Predator–prey dynamics have been suggested as simplified models of stratocumulus clouds, with rain acting as a predator of the clouds. We describe a mathematical and computational framework for estimating the parameters of a simplified model from a large eddy simulation (LES). In our method, we extract cycles of cloud growth and decay from the LES and then search for parameters of the simplified model that lead to similar cycles. We implement our method via Markov chain Monte Carlo. Required error models are constructed based on variations of the LES cloud cycles. This computational framework allows us to test the robustness of our overall approach and various assumptions, which is essential for the simplified model to be useful. Our main conclusion is that it is indeed possible to calibrate a predator–prey model so that it becomes a reliable, robust, but simplified representation of selected aspects of a LES. In the future, such models may then be used as a quantitative tool for investigating important questions in cloud microphysics.

捕食者-被捕食者的动力学被认为是层状积云的简化模型，雨水充当了云的捕食者。我们描述了一种数学和计算框架，用于根据大型涡流仿真（LES）估算简化模型的参数。在我们的方法中，我们从LES中提取云的生长和衰变的周期，然后搜索导致相似周期的简化模型的参数。我们通过马尔可夫链蒙特卡罗实现我们的方法。根据LES云周期的变化构建所需的错误模型。该计算框架使我们能够测试整体方法和各种假设的鲁棒性，这对于简化模型的使用至关重要。我们的主要结论是，确实有可能校准食肉动物-猎物模型，使其成为可靠的，LES选定方面的可靠，简化表示。将来，此类模型可以用作研究云微观物理学中重要问题的定量工具。