3 ms·

Forecast models predict 7 to 14 days ahead. They have not and never will be able to predict further than that. We don't even need them to.

zsims 2y ago
We do, I want to know if it's going to rain on my birthday
unsupp0rted 2y ago
Never will? I wouldn't be surprised if predicting climate + weather 12 months out is a simpler problem than most medical problems at which AI is currently being pointed.
- JumpCrisscross 2y ago
  > wouldn't be surprised if predicting climate + weather 12 months out is a simpler problem than most medical problems at which AI is currently being pointed Simple systems can be famously unpredictable [1]. Our bodies manage entropy; that should make them complex but predictable. The weather, on the other hand, has no governors or raison d'être. [1] https://en.wikipedia.org/wiki/Three-body_problem https://en.wikipedia.org/wiki/Three-body_problem
  - tomjakubowski 2y ago
    The three body problem lacks a closed form solution. How does that mean it's unpredictable, though? I thought that numerical methods can be used to make n-body predictions to arbitrary precision. Are these simulations less accurate than I am thinking? How do engineers and scientists working on space probes plan their trajectories and such?
    - JumpCrisscross 2y ago
      > numerical methods can be used to make n-body predictions to arbitrary precision Arbitrary precision, not arbitrary length. Even "from [a] mathematical viewpoint, given an exact initial condition, we can gain mathematically reliable trajectories of chaotic dynamic systems" to only a "finite...interval" [1]. (This is due to "numerical noises, i.e. truncation and round-off error, where truncation error is determined by numerical algorithms and round-off error is due to the limited precision of numerical data, respectively.") For a physical system like the weather, uncertainty "mainly comes from limited precision of measurement," though there is also the "inherently uncertain/random property of nature, caused by such as thermal fluctuation, wave-particle duality of de Broglie’s wave, and so on." [1] https://www.sciencedirect.com/science/article/abs/pii/S1007570413003109 https://www.sciencedirect.com/science/article/abs/pii/S10075...
      - echoangle 2y ago
        Finite interval doesn’t mean it can’t be arbitrary. I’m not saying it can be in this example but your counterpoint doesn’t follow from the quote. For example, I can calculate the Fibonacci sequence to an arbitrary length but not infinite.
        JumpCrisscross 2y ago
        > Finite interval doesn’t mean it can’t be arbitrary Skim the paper. Numerical noise means you cannot calculate the 3-body problem to an arbitrary length. There is a finite, mathematical limit even with perfect knowledge of initial conditions.
        echoangle 2y ago
        Isn’t the paper about the uncertainties that inherently exist with physical systems? There isn’t any claim that mathematically exact starting values can’t be propagated with arbitrary precision to arbitrary length, and I would claim that this is possible (but not practical due to compute being limited, of course). But there’s no hard limit of precision and length where a simulation can’t be made if the starting conditions are exact. The point of the paper is that starting conditions are never exact which limits the length you can propagate.
        JumpCrisscross 2y ago
