Earth Materials and Processes; ECP Early Career Program: Quantifying the Impact of Surface Uncertainties on the Aerodynamic Properties of Built Environments

The rapid growth of the urban population and the looming threat of climate change has prompted a stronger focus on the identification of optimal strategies to make our cities more sustainable and resilient. Being able to understand and predict how the urban form and its materials properties affect the exchange of mass, energy and momentum with the atmosphereÑthe main drivers of urban climate variabilityÑat both local and area-aggregate scales is key towards the development of these strategies. These exchanges are regulated by the interaction of the urban environment with atmospheric winds, which takes places over a wide continuum of temporal and spatial scales and poses a formidable challenge our conceptual understanding and ability to predictively model it. Of relevance for this project is the fact that although numerical models have become highly sophisticated in terms of physical processes that they can accurately represent, their predictive capabilities still largely depend on the quality of input parameters. These include surface geometry and related material properties, which cannot be measured exactly in urban areas. Recent advances in computational fluid dynamics (CFD) models, uncertainty quantification (UQ) techniques, and digital surface data offer a promising pathway for bridging this knowledge gap. Our driving hypothesis is that a CFD-based UQ framework can be used along with in-situ measurements and Lidar-derived surface models to accurately and efficiently quantify the impact of surface uncertainties on exchange processes in urban environments. To test this hypothesis, this project will seek to determine how the neighborhood-averaged momentum fluxÑan important process from an urban-microclimate perspectiveÑis affected by uncertain terrain and building surface roughness, as well as tree geometry. To achieve this objective, we will: (i) collect in-situ measurements of wind velocity and momentum fluxes in the Lamont Doherty Earth Observatory campus at Columbia University; ii) develop a digital surface model from the broadly available 3DEP Lidar dataset; iii) develop and validate a CFD-based UQ framework that makes use of the in-situ measurements to quantify uncertainties in the digital surface model and efficiently propagate them to selected flow statistics; (iv) use the validated framework to quantify and characterize the impact of surface uncertainties on flow statistics for representative but distinct urban forms; and v) to develop a simple predictive model that relates urban morphology to corresponding aerodynamic parameters with error bounds. Findings and methodologies stemming from this project would be of significant value to the Army and for civilian applications. A probabilistic characterization of built surfaces and their impact on local weather will facilitate ground military operations, give that terrain morphology and local weather can impact the ability of soldiers to conduct operations, as well as challenges the use of small unmanned aerial vehicles, radio communications, and technologies relying on optics. At an area-aggregate level, being able to accurately predict the aerodynamic properties of urban surfaces with a given probability will enhance the predictive capabilities of urban weather forecasting, which military operations routinely rely on and which impacts the everyday life of civilians. Further, by providing a more nuanced understanding of how surface morphology affects the aerodynamic properties of an urban area, this project will help urban planners and policy makers make our cities more sustainable and resilient. Our findings will also influence fundamental thermo-fluid sciences by elucidating physical mechanisms underpinning momentum transfer over aerodynamically rough surfaces.