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http://en.wikipedia.org/wiki/Chaos_theory http://en.wikipedia.org/wiki/Chaos_theory To his surprise the weather that the machine began to predict was comp

http://en.wikipedia.org/wiki/Chaos_theory http://en.wikipedia.org/wiki/Chaos_theory To his surprise the weather that the machine began to predict was completely different from the weather calculated before. Lorenz tracked this down to the computer printout. The computer worked with 6-digit precision, but the printout rounded variables off to a 3-digit number, so a value like 0.506127 was printed as 0.506. This difference is tiny and the consensus at the time would have been that it should have had practically no effect. However Lorenz had discovered that small changes in initial conditions produced large changes in the long-term outcome.[43] Lorenz's discovery, which gave its name to Lorenz attractors, showed that even detailed atmospheric modelling cannot in general make long-term weather predictions. Weather is usually predictable only about a week ahead.[25] Note this is different from predicting Global Warming, Global warming is a long term trend prediction, not what will be temperature at certain day at a certain place kind of prediction.

pvg 16y ago
You should also read the wikipedia page on 'Weather Forecasting' while you're there. Or consider if you can predict whether the upcoming December in the Northern hemisphere might be colder than this last July.
- akshayubhat 16y ago
  read before you type, from my comment above: Weather is usually predictable only about a week ahead. and about December in the Northern hemisphere might be colder than this last. Thats not exactly a prediction, It is a seasonal variation due to inclination of earth w.r.t. sun. Thats same as some product will have higher sale before Christmas, or there will be more traffic on roads before thanksgiving.
  - mturmon 16y ago
    Well, I think you said two things. (1) "Predicting Weather is near impossible in theory forget the practice." and (2) Quoting wikipedia, "Weather is usually predictable only about a week ahead." These two remarks are not quite opposites, but almost.
    - akshayubhat 16y ago
      you are getting confused in semantics of word "prediction". Weather in theory is an Chaotic system thus there is no simple laws such as F = Ma to predict it. Time frames of week , seconds and years are meaningless. You can always argue that you can predict weather for next milli or micro or femto seconds, why stop at weeks? but that does not proves that chaos theory is wrong or that there is some generative law which can be used to predict weather without relying on data. Also from a utilitarian perspective, a long term accurate weather forecast would be so much useful rather than just a week long range [Assuming that is accurate right now,]. But you dont find accurate prediction for monsoon in January, or even of say a hurricane a fortnight before.
      - pvg 16y ago
        thus there is no simple laws such as F = Ma There are plenty of simple mechanical systems governed by mechanical laws that exhibit chaotic behaviour. You said a silly thing about weather prediction, it happens. There's really no need to dig yourself into some deeper hole of gibberish.
      - btilly 16y ago
        You can always argue that you can predict weather for next milli or micro or femto seconds, why stop at weeks? The reason that I've heard for stopping at weeks is that that is the time frame for perturbations to work their way up from the quantum scale to the macro scale. We cannot, even in principle, measure what is happening everywhere on the quantum scale. Of course as soon as you merge quantum mechanics and chaos theory, life gets very, very weird. See http://www.iqc.ca/publications/tutorials/chaos.pdf http://www.iqc.ca/publications/tutorials/chaos.pdf for more.
        mturmon 16y ago
        Sometimes these smaller perturbations are called "sub-grid phenomena". I think practitioners think of them as, say, pressure waves or flows which average to zero when observed on a 10km x 10km grid. But it is possible that their ultimate origin is on a much finer grid ;-) Another problem, separate from these effects, is getting closure on the variables in the model. Things like evaporation from soils and vegetation, for example, which ECMWF is trying to include in their models. You put them in the weather model to improve accuracy, and all the sudden you need a time-dependent model for soil and vegetation water content. And also, sensors to satisfy the boundary conditions for your model (e.g., to estimate plant vegetation type).

pvg 16y ago

You should also read the wikipedia page on 'Weather Forecasting' while you're there. Or consider if you can predict whether the upcoming December in the Northern hemisphere might be colder than this last July.

akshayubhat 16y ago
read before you type, from my comment above: Weather is usually predictable only about a week ahead. and about December in the Northern hemisphere might be colder than this last. Thats not exactly a prediction, It is a seasonal variation due to inclination of earth w.r.t. sun. Thats same as some product will have higher sale before Christmas, or there will be more traffic on roads before thanksgiving.
- mturmon 16y ago
  Well, I think you said two things. (1) "Predicting Weather is near impossible in theory forget the practice." and (2) Quoting wikipedia, "Weather is usually predictable only about a week ahead." These two remarks are not quite opposites, but almost.
  - akshayubhat 16y ago
    you are getting confused in semantics of word "prediction". Weather in theory is an Chaotic system thus there is no simple laws such as F = Ma to predict it. Time frames of week , seconds and years are meaningless. You can always argue that you can predict weather for next milli or micro or femto seconds, why stop at weeks? but that does not proves that chaos theory is wrong or that there is some generative law which can be used to predict weather without relying on data. Also from a utilitarian perspective, a long term accurate weather forecast would be so much useful rather than just a week long range [Assuming that is accurate right now,]. But you dont find accurate prediction for monsoon in January, or even of say a hurricane a fortnight before.
    - pvg 16y ago
      thus there is no simple laws such as F = Ma There are plenty of simple mechanical systems governed by mechanical laws that exhibit chaotic behaviour. You said a silly thing about weather prediction, it happens. There's really no need to dig yourself into some deeper hole of gibberish.
    - btilly 16y ago
      You can always argue that you can predict weather for next milli or micro or femto seconds, why stop at weeks? The reason that I've heard for stopping at weeks is that that is the time frame for perturbations to work their way up from the quantum scale to the macro scale. We cannot, even in principle, measure what is happening everywhere on the quantum scale. Of course as soon as you merge quantum mechanics and chaos theory, life gets very, very weird. See http://www.iqc.ca/publications/tutorials/chaos.pdf http://www.iqc.ca/publications/tutorials/chaos.pdf for more.
      - mturmon 16y ago
        Sometimes these smaller perturbations are called "sub-grid phenomena". I think practitioners think of them as, say, pressure waves or flows which average to zero when observed on a 10km x 10km grid. But it is possible that their ultimate origin is on a much finer grid ;-) Another problem, separate from these effects, is getting closure on the variables in the model. Things like evaporation from soils and vegetation, for example, which ECMWF is trying to include in their models. You put them in the weather model to improve accuracy, and all the sudden you need a time-dependent model for soil and vegetation water content. And also, sensors to satisfy the boundary conditions for your model (e.g., to estimate plant vegetation type).