There are no error boundaries or even attempt at giving meaningful estimation of the error in these calculations, in fact, the various models disagree quite wildly in the sense that after accounting for variation between models, you're left with barely a weak directional claim.

There's also a significance difference between predicting global climate, and estimating with accuracy the CO2 forcing. While the global temperature is at least measurable, nobody has any way to test CO2 forcing meaningfully. Which is the entire claim.

The reason for the decision to move trillions of dollars is the prediction about CO2 forcing, but if it is wrong and we're going to rely on "renewable energy" a.k.a. wind and sun when we are currently forecasting they are going to be unreliable, that's suicide. You can even worry about whether it is the correct decision even if the entire uncertainty was geopolitics by the way. In fact, just the unpredictability of China alone is enough to put the entire policy of the west in huge doubt, but that's something else.

> This is just you repeating what you said before. The code quality is not relevant unless you point out a bug.

I literally just pointed out several bugs. These things are not constant, they depend on these parameters, you're going to accumulate huge errors if you don't take them into account, and even worse, you're going to completely miscalculate CO2 forcing if you have entire sections of your code which ignore CO2 forcing (by having "constants" that aren't constants at all but depend on CO2).

And again, you're projecting from a real science (astrophysics) where you can point your telescope anywhere you wish and collect data, which is worth millions of bits, to climate science where the only "data" is very few temperature measurements which need to be averaged to retain a very weak signal. But on the other hand, nobody dies because they got astrophysics wrong (except in "Don't look up" movie)

It's not science. They hardly have any data points fitting their models compared to the size of these models and the variation in their results, and most importantly, they don't have any data on the central claim (CO2 forcing) at all. My argument is basically, nobody can trust the story because stories are misleading, you need a detailed calculation. Not misleading in a conspiratorial way, misleading in that this is numerical question which we humans suck at estimating narratively.

And again, those calculations could and should be much less of a dumpster fire if we're going to trust the future of humanity with them. Another example of "simplifying assumptions" blowing up in the face of the economy was 1987 stock crash where "simplifying assumptions" in modelling option prices blew up in everyone's faces and led to multi year recession. And another "simplifying assumption" in the coronavirus response led by misleading infection models and proceeding ahead out of pure cognitive dissonance. I'm sure the climate modelers are doing the best they can, but the best they can is not enough.

This dishonesty about the certainty of models, which usually results from a broken telephone where the honestly and articulated science claims are transformed into propaganda that misleads even the leaders is a bigger problem than what these models claim to solve.

If this blows in everyone's faces and "moving to renewables" turns out to be a complete disaster, they will be hanging scientists in the streets and I won't blame them. Everyone's maximizing for the "scientists were extremely accurate in their predictions and we listened to them and got it right" scenario and it's because in everyone's mind the probability the scientists are right is like 90% when in reality it's more likely 10%.

I don't want to convince you it's wrong. I want to convince you it's very non-trivial calculation to understand whether the problem is CO2, that framing it as "scientists always knew that and it's basic physics" is extremely misleading about the certainty, and that the narrativistic mindset is extremely dangerous.