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Lesson 14 |
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The Butterfly Effect |
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Why do small errors make it impossible to predict the weather system with a high degree of accuracy? |
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Beyond two or three days, the world's best weather forecasts are speculative, |
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and beyond six or seven they are worthless. |
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The Butterfly Effect is the reason. |
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For small pieces of weather -- |
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-- and to a global forecaster, small can mean thunderstorms and blizzards -- |
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any prediction deteriorates rapidly. |
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Errors and uncertainties multiply, cascading upward through a chain of turbulent features, |
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from dust devils and squalls up to continent-size eddies that only satellites can see. |
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The modern weather models work with a grid of points of the order of sixty miles apart, |
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and even so, some starting data has to be guessed, |
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since ground stations and satellites cannot see everywhere. |
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But suppose the earth could be covered with sensors spaced one foot apart, |
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rising at one-foot intervals all the way to the top of the atmosphere. |
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Suppose every sensor gives perfectly accurate readings of temperature, |
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pressure, humidity, and any other quantity a meteorologist would want. |
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Precisely at noon an infinitely powerful computer takes all the data and calculates what will happen at each point |
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at 12.01, then 12.02, then 12.03... |
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The computer will still be unable to predict whether Princeton, New Jersey, will have sun or rain on a day one month away. |
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At noon the spaces between the sensors will hide fluctuations that the computer will not know about, |
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tiny deviations from the average. |
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By 12.01, those fluctuations will already have created small errors one foot away. |
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Soon the errors will have multiplied to the ten-foot scale, and so on up to the size of the globe. |