Improved algorithms to generate 3-dimensional cloud fields for use in radiative transfer modelling

要解决多云大气中的多维辐射传输问题，不仅需要良好的辐射传输模型，还需要真实的二维或三维云场。研究云结构最常用的三维云场是来自动态模型的云场或分形云场。我们已经开发了算法来生成替代场，其中功率谱和分布的形状可以自由和独立地选择。这有利于敏感性研究，并允许生成与测量数据密切匹配的场。后者很重要，因为云的结构非常复杂，无法完全测量。因此，实证研究需要基于测量生成替代字段的方法，例如闭合研究或需要将不同尺度的测量结合在一起的研究。在这个项目中，我们希望通过以下方式开发更通用和更好的算法：1)包括多元统计（例如，同时考虑含水量和有效半径中的结构）；2)其他结构测量（以产生更好的积云）；3)包括空间信息（使算法成为保留结构的插值方法，以便能够与辐射点测量进行闭合研究）。我们将从实验数据中生成代理字段。这些将与算法一起在互联网上下载。

For solving multidimensional radiative transfer problems in the cloudy atmosphere, one needs not only a good Radiative Transfer (RT) model, but also realistic 2D or 3D cloud fields. The most used 3D cloud fields for research into cloud structure are fields from dynamical models or fractal cloud fields. We have developed algorithms to generate surrogate fields where the power spectrum and the shape of the distribu-tion can be chosen freely and independently. This facilitates sensitivity studies and allows generating fields that have a close fit with statistics from measurements. The latter is important since clouds have such a complicated structure that they cannot be measured fully. Therefore, methods to generate surrogate fields based on meas-urements are needed for empirical studies, such as closure studies or studies that need to bring measurements made at different scales together. In this project we would like to develop more versatile and better algorithms by 1) including multivariate statistics (to e.g. consider the structure in water content and effective radius simulta-neously), and 2) other structure measures (to generate better cumulus clouds) and 3) by including spatial information (making the algorithm an interpolation method that preserves structure, to be able to make closure studies with radiation point-measurements). We will generate surrogate fields from experimental data. These will be downloadable on the internet together with the algorithms.