Abstract

Abstract. The digital terrain model (DTM), the representation of earth's surface at regularly spaced intervals, is the first input in the computational modelling of atmospheric flows. The ability of computational meshes based on high- (2 m; airborne laser scanning, ASL), medium- (10 m; military maps, Mil) and low-resolution (30 m; Shuttle Radar Topography Mission, SRTM) DTMs to replicate the Perdigão experiment site was appraised in two ways: by their ability to replicate the two main terrain attributes, elevation and slope, and by their effect on the wind flow computational results. The effect on the flow modelling was evaluated by comparing the wind speed, wind direction and turbulent kinetic energy using VENTOS®/2 at three locations, representative of the wind flow in the region. It was found that the SRTM was not an accurate representation of the Perdigão site. A 40 m mesh based on the highest-resolution data yielded an elevation error of less than 1.4 m and an RMSE of less than 2.5 m at five reference points compared to 5.0 m in the case of military maps and 7.6 m in the case of the SRTM. Mesh refinement beyond 40 m yielded no or insignificant changes on the flow field variables, wind speed, wind direction and turbulent kinetic energy. At least 40 m horizontal resolution – threshold resolution – based on topography available from aerial surveys is recommended in computational modelling of the flow over Perdigão.

Highlights

  • A digital terrain or digital elevation model (DTM or DEM) is a representation of the earth’s surface elevation at regularly spaced horizontal intervals

  • The terrain model is the first input in computational modelling of atmospheric flows, its impact on flow results has not been a matter of concern because the spatial resolution of publicly available digital terrain model (DTM) is higher than the size of the computational grid often used to resolve the terrain

  • With the advent of high-resolution techniques such as lidar aerial survey, terrain data have become available with resolutions above 10 m and vertical accuracy typically below 0.2 m (Hawker et al, 2018), and the question is whether such high resolution is needed in the computational modelling of atmospheric flows over complex terrain

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Summary

Introduction

A digital terrain or digital elevation model (DTM or DEM) is a representation of the earth’s surface elevation at regularly spaced horizontal intervals. The terrain model is the first input in computational modelling of atmospheric flows, its impact on flow results has not been a matter of concern because the spatial resolution of publicly available DTMs is higher than the size of the computational grid often used to resolve the terrain. For studies of the atmospheric flow over Perdigão the publicly available DTMs were considered not accurate enough (Mukherjee et al, 2013; Simpson et al, 2015), and an airborne laser scanning (ASL) campaign of the region was carried out in 2015, first to assist the design of the Perdigão campaigns in 2015 and 2017 (cf., Vasiljevicet al., 2017; Fernando et al, 2019) and second to provide the highresolution terrain data for computational flow modelling, on par with the resolution provided by the large amount of measuring equipment within a small region. With the advent of high-resolution techniques such as lidar aerial survey, terrain data have become available with resolutions above 10 m and vertical accuracy typically below 0.2 m (Hawker et al, 2018), and the question is whether such high resolution is needed in the computational modelling of atmospheric flows over complex terrain

Literature review
Objectives and outline
Topographical surveying: equipment and techniques
Lidar point cloud processing
Buildings
Two-dimensionality and main geometrical parameters
Terrain profile and slope
Digital terrain model: results and discussion
Mesh generation
Elevation at five reference points
Spectra analysis
Flow modelling
Computational flow model
Integration domain and boundary conditions
Computational meshes
Flow pattern
Southwesterly winds
Findings
Discussion and conclusions
Full Text
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