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

点击翻译按钮获取中文摘要

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.