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The world's climate scientists are charged with a difficult task:
世界气候科学家肩负着一项艰巨的任务：
to create a crystal ball with which to skry a future that promises to be hotter than today.
创造一个水晶球，用它来预示一个比现在更热的未来。
But exactly how much hotter depends on innumerable factors, both natural and human.
但到底有多热，这取决于无数的因素，有自然也有人类因素。
Creating the crystal ball is thus a two-stage process. First, you have to build a simulacrum of how Earth's climate works.
因此，创建水晶球是一个两阶段的过程。首先，你需要建立一个地球气候运行的模拟模型。
Then, you try to perturb this simulacrum with plausible future human actions, to see what picture appears.
然后，你要尝试用未来可能的人类行为扰乱这个拟像，看看会出现什么情况。
Modern magic being what it is, the crystal balls are actually supercomputers running programs with 1m or more lines of code.
现代魔法就是这样，水晶球其实是超级计算机，运营着拥有百万或更多代码的程序。
These programs are models that divide the planet's atmosphere, ocean and land surface into grids of cells—many millions of them.
这些程序就是模型，将地球的大气、海洋和陆地分成网格细胞—有数百万个。
Land cells are flat. Atmosphere and ocean cells are three-dimensional
陆地细胞是平的。大气和海洋细胞时三维的
and are stacked in columns to account for the effects of altitude and depth.
并被堆叠在列中，以解释高度和深度的影响。
A model calculates what is going on, physically and chemically, inside each cell,
这是一个计算每个细胞中物理和化学变化的模型
and how this will affect that cell's neighbours, both sideways and, if appropriate, above and below.
一个全方位计算这将如何影响这个细胞邻居的模型。
Then it does it again. And again. And again. That is a complicated process.
然后再重复一遍。重复再重复，这是一个复杂的过程。
A model's code has to represent everything from the laws of thermodynamics to the intricacies of how air molecules interact with one another.
一个模型的代码必须代表一切，从热力学定律到空气分子相互作用的复杂性。
Running it means performing quadrillions of mathematical operations a second—hence the need for supercomputers.
运行这个模型意味着每秒要执行千万亿次数学运算——因此需要超级计算机。
And using it to make predictions means doing this thousands of times,
用它来进行预测意味着要执行数千次
with slightly different inputs on each run, to get a sense of which outcomes are likely,
每次运行的输入略有不同，这样才能了解哪些结果有可能
which unlikely but possible, and which implausible in the extreme.
哪些不太可能，但有希望以及哪些在极端情况下是不可信的。
Even so, such models are crude. Millions of grid cells might sound a lot,
即便如此，这样的模型也很粗糙。数以百万计的网格单元可能听起来很多，
but it means that an individual cell's area, seen from above, is about 10,000 square kilometres,
但这意味着从上面看，单个细胞领域约有一万平方公里，
while an air or ocean cell may have a volume of as much as 100,000 cubic kilometers.
而一个空气或海洋细胞的体积可能高达10万立方千米。
Treating these enormous areas and volumes as points misses much detail.
把这些巨大的区域和体量当作点来处理会忽略很多细节。
Clouds, for instance, present a particular challenge to modellers.
例如，云层是分析员面临的一个特殊挑战。
Depending on how they form and where, they can either warm or cool the climate.
根据它们的形成方式和地点，它们可以使气候变暖或变冷。
But a cloud is far smaller than even the smallest grid-cells, so its individual effect cannot be captured.
但是云甚至比最小的网格单元都要小得多，因此它的个体效应无法被捕捉到。
The same is true of regional effects caused by things like topographic features or islands.
地形特征或岛屿等因素造成的区域效应也是如此。
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