Univ. of Texas at Austin"> Abstract: Development of GLObal Building Heights for Urban Studies (UT GLOBUS) for City and Street Scale Urban Microclimate Simulations. (104th AMS Annual Meeting) Univ. of Texas at Austin">

E95 Development of GLObal Building Heights for Urban Studies (UT GLOBUS) for City and Street Scale Urban Microclimate Simulations.

Thursday, 1 February 2024
Hall E (The Baltimore Convention Center)
Aditya Patel, Univ. of Texas at Austin, Austin, TX; and H. Kamath, M. Singh, A. Martilli, N. Malviya, L. He, L. A. Magruder, D. G. Aliaga, C. He, F. Chen, Z. L. Yang, and D. Niyogi

As concerns about urban hazards' impact on economies and public health grow, there's a rising interest in developing more detailed models of urban microclimates at finer scales. Existing models can simulate phenomena at city and street-scales, but the lack of specific building data for model input acts as a bottleneck. Typically, light detection and ranging (LiDAR) surveys and satellite photogrammetric digital surface models (DSM) are used to obtain building-level information. However, LiDAR surveys have limited global availability and coverage, and DSM data is often noisy and requires additional processing to generate accurate DSMs. Further, these datasets are generally not open-source, and are not directly compatible with models. To address this, we introduce GLObal Building heights for Urban Studies (GLOBUS), a level of detail-1 building dataset that utilizes open-source spaceborne data and a random forest model to predict building-level information. This study compares GLOBUS-derived building heights with LiDAR data and presents why urban canopy parameters are necessary for city-scale modeling.

Our research demonstrates that GLOBUS enhances intra-urban heterogeneity in air and land surface temperature in the Weather Research and Forecasting (WRF-Urban) model, when compared to the conventional table-based local climate zone approach. We also demonstrate how GLOBUS can be used to simulate building energy use on a city scale using WRF-Urban, and heat management tactics such as cool roofs, green roofs, cool pavements, yielding valuable insights into the underlying physical processes. Lastly, we compare street-level simulations using the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model, using GLOBUS and LiDAR-derived building data, to highlight GLOBUS's utility in presenting valuable insights into pedestrian-level thermal comfort and planning heat mitigation strategies.

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