Urban Heat Island Dynamics in an Urban–Rural Domain with Variable Porosity: Numerical Methodology and Simulation

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Abstract

Heat transfer and fluid dynamics modeling in porous media is a widely explored topic in physics and applied mathematics, and it involves advanced numerical methods to address its non-linear nature. One interesting application has been the urban-heat-island (UHI) numerical simulation. The UHI is a negative consequence of the increasing urbanization in cities, which is defined as the presence of warm temperatures inside the urban canopy in contrast to the colder surroundings. Furthermore, an interesting phenomena occurs within a UHI context when the city transitions from a heat island to a cold island, matching the increases and decreases of solar radiation over the span of a day, as well as the decrease in the UHI intensity as a result of wind action. The numerical study in this paper had, as its main goal, to reproduce this phenomenon. Therefore, the key elements proposed in this work were the following: A 2D horizontal urban–rural domain that had a variable porosity with a Gaussian distribution centered in the city center. A non-stationary Darcy–Forchheimer–Brinkman model to simulate the flow in porous media, combined with an air–soil heat transport model linked by a balancing equation for the surface energy that includes the evapotranspiration of plants. In regards to the numerical resolution of the model, a classical numerical methodology based on the finite elements of Lagrange P1 type combined with explicit and implicit time-marching schemes have been effective for high-quality numerical simulations. Several numerical tests were performed on a domain inspired by the metropolitan region of Guadalajara (Mexico), in which not only the temperature inversion was reproduced but also the simulation of the UHI transition by strong wind gusts.

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García-Chan, N., Licea-Salazar, J. A., & Gutierrez-Ibarra, L. G. (2023). Urban Heat Island Dynamics in an Urban–Rural Domain with Variable Porosity: Numerical Methodology and Simulation. Mathematics, 11(5). https://doi.org/10.3390/math11051140

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