论文标题
映射积云云以扩展不变的粗糙表面
Mapping cumulus clouds to scale invariant rough surfaces
论文作者
论文摘要
在最近观察到的积云云的批判性的最新观察中（Phys。RevE 103，052106，2021），我们研究了它们与自相似粗糙表面的联系，其中$ f \ equiv \ equiv \ log i $扮演着主要领域的作用，在其中$ i是接收到可见光的强度。通过在二维云中基于粗粒现象学模型模拟光散射，我们认为$ i $可能与实际的云厚度之间的连接。尽管在垂直事件中，$ f $与云厚度成正比，但在一般情况下，它得到了批准。我们研究了$ f $的观测数据的统计特性，重点是这种规模不变粗糙表面的常规指数。通过计算粗糙度指数，并将其与其他指数进行比较，例如循环的分形维度，回旋和环长度的半径的分布功能以及绿色功能的指数，我们证明，这种表面是非常规的，因为它是非高斯自动伴随的随机表面，这违反了KONDEV的无限型相关性。
Motivated by a recent observation on the self-organized criticality of cumulus clouds (Phys. Rev E 103, 052106, 2021) we study their connection to self-similar rough surfaces, in which $f\equiv \log I$ plays the role of the main field, where $I$ is the intensity of the received visible light. By simulating the light scattering based on a coarse-grained phenomenological model in a two-dimensional cloud, we argue the possible connection of $I$ to the actual cloud thickness. Although in the vertical incident light $f$ is proportional to the cloud thickness, in the general case it is complected. We study the statistical properties of observational data for $f$ with a focus on the conventional exponents of this scale-invariant rough surface. By calculating the roughness exponents, and comparing them with other exponents like the fractal dimension of loops, the distribution function of the radius of gyration and loop lengths, and the exponent of the green function, we prove that this surface is unconventional in the sense that it is the non-Gaussian self-affine random surface which violates the Kondev hyper-scaling relations.
