14 · 蝴蝶效应
The Butterfly Effect
区分观点、依据、例子与限制，用自己的话准确重建论述。
时代语境：开头的“两三天”“六七天”与后文的网格尺度，反映作者成文时对预报能力的描述，不是今天气象预报的统一有效期。阅读重点是初始不确定性如何放大，以及预测的边界。
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Beyond two or three days, the world's best weather forecasts are speculative, and beyond six or seven they are worthless.
The Butterfly Effect is the reason. For small pieces of weather—and to a global forecaster, small can mean thunderstorms and blizzards—any prediction deteriorates rapidly. Errors and uncertainties multiply, cascading upward through a chain of turbulent features, from dust devils and squalls up to continent-size eddies that only satellites can see.
The modern weather models work with a grid of points of the order of sixty miles apart, and even so, some starting data has to be guessed, since ground stations and satellites cannot see everywhere. But suppose the earth could be covered with sensors spaced one foot apart, rising at one-foot intervals all the way to the top of the atmosphere. Suppose every sensor gives perfectly accurate readings of temperature, pressure, humidity, and any other quantity a meteorologist would want. Precisely at noon an infinitely powerful computer takes all the data and calculates what will happen at each point at 12.01, then 12.02, then 12.03...
The computer will still be unable to predict whether Princeton, New Jersey, will have sun or rain on a day one month away.At noon the spaces between the sensors will hide fluctuations that the computer will not know about, tiny deviations from the average. By 12.01, those fluctuations will already have created small errors one foot away. Soon the errors will have multiplied to the ten-foot scale, and so on up to the size of the globe.
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整篇课文
Beyond two or three days, the world's best weather forecasts are speculative, and beyond six or seven they are worthless.
The Butterfly Effect is the reason. For small pieces of weather—and to a global forecaster, small can mean thunderstorms and blizzards—any prediction deteriorates rapidly. Errors and uncertainties multiply, cascading upward through a chain of turbulent features, from dust devils and squalls up to continent-size eddies that only satellites can see.
The modern weather models work with a grid of points of the order of sixty miles apart, and even so, some starting data has to be guessed, since ground stations and satellites cannot see everywhere. But suppose the earth could be covered with sensors spaced one foot apart, rising at one-foot intervals all the way to the top of the atmosphere. Suppose every sensor gives perfectly accurate readings of temperature, pressure, humidity, and any other quantity a meteorologist would want. Precisely at noon an infinitely powerful computer takes all the data and calculates what will happen at each point at 12.01, then 12.02, then 12.03...
The computer will still be unable to predict whether Princeton, New Jersey, will have sun or rain on a day one month away.At noon the spaces between the sensors will hide fluctuations that the computer will not know about, tiny deviations from the average. By 12.01, those fluctuations will already have created small errors one foot away. Soon the errors will have multiplied to the ten-foot scale, and so on up to the size of the globe.
即使是世界上最好的天气预报，超过两三天也只能算推测，超过六七天就没有价值了。
原因就在于蝴蝶效应。对局部天气所作的预测，会很快失准；而在负责全球天气预报的人眼里，雷暴和暴风雪也只能算局部现象。误差和不确定性不断增大，沿着一系列湍流现象逐级向更大尺度传递：从小旋风、突发的狂风，一直到只有卫星才能看清的大陆规模的巨大涡旋。
现代天气模型采用的网格，格点间距约为六十英里。即便如此，有些初始数据仍不得不靠估计，因为地面观测站和卫星不可能覆盖每一处。现在不妨假设，整个地球都布满了传感器，水平方向每隔一英尺一个，垂直方向也每隔一英尺一层，一直延伸到大气层顶部。再假设，每个传感器都能完全准确地测出温度、气压、湿度，以及气象学家需要的任何其他物理量。正午十二点，一台算力无限的计算机收集全部数据，计算每个地点在十二点零一分、十二点零二分、十二点零三分会发生什么……
即便如此，这台计算机仍无法预测一个月后的某一天，新泽西州普林斯顿究竟晴天还是下雨。因为在正午时刻，传感器之间的空隙里仍会存在计算机不知道的微小波动，也就是偏离平均值的细微差异。到十二点零一分，这些波动就已在一英尺的范围内造成小误差。不久，误差会扩大到十英尺的尺度，再不断扩展，直至影响全球。
学完这一课
用一个主句加分词描述某影响逐步扩散的过程。
译文依据整理稿，由本站按中文表达重新校订；解析据吴应时整理资料及首轮审校稿；词伙与练习提示为本站学习设计。原PDF第57—59页，2022年2月第2版。