In this study, we investigate uncertainties in a large eddy simulation of the atmosphere, employing modern uncertainty quantification methods that have hardly been used yet in this context. When analysing the uncertainty of model results, one can distinguish between uncertainty related to physical parameters whose values are not exactly known, and uncertainty related to modelling choices such as the selection of numerical discretization methods, of the spatial domain size and resolution, and the use of different model formulations. While the former kind is commonly studied e.g. with forward uncertainty propagation, we explore the use of such techniques to also assess the latter kind. From a climate modelling perspective, uncertainties in the convective response and cloud formation are of particular interest, since these affect the cloud-climate feedback, one of the dominant sources of uncertainty in current climate models. Therefore we analyse the DALES model in the RICO case, a well-studied convection benchmark. We use the VECMA toolkit for uncertainty propagation, assessing uncertainties stemming from physical parameters as well as from modelling choices. We find substantial uncertainties due to small random initial state perturbations, and that the choice of advection scheme is the most influential of the modelling choices we assessed.

This article is part of the theme issue ‘Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico’.

在这项研究中，我们采用了在这方面几乎没有使用过的现代不确定性量化方法，研究了大气大涡模拟中的不确定性。在分析模型结果的不确定性时，可以区分与数值不完全已知的物理参数有关的不确定性，以及与数值离散方法的选择、空间域大小和分辨率的选择以及使用方法等建模选择有关的不确定性。不同的模型公式。虽然前一种通常被研究，例如前向不确定性传播，但我们探索使用这种技术来评估后一种。从气候建模的角度来看，对流响应和云形成的不确定性尤其令人感兴趣，由于这些影响云气候反馈，这是当前气候模型中不确定性的主要来源之一。因此，我们在 RICO 案例中分析了 DALES 模型，这是一个经过充分研究的对流基准。我们使用 VECMA 工具包进行不确定性传播，评估源自物理参数以及建模选择的不确定性。由于小的随机初始状态扰动，我们发现了很大的不确定性，并且对流方案的选择是我们评估的建模选择中最具影响力的。

本文是主题问题“计算科学中的可靠性和再现性：在计算机中实现验证、确认和不确定性量化”的一部分。