UCLA-LES shallow cumulus dataset with 3D cloud output data

The dataset features 6 hours of single layer shallow cumulus clouds with an ever increasing cloud deck. I.e. domain average cloud fraction ranges from 0% in the beginning to 100% towards the end of the simulation. A key feature of the dataset is its very high temporal resolution of 3D output fields (every 10 seconds). The vision is that the high temporal frequency and spatial resolution of cloud and wind variables will allow for a wide range of offline benchmarks. Applications that come to our mind are offline benchmark for 1D and 3D radiative heating rate computations, 3D radiative transfer effects on retrievals as well as cloud motion tracking algorithms. Access to dataData files are available for download at: https://opendata.physik.lmu.de/5d0k9-q2n86

本数据集涵盖6小时的单层浅积云（shallow cumulus clouds）演化过程，云盖持续增厚。具体而言，模拟初始时刻的区域平均云量为0%，随模拟推进最终升至100%。本数据集的核心特征之一是其三维输出场具备极高的时间分辨率——输出间隔仅为10秒。本数据集的设计初衷是，依托云量与风场变量的高时间与空间分辨率，可支撑多类离线基准测试任务。可供参考的应用场景包括：一维与三维辐射加热率计算的离线基准测试、反演过程中的三维辐射传输效应分析，以及云运动追踪算法相关研究。数据获取：数据集文件可通过以下链接下载：https://opendata.physik.lmu.de/5d0k9-q2n86