The role of unresolved processes in climate and climate change

我们预测未来气候的最好方法是在世界上速度最快的计算机上运行复杂的模型。这些模型将地球表面分割成大约100公里长的盒子。因此，任何小于100公里的东西(例如，云和许多其他重要特征)都会从模型中遗漏。没有人怀疑这会降低模型及其预测的可靠性，但我们能做些什么呢？我们不能把盒子做得更小，因为即使是世界上最强大的超级计算机也不能足够快地完成计算！一些科学家最近提出，最好的解决方案可能是在模型中添加一些随机噪声。随机噪声是你在没有信号的情况下在电视屏幕上看到的东西，也是你在调谐收音机时听到的东西的原因。理论上，云和其他小特征无论如何都是相当随机的，所以为什么不在模型中使它们随机呢？奇怪的是，有很多证据表明，这实际上可以让天气预报变得更好。该项目将调查随机噪声对气候模型的影响。重要的是让这些模型尽可能准确，因为各国政府使用它们来决定我们可以安全地向大气中排放的温室气体水平，而不会让全球变暖对我们构成威胁。

The best way we have of predicting the climate of the future is to run complicated models on the world's fastest computers. These models divide the surface of the Earth up into boxes measuring around a hundred kilometres. Anything that measures less than a hundred kilometres (e.g. clouds and many other important features) is therefore missed out of the model. Nobody doubts that this makes the models and their predictions less reliable, but what can be done about it? We cannot make the boxes smaller, because even the world's most powerful supercomputers would not be able to do the calculations fast enough! Some scientists have recently suggested that the best solution might be to add some random noise to the models. Random noise is responsible for what you see on your TV screen when there's no signal, and for what you hear when you're tuning your radio. The theory is that clouds and other small features are pretty random anyway, so why not make them random in the model? Strangely, there is a lot of evidence that this can actually make weather forecasts better. This project will investigate the impacts of random noise on climate models. It is important to make these models as accurate as possible, because governments use them to decide the level of greenhouse gases we can safely emit into the atmosphere, without global warming becoming a danger to us.