Dataset for "Multi-scale analysis of flow over heterogeneous urban environments"

Dataset for "Multi-scale analysis of flow over heterogeneous urban environments"
zenodo · 2025 · cc-by-4.0 · 11 GB
Open on zenodo DOI: 10.5281/zenodo.17102845

Description

This dataset accompanies the paper Multi-scale analysis of flow over heterogeneous urban environments (2025). Maarten van Reeuwijk and Jingzi Huang Boundary-Layer Meteorology If you make use of this dataset, please cite both the paper and the dataset. # ------------------------------------------------- # The main directory contains the following files and folders: Functions/: Auxiliary MATLAB functions. Figures/: All the figure files from the paper. Data/: Raw simulation data. main.m: Loads the simulation data and reproduces the figures in the paper. coarsegraining_example.m: an example of efficiently implementing the coarse-graining method in convolution form using Fast-Fourier Transform --- the core of the multi-scale analysis. # ------------------------------------------------- # Data folder: Simulation geometry: geom.stl Local time-averaged data (x,y,z) tdump.302.nc: contains 3-D fields of variables and budgets. Time- and plane- averaged data (z) xytdump.302.nc: contains intrinsically averaged vertical profiles of variables and budgets. Facet time-averaged data fac.302.nc: contains variables defined on solid facets. Additional simulation data facet_sections_*: information on solid facets. fluid_boundary_*: information on fluid-solid boundary. solid_*: information on solid areas. namoptions.302: preset simulation parameters. # ------------------------------------------------- # Functions folder: Matlab/: supporting the 'udbase' post-processing class, which reads key input parameters and provides methods to load both field and facet data. Adding it to the path before using 'udbase'. Filter_fft.m: a function that implements the Fast Fourier Transform. # ------------------------------------------------- # Further information For more details on the dataset and post-processing tutorials, please visit: 'https://udales.github.io/u-dales/'.

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