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You are not "far from a climate change skeptic". You are a climate change skeptic. At best, your post is the vague claim that complex systems cannot be modeled

You are not "far from a climate change skeptic". You are a climate change skeptic. At best, your post is the vague claim that complex systems cannot be modeled or tested empirically, and is empirically wrong in its claim that no-one predicted the financial crisis.

ThomBot 15y ago
Based on the second claim of stfu’s post, “as soon as humans are involved data and data analysis will always be subjective”, I think he is really trying to highlight the unpredictability of a model that must generalize human choices using statistics. Since even conservative scientists will agree that climate change has some anthropogenic dimension, we should understand the limitations of modeling it. Being skeptical of the model, however, does not prohibit you from accepting what the model is suggesting. Historical data and scientific opinion can be enough to convince us that climate change is occurring. But no model can predict how our reaction to that knowledge will affect climate change in the future.
Produce 15y ago
Call me a skeptic too in that case. Chaotic systems are inherently unpredictable to us, though they are ofcourse deterministic. The climate is chaotic (http://www.mendeley.com/research/nonlinearities-feedbacks-and-critical-thresholds-within-the-earths-climate-system/ http://www.mendeley.com/research/nonlinearities-feedbacks-an...). Chaotic systems have a horizon of predictability (http://www.britannica.com/EBchecked/media/3227/Sensitivity-of-a-chaotic-number-sequence-to-initial-value-illustrating http://www.britannica.com/EBchecked/media/3227/Sensitivity-o...), so climate models are still useful to an extent. They will tell us, with some degree of accuracy, roughly what will happen in the near future. The long term remains a mystery and there's little that can be done about that.
- scarmig 15y ago
  It goes much too far to say that the climate is chaotic and therefore totally unpredictable in the long run. After all, if you buy that whole hog, you're also led to say that if you moved the Earth to Mercury's orbit it would be impossible to predict that the Earth would get hotter, in the long term. This results from the flaw of confusing weather (which is indeed chaotic) with statistics about weather (i.e. climate). A butterfly flapping its wings can cause a hurricane. But it can also prevent a hurricane. All those perturbations don't change the fact that, within an order of magnitude, we can predict how many hurricanes will occur in a given year. Alternatively, think about the classical three body problem: even though it's the preeminent example of a chaotic system, you can still make broad predictions about it. Center of mass, average speed of the bodies, average collision time. This isn't some obscure controversial field, either: in physics, these emergent statistical properties form the basis of statistical mechanics and therefore thermodynamics as a whole. Chaos doesn't mean you have to throw your hands up and give up on making any long term predictions at all about a system.
  - Produce 15y ago
    >Chaos doesn't mean you have to throw your hands up and give up on making any long term predictions at all about a system. But we can't tell what the weather will be in 45 days in New York. One of the attributes of chaotic systems is their self-similarity. The behavior on one level is similar to the behavior on another - in this case weather is similar to climate. We can make predictions about the weather in the next few days, just as we can with climate, but in the next few months or years (or centuries or millenia for climate) is another story. The tiny pertrubations in the system which we do not model (the butterflies) end up throwing our predictions off in the long run.
    - xyzzyz 15y ago
      Yes, and that's why nobody is claiming to be able to predict the weather in the long run. Nevertheless, some things still can be predicted, even in chaotic systems. What is your point?
      - Produce 15y ago
        My point is that pollution should be reduced, climate models should still be developed and that at the same time we shouldn't take their predictions as dogma and continue to question them.
        scarmig 15y ago
        I agree with all of what you say above and am skeptical of the models as they exist now, as another comment of mine elsewhere suggests. I'm more interested in the theoretical question here, though. I'm unconvinced that self-similarity in chaotic systems means that since weather is a chaotic system, climate is itself a chaotic system that's unpredictable in the long term. One way of thinking about chaos is that at some point in the future, a system's position in phase space will become wholly uncorrelated with the system's initial position. So for weather, tomorrow's weather is correlated with today's weather, but weather two weeks from now (or whenever) is wholly uncorrelated. But with climate you do end up with persistent correlations, year on year, decade on decade, millenia on millenia. Temperate regions show (anti-)correlations of deviation from annual average temperature between 180 day periods, and daily solar energy impingement is correlated with positive deviation from global mean temperature. I've always made a mental analogy between that and a gas (the n-body problem): even though the positions of gas molecules rapidly become uncorrelated from their starting position, certain statistical properties--e.g., the pressure the gas exerts on the walls of its container--are highly correlated from one moment to another. Not just initially but into the indefinite future. I'm open to arguments that that analogy is flawed and could see some assumptions that I'm not 100% confident in, but I don't see any obvious flaws. What's going wrong here, in your view?
- Tichy 15y ago
  That argumentation is a bit silly. Chaotic systems are not necessarily unpredictable. For example take the pendulum that swings among the magnets (one of those classic examples). So the exact path of the pendulum might be unpredictable, but it is predictable that it will reach equilibrium eventually. What I mean is: some aspects can be predictable while others are not predictable. Therefore your argument is wrong.
  - deleted 15y ago
    [deleted]

ThomBot 15y ago

Based on the second claim of stfu’s post, “as soon as humans are involved data and data analysis will always be subjective”, I think he is really trying to highlight the unpredictability of a model that must generalize human choices using statistics. Since even conservative scientists will agree that climate change has some anthropogenic dimension, we should understand the limitations of modeling it. Being skeptical of the model, however, does not prohibit you from accepting what the model is suggesting. Historical data and scientific opinion can be enough to convince us that climate change is occurring. But no model can predict how our reaction to that knowledge will affect climate change in the future.

