论文标题
部分可观测时空混沌系统的无模型预测
Significance of a one-degree Celsius increase in global temperature
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
The Intergovernmental Panel on Climate Change reports indicate that the global mean temperature is about one-degree Celsius higher than pre-industrial levels, that this increase is anthropogenic, and that there is a causal relationship between this higher temperature and an increase in frequency and magnitude of extreme weather events. This causal relationship seems at odds with common sense, and may be difficult to explain to non-experts. Thus to appreciate the significance of a one-degree increase in global mean temperature, we perform back-of-the-envelope calculations relying on simple physics. We estimate the excess thermal energy trapped in the climate system (oceans, land, atmosphere) from a one-degree Celsius increase in global mean temperature, and show that it is thousands of times larger than the estimated energy required to form and maintain a hurricane. Our estimates show that global warming is forming a very large pool of excess energy that could in principle power heatwaves, heavy precipitation, droughts, and hurricanes. The arguments presented here are sufficiently simple to be presented in introductory physics classes, and can serve as plausibility arguments showing that even a seemingly small increase in global mean temperature can potentially lead to extreme weather events.
