UrbanTALES: A Large-Eddy Simulation Dataset for Urban Canopy Layer Turbulence and Parameterization

作者：Negin Nazarian, Jiachen Lu, Mathew Lipson, Melissa Hart, Sijie Liu, E. Scott Krayenhoff, Lewis Blunn, Alberto Martilli · 发表于：Bulletin of the American Meteorological Society · 年份：2025 · DOI：10.1175/bams-d-25-0061.1 · 被引用次数：11 · 研究领域：Wind and Air Flow Studies、Meteorological Phenomena and Simulations、Urban Heat Island Mitigation

Abstract The urban canopy layer (UCL) exhibits complex, heterogeneous flow patterns shaped by urban geometry. Traditionally, research has relied on microscale simulations over limited and often idealized building arrays, leaving a need for more extensive datasets to capture the dynamics across diverse urban neighborhoods. Responding to this gap, we developed an extensive dataset, known hereafter as Urban Turbulence Analyses from Large-Eddy Simulations (UrbanTALES), based on state-of-the-art large-eddy simulations (LESs) over 538 urban layouts (generated using over 3 000 000 CPU hours and 35 TB of storage) with both idealized and realistic configurations. Realistic urban neighborhood configurations were obtained from major cities worldwide, incorporating wide variations in building plan area densities [0.06–0.64] and height distributions [4–50 m]. Idealized urban arrays, on the other hand, include two commonly studied configurations (aligned and staggered building arrays), featuring both uniform and variable height scenarios along with oblique wind directions. UrbanTALES offers canopy-averaged flow data as well as 2D and 3D flow fields tailored for different applications in urban climate research such as the development and testing of urban canopy models. The dataset provides time-averaged wind flow properties, as well as second- and third-order flow moments that are critical for understanding turbulent processes in the UCL. Here, we describe the UrbanTALES dataset and its app...