        > Isn’t the paper about the uncertainties that inherently exist with physical systems? It talks about that. Which is relevant when we're talking about the weather. But it opens by discussing the hard mathematical limits to numerical methods. > there’s no hard limit of precision and length where a simulation can’t be made if the starting conditions are exact Wrong. Read. The. Paper. Numerical methods for chaotic systems are inherently, mathematically uncertain. Beyond a certain number of steps, adding precision doesn't yield a more precise answer, it just produces a different one. At a certain point, the difference between the different answers you get with more precision covers the entire solution space.
    - strls 2y ago
      You can solve to arbitrary precision but you can't measure and specify initial conditions to arbitrary precision, making the solution wrong outside of a small time interval.
      - JumpCrisscross 2y ago
        > can solve to arbitrary precision but you can't measure and specify initial conditions to arbitrary precision Even with perfect knowledge of initial conditions, numerical noise limits the forecast interval.
- akira2501 2y ago
  In order to predict the climate you need to predict volcanic eruptions. Good luck.
- wongarsu 2y ago
  Predicting that next December will be cold, sure. Predicting how cold or how much rainfall or snowfall there will be in next December would be difficult, but you could get in the right ballpark. Predicting in which week it will snow a year from now? Not a chance.
JumpCrisscross 2y ago
> have not and never will be able to predict further than that Is this a chaos theory prediction? Why 14 days?
- akira2501 2y ago
  Exactly. https://press.uni-mainz.de/the-limits-of-weather-forecasting-how-far-into-the-future-can-we-look/ https://press.uni-mainz.de/the-limits-of-weather-forecasting...
aithrowawaycomm 2y ago
The point is that the underlying physics of classical models should still hold true as the climate changes - and where they don't hold, we will have causal insight as to why. But this isn't necessarily true for an ML model: as climate changes and develops new patterns, there is no reason to think ML will adapt to it (and a ton of reasons to guess it won't).
achrono 2y ago
> We don't even need them to. Why not? What's so special about 7-14 days? I can see plenty of reasons one might want to predict accurately the weather even a year out, just one example: will the weather support an outdoor bbq event this late in fall next year?
- akira2501 2y ago
  > will the weather support an outdoor bbq event this late in fall next year? Sure, but there could be a disease outbreak, or a pork meat recall that prevents it anyways. The weather, as a factor, is generally insignificant with respect to loss of life events. To the extent they are we can see those events far enough in advance at 7 to 14 days to compensate correctly. A better example would be "can we launch a space craft from this launch site next year." Even then, we never pick a launch day, we establish a launch window, because we already know, the weather changes fast enough that it's unlikely to remain identical for several days in a row. So conditions on a single day are effectively meaningless. The Space Shuttle program got even better with this by feeding in wind data from high atmosphere probes back into the launch vehicle software so it could plan it's maneuvers ahead of the wind so it could reduce vehicle stresses to within tolerable parameters. They went from a 20% launch probability to an 80% launch probability with this system. I mean.. enjoy your BBQ either way just bring some popup tents.
otterley 2y ago
Farmers definitely want long range weather predictions so they can better plan what crops to plant and avoid crop failures. Crop failures due to weather have caused devastating losses.

