Brookhaven National Laboratory, Upton, USA.
Stony Brook University, Stony Brook, USA.
Sci Data. 2024 Jun 22;11(1):661. doi: 10.1038/s41597-024-03477-9.
In 2022, Houston, TX became a nexus for field campaigns aiming to further our understanding of the feedbacks between convective clouds, aerosols and atmospheric boundary layer (ABL) properties. Houston's proximity to the Gulf of Mexico and Galveston Bay motivated the collection of spatially distributed observations to disentangle coastal and urban processes. This paper presents a value-added ABL dataset derived from observations collected by eight research teams over 46 days between 2 June - 18 September 2022. The dataset spans 14 sites distributed within a ~80-km radius around Houston. Measurements from three types of instruments are analyzed to objectively provide estimates of nine ABL parameters, both thermodynamic (potential temperature, and relative humidity profiles and thermodynamic ABL depth) and dynamic (horizontal wind speed and direction, mean vertical velocity, updraft and downdraft speed profiles, and dynamical ABL depth). Contextual information about cloud occurrence is also provided. The dataset is prepared on a uniform time-height grid of 1 h and 30 m resolution to facilitate its use as a benchmark for forthcoming numerical simulations and the fundamental study of atmospheric processes.
2022 年,德克萨斯州休斯顿成为了一系列旨在进一步了解对流云、气溶胶和大气边界层(ABL)特性之间反馈的野外考察活动的中心。休斯顿靠近墨西哥湾和加尔维斯顿湾,这促使研究团队进行了空间分布观测,以区分沿海和城市过程。本文介绍了一个增值 ABL 数据集,该数据集是由八个研究团队在 2022 年 6 月 2 日至 9 月 18 日期间进行的 46 天观测收集得到的。该数据集跨越了休斯顿周围约 80 公里半径范围内的 14 个站点。分析了三种仪器的测量数据,以客观地提供九个 ABL 参数的估计值,包括热力学参数(位温、相对湿度廓线和热力学 ABL 深度)和动力学参数(水平风速和风向、平均垂直速度、上升和下降速度廓线以及动力学 ABL 深度)。还提供了关于云发生情况的上下文信息。该数据集在 1 小时和 30 米的均匀时间-高度网格上进行准备,以方便其用作即将到来的数值模拟和大气过程基础研究的基准。