren't a scientist in that field. As you're not qualified to do otherwise.
As a physicist in quantum sensing. I follow the science (opinion) of climate scientists as they're the experts of that field. And that opinion is constantly evolving, but I follow that.
Anything else is just being an armchair scientist.
That's called gatekeeping. Wonderful opinions can come for anyone.
A scientist is someone who found someone to pay them. Nothing more, nothing less.
Ignoring ideas unless they came from a brand is the opposite of science. Then you drop your brand (physicist) and expect others to judge your opinion as more important. It didn't work. As a senior physicist in quantum sensing I'm invalidating your brand.
Are these scientifically founded opinions. Not necessarily, hence why "following the science" is valid if you are following experts in their field.
If you're a software consultant, would you take on the opinions from a marketing client on the best algorithm to implement for their solution? Probably not.
If someone put in the effort and time to throughly research the topic and draw an opinion from that. Regardless of their title or their funding, then why would you discount it?
If it was a better algorithm - then of couse. You wouldn't be a very good software engineer (or scientist) if you couldn't recognise that.
This has veered off from my original point. In that saying "follow the science" is not a issue - there is nothing wrong with following the opinion of experts in their field.
Climate models are fundamentally physical, but I don't have the insight in the field to have the deep insight to make qualified opinions.
I could after significant research as suggested. But that is a significant endeavour, hence following the opinion of the field is typically sufficient.
It's like a fronted developer making comments on kernel development and vice versa. It's both fundamentally code, but different fields.
I think if you’ve looked at numerical models then you have enough knowledge to at least judge the underlying assumptions: boundary conditions, numerical stability, discretisation methods, validation methods and results.
In the same way that I can verify a SAT solution, I don’t need to know how to code a sat solver.
Unfortunately there are fundamental disagreements about most of the critical parts of climate science, so going by the opinion of the field isn’t foolproof (who to choose? How to choose?). Many fields have had false consensus beliefs before, and most of their problems weren’t 1000th the difficulty of climate modelling.
This is true, but there are no biological simulations in the mainstream models, just various correction factors with their own uncertainty. I wish they had biological data because then we would have more domains in which to measure their accuracy.
As a physicist in quantum sensing. I follow the science (opinion) of climate scientists as they're the experts of that field. And that opinion is constantly evolving, but I follow that.
Anything else is just being an armchair scientist.