无需流体力学的气象与气候
Weather and Climate Without Fluid Mechanics
- The University of Utah（犹他大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出基于尺度不变性和“湍流子”构建的STEAM模型，以涌现定律替代显式流体模拟，计算成本降低百万倍，且能逼真再现大气统计与云图，暗示无需纳维-斯托克斯方程即可预测天气气候。
AI中文摘要：
即使可行，试图通过追踪管道中每个单独分子来模拟流体运动，也将是对计算资源的极大浪费。流体力学的涌现定律在笔记本电脑上而非数据中心中即可实现同样的目标。然而，像地球大气这样足够复杂的流体，再次需要数据中心，这次是为了解析构成我们天气的众多场中的各种扭曲形态。是否存在某种类似的涌现定律集合，能够代表这些扰动的影响，而无需在数值网格上显式表示它们？我们认为，一个对称性原理的存在暗示了这类定律很可能存在。大气具有尺度不变性，这意味着在一个尺度上观测到的结构，不过是任何其他尺度上结构的拉伸版本，至少在不变区间内如此。尽管基于尺度不变性已存在一些涌现定律，但它们建立在具有挑战性的本体论基础上，难以进一步发展。我们提出了一条前进路径，首先引入一个我们称之为“湍流子”（turbulon）的大气新基本构建块，其灵感来源于一种较少为人知的、考虑了浮力的湍流理论推广。随后，我们构建了湍流子与涡旋叠加大气模型（STEAM），并展示了与最先进的水动力学模拟输出相比，模拟的大气体积大体上是合理的。STEAM的某些方面显然需要改进，但其他统计量比水动力学模型更好地再现了观测结果，且模拟云的可视化效果惊人地逼真。我们估计STEAM的计算成本比水动力学模型低至多一百万倍，这表明纳维-斯托克斯方程可能实际上并非模拟和预测地球天气与气候所必需的。
英文摘要：
Even if it were possible, attempting to model the motion of a fluid in a pipe by tracking each individual molecule would be an extraordinary waste of computation. The emergent laws of fluid mechanics accomplish the same goal on a laptop instead of a datacenter. But a sufficiently complex fluid such as in Earth's atmosphere again requires a datacenter, this time to resolve the many contortions in the fields making up our weather. Might there be some analogous set of emergent laws that would represent the effect of these perturbations without needing their explicit representation on a numerical grid? We argue that the existence of a symmetry principle implies such laws are likely to exist. The atmosphere is scale invariant, implying that the observed structure at one scale is nothing but a stretched version of that at any other scale, at least within the invariant regime. Though some emergent laws built on scale invariance exist, they are built on a challenging ontological foundation, making them hard to develop further. We propose a path forward, first by introducing a new fundamental building block of the atmosphere that we term a ``turbulon'', inspired by a lesser-known generalization of turbulence theory that accounts for buoyancy. We then construct the Superposition of Turbulons and Eddies Atmospheric Model (STEAM), and show that simulated atmospheric volumes are broadly plausible when compared to state-of-the-art hydrodynamic simulation output. Some aspects of STEAM clearly need improvement, though other statistics reproduce observations better than hydrodynamic models, and visualizations of simulated clouds are strikingly realistic. We estimate STEAM's computational cost to be up to a million times less than hydrodynamic models, suggesting that the Navier-Stokes equations may not, in fact, be required for simulation and prediction of Earth's weather and climate.