zsims 2y ago

We do, I want to know if it's going to rain on my birthday

unsupp0rted 2y ago

Never will? I wouldn't be surprised if predicting climate + weather 12 months out is a simpler problem than most medical problems at which AI is currently being pointed.

JumpCrisscross 2y ago
> wouldn't be surprised if predicting climate + weather 12 months out is a simpler problem than most medical problems at which AI is currently being pointed Simple systems can be famously unpredictable [1]. Our bodies manage entropy; that should make them complex but predictable. The weather, on the other hand, has no governors or raison d'être. [1] https://en.wikipedia.org/wiki/Three-body_problem https://en.wikipedia.org/wiki/Three-body_problem
- tomjakubowski 2y ago
  The three body problem lacks a closed form solution. How does that mean it's unpredictable, though? I thought that numerical methods can be used to make n-body predictions to arbitrary precision. Are these simulations less accurate than I am thinking? How do engineers and scientists working on space probes plan their trajectories and such?
  - JumpCrisscross 2y ago
    > numerical methods can be used to make n-body predictions to arbitrary precision Arbitrary precision, not arbitrary length. Even "from [a] mathematical viewpoint, given an exact initial condition, we can gain mathematically reliable trajectories of chaotic dynamic systems" to only a "finite...interval" [1]. (This is due to "numerical noises, i.e. truncation and round-off error, where truncation error is determined by numerical algorithms and round-off error is due to the limited precision of numerical data, respectively.") For a physical system like the weather, uncertainty "mainly comes from limited precision of measurement," though there is also the "inherently uncertain/random property of nature, caused by such as thermal fluctuation, wave-particle duality of de Broglie’s wave, and so on." [1] https://www.sciencedirect.com/science/article/abs/pii/S1007570413003109 https://www.sciencedirect.com/science/article/abs/pii/S10075...
    - echoangle 2y ago
      Finite interval doesn’t mean it can’t be arbitrary. I’m not saying it can be in this example but your counterpoint doesn’t follow from the quote. For example, I can calculate the Fibonacci sequence to an arbitrary length but not infinite.
      - JumpCrisscross 2y ago
        > Finite interval doesn’t mean it can’t be arbitrary Skim the paper. Numerical noise means you cannot calculate the 3-body problem to an arbitrary length. There is a finite, mathematical limit even with perfect knowledge of initial conditions.
        echoangle 2y ago
        Isn’t the paper about the uncertainties that inherently exist with physical systems? There isn’t any claim that mathematically exact starting values can’t be propagated with arbitrary precision to arbitrary length, and I would claim that this is possible (but not practical due to compute being limited, of course). But there’s no hard limit of precision and length where a simulation can’t be made if the starting conditions are exact. The point of the paper is that starting conditions are never exact which limits the length you can propagate.
        JumpCrisscross 2y ago
        > Isn’t the paper about the uncertainties that inherently exist with physical systems? It talks about that. Which is relevant when we're talking about the weather. But it opens by discussing the hard mathematical limits to numerical methods. > there’s no hard limit of precision and length where a simulation can’t be made if the starting conditions are exact Wrong. Read. The. Paper. Numerical methods for chaotic systems are inherently, mathematically uncertain. Beyond a certain number of steps, adding precision doesn't yield a more precise answer, it just produces a different one. At a certain point, the difference between the different answers you get with more precision covers the entire solution space.
  - strls 2y ago
    You can solve to arbitrary precision but you can't measure and specify initial conditions to arbitrary precision, making the solution wrong outside of a small time interval.
    - JumpCrisscross 2y ago
      > can solve to arbitrary precision but you can't measure and specify initial conditions to arbitrary precision Even with perfect knowledge of initial conditions, numerical noise limits the forecast interval.
akira2501 2y ago
In order to predict the climate you need to predict volcanic eruptions. Good luck.
wongarsu 2y ago
Predicting that next December will be cold, sure. Predicting how cold or how much rainfall or snowfall there will be in next December would be difficult, but you could get in the right ballpark. Predicting in which week it will snow a year from now? Not a chance.

JumpCrisscross 2y ago

> have not and never will be able to predict further than that Is this a chaos theory prediction? Why 14 days?

akira2501 2y ago
Exactly. https://press.uni-mainz.de/the-limits-of-weather-forecasting-how-far-into-the-future-can-we-look/ https://press.uni-mainz.de/the-limits-of-weather-forecasting...

aithrowawaycomm 2y ago

The point is that the underlying physics of classical models should still hold true as the climate changes - and where they don't hold, we will have causal insight as to why. But this isn't necessarily true for an ML model: as climate changes and develops new patterns, there is no reason to think ML will adapt to it (and a ton of reasons to guess it won't).

achrono 2y ago

> We don't even need them to. Why not? What's so special about 7-14 days? I can see plenty of reasons one might want to predict accurately the weather even a year out, just one example: will the weather support an outdoor bbq event this late in fall next year?

akira2501 2y ago
> will the weather support an outdoor bbq event this late in fall next year? Sure, but there could be a disease outbreak, or a pork meat recall that prevents it anyways. The weather, as a factor, is generally insignificant with respect to loss of life events. To the extent they are we can see those events far enough in advance at 7 to 14 days to compensate correctly. A better example would be "can we launch a space craft from this launch site next year." Even then, we never pick a launch day, we establish a launch window, because we already know, the weather changes fast enough that it's unlikely to remain identical for several days in a row. So conditions on a single day are effectively meaningless. The Space Shuttle program got even better with this by feeding in wind data from high atmosphere probes back into the launch vehicle software so it could plan it's maneuvers ahead of the wind so it could reduce vehicle stresses to within tolerable parameters. They went from a 20% launch probability to an 80% launch probability with this system. I mean.. enjoy your BBQ either way just bring some popup tents.

otterley 2y ago

Farmers definitely want long range weather predictions so they can better plan what crops to plant and avoid crop failures. Crop failures due to weather have caused devastating losses.