Produce 15y ago

Call me a skeptic too in that case. Chaotic systems are inherently unpredictable to us, though they are ofcourse deterministic. The climate is chaotic (http://www.mendeley.com/research/nonlinearities-feedbacks-and-critical-thresholds-within-the-earths-climate-system/ http://www.mendeley.com/research/nonlinearities-feedbacks-an...). Chaotic systems have a horizon of predictability (http://www.britannica.com/EBchecked/media/3227/Sensitivity-of-a-chaotic-number-sequence-to-initial-value-illustrating http://www.britannica.com/EBchecked/media/3227/Sensitivity-o...), so climate models are still useful to an extent. They will tell us, with some degree of accuracy, roughly what will happen in the near future. The long term remains a mystery and there's little that can be done about that.

scarmig 15y ago
It goes much too far to say that the climate is chaotic and therefore totally unpredictable in the long run. After all, if you buy that whole hog, you're also led to say that if you moved the Earth to Mercury's orbit it would be impossible to predict that the Earth would get hotter, in the long term. This results from the flaw of confusing weather (which is indeed chaotic) with statistics about weather (i.e. climate). A butterfly flapping its wings can cause a hurricane. But it can also prevent a hurricane. All those perturbations don't change the fact that, within an order of magnitude, we can predict how many hurricanes will occur in a given year. Alternatively, think about the classical three body problem: even though it's the preeminent example of a chaotic system, you can still make broad predictions about it. Center of mass, average speed of the bodies, average collision time. This isn't some obscure controversial field, either: in physics, these emergent statistical properties form the basis of statistical mechanics and therefore thermodynamics as a whole. Chaos doesn't mean you have to throw your hands up and give up on making any long term predictions at all about a system.
- Produce 15y ago
  >Chaos doesn't mean you have to throw your hands up and give up on making any long term predictions at all about a system. But we can't tell what the weather will be in 45 days in New York. One of the attributes of chaotic systems is their self-similarity. The behavior on one level is similar to the behavior on another - in this case weather is similar to climate. We can make predictions about the weather in the next few days, just as we can with climate, but in the next few months or years (or centuries or millenia for climate) is another story. The tiny pertrubations in the system which we do not model (the butterflies) end up throwing our predictions off in the long run.
  - xyzzyz 15y ago
    Yes, and that's why nobody is claiming to be able to predict the weather in the long run. Nevertheless, some things still can be predicted, even in chaotic systems. What is your point?
    - Produce 15y ago
      My point is that pollution should be reduced, climate models should still be developed and that at the same time we shouldn't take their predictions as dogma and continue to question them.
      - scarmig 15y ago
        I agree with all of what you say above and am skeptical of the models as they exist now, as another comment of mine elsewhere suggests. I'm more interested in the theoretical question here, though. I'm unconvinced that self-similarity in chaotic systems means that since weather is a chaotic system, climate is itself a chaotic system that's unpredictable in the long term. One way of thinking about chaos is that at some point in the future, a system's position in phase space will become wholly uncorrelated with the system's initial position. So for weather, tomorrow's weather is correlated with today's weather, but weather two weeks from now (or whenever) is wholly uncorrelated. But with climate you do end up with persistent correlations, year on year, decade on decade, millenia on millenia. Temperate regions show (anti-)correlations of deviation from annual average temperature between 180 day periods, and daily solar energy impingement is correlated with positive deviation from global mean temperature. I've always made a mental analogy between that and a gas (the n-body problem): even though the positions of gas molecules rapidly become uncorrelated from their starting position, certain statistical properties--e.g., the pressure the gas exerts on the walls of its container--are highly correlated from one moment to another. Not just initially but into the indefinite future. I'm open to arguments that that analogy is flawed and could see some assumptions that I'm not 100% confident in, but I don't see any obvious flaws. What's going wrong here, in your view?
Tichy 15y ago
That argumentation is a bit silly. Chaotic systems are not necessarily unpredictable. For example take the pendulum that swings among the magnets (one of those classic examples). So the exact path of the pendulum might be unpredictable, but it is predictable that it will reach equilibrium eventually. What I mean is: some aspects can be predictable while others are not predictable. Therefore your argument is wrong.
- deleted 15y ago
  [deleted]