> Your response is you don’t understand it so nobody else should.
Ah I see. I misinterpreted the _you_ in this sentence (to mean me).
My main points still stand though:
1. weather is well understood to exhibit chaotic behavior (in the technical sense, not the colloquial sense)
2. there is an upper bound to accurate (edit: precise) weather forecasting the farther you predict into the future
As an aside, there was no need to get personal. I wasn’t the downvoter but that is very likely why the comment got flagged.
You've done nothing but be personal, complaining that it's being returned is hypocritical. You started making personal comments, not me.
> 2. there is an upper bound to accurate (edit: precise) weather forecasting the farther you predict into the future
Quick, everyone, halt all the research into weather prediction, we've already found all the answers. There's no need to look any further, none at all.
Actual answer: Currently we use a statistical model, that (as I previously pointed out currently degrades after about 3 days into the future)
There's absolutely nothing preventing us from making that more accurate, with better models, and algorithms (as I have been saying from the start)
I get that you don't have any understanding of the way that human knowledge is acquired, but that's no reason for you to jump on the internet and yell at people who do.
(Someone should tell Edison to stop at the 90th attempt of his lightbulb, it's clear that there are no answers to the problem he is faced with)
I don’t see how disagreeing with you constitutes “a complete and utter lack of grasp of the subject”. That’s hyperbole.
So your claim is that the state of the art weather models are accurate at somewhere between 24h and 2 weeks (unclear based on the other sub threads) and continually improving. Based on this you extrapolate that given enough compute and sensors it would be possible to predict the weather with the same accuracy a month or more out. I think that’s a reasonable claim assuming that (1) the behavior of the system is deterministic and (2) the system behaves the same at both time scales.
Setting (1) aside, I claim that (2) is a wrong assumption. That weather exhibits chaotic behavior and that this likely puts an upper bound on prediction accuracy and the upper bound is less than 1 month.
The state of the art appears to be GraphCast [1] and FengWu [2]. These show promise out past 2 weeks when run against historical data. However, neither model is making actual weather predictions, and both are still in preprint (e.g. methodology has not been peer reviewed). This is super interesting and it’s possible my claim is incorrect, and that the upper bound is further out than the conventional 2 week limit.
> I don’t see how disagreeing with you constitutes “a complete and utter lack of grasp of the subject”. That’s hyperbole.
Your complaint is that I am applying your measure with the same effort that you did to me.
The current upper bounds are constantly being reviewed, just as with other active areas of research. With that in mind, we don't really know what the final upper bound might be, we can only say with any semblance of surety that the upper bound at any given point in time is limited by our imagination (read: our ability to create new and possible novel ways to model the future)
Ah I see. I misinterpreted the _you_ in this sentence (to mean me).
My main points still stand though:
1. weather is well understood to exhibit chaotic behavior (in the technical sense, not the colloquial sense) 2. there is an upper bound to accurate (edit: precise) weather forecasting the farther you predict into the future
As an aside, there was no need to get personal. I wasn’t the downvoter but that is very likely why the comment got flagged.