Preprints
https://doi.org/10.5194/egusphere-2026-4950
https://doi.org/10.5194/egusphere-2026-4950
28 Sep 2026
 | 28 Sep 2026
Status: this preprint is open for discussion and under review for Earth System Dynamics (ESD).

A framework to assess the impacts of urbanization on meteorological dynamics in megacities

Aasif Ahmad Wagay, Pauli Paasonen, Tuukka Petäjä, Victoria Sinclair, Sarath Guttikunda, and Shahzad Gani

Abstract. Urbanization modifies near-surface meteorology through changes in surface energy exchange, aerodynamic roughness, and boundary-layer development, with important implications for urban heat exposure and air quality. Although many studies have examined these effects in individual cities, a consistent, transferable framework for comparing urban meteorological signals across megacities remains lacking, and the extent to which such signals are shaped by the characteristics of the surrounding reference environment is rarely quantified. Here, we present a WRF based radial framework to diagnose urban rural contrast in near-surface meteorology and demonstrate its applicability across 20 global megacities during two contrasting months, May and October 2024. The framework characterizes radial variations in 2 m air temperature (T), 10 m wind speed (WS), and planetary boundary layer height (PBLH) using concentric 5 km circular rings extending 60 km from the city centres, from which a reproducible Urban–radial Contrast (URC) metric is derived. The framework further accounts for the influence of mixed land-ocean sampling and elevation differences within the reference environment, allowing the diagnosed URC to be decomposed into urbanization-attributed (URCUA), ocean-attributed (URCOA), and elevation-attributed components (URCEA).

Application of the framework reveals consistent urban signatures in both months, characterized by warmer temperatures, deeper boundary layers, and weaker near-surface winds over urban cores relative to their surrounding reference environments, with stronger and more consistent contrasts in inland than in coastal megacities. Accounting for ocean and elevation-attributed contributions, however, substantially reshapes this picture in topographically complex cities. The strongest URCUA-T occurs at night, reaching 6.1 and 6.0 °C in Delhi and Lahore, respectively, in October. Terrain complex cities such as Tehran and Mexico City exhibit the largest simulated nocturnal URC-T values of 7.6 and 5.1, respectively, which decrease to 3.6 and 3.2 (URCUA-T) after accounting for the elevation-attributed contribution, although both remain among the strongest warming signals in the ensemble. Coastal cities exhibit much weaker nocturnal URC-T, generally ranging from 0.7 to 2.1 °C. The urban wind-speed deficit persists during both daytime and nighttime, with the strongest URC-WS occurring in Los Angeles (−2.0 m s⁻¹; nighttime, October) and Tehran (−1.8 m s⁻¹; daytime). In contrast, the strongest urban enhancement of PBLH occurs during the daytime, with URC-PBLH reaching 592 m in Tehran (May), 489 m in Mexico City (May), and 526 m in Delhi (October). These diagnosed Urban–radial Contrasts, particularly their urbanization-attributed component, have important implications for pollutant dispersion and urban air quality in rapidly urbanising megacities.

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Aasif Ahmad Wagay, Pauli Paasonen, Tuukka Petäjä, Victoria Sinclair, Sarath Guttikunda, and Shahzad Gani

Status: open (until 09 Nov 2026)

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Aasif Ahmad Wagay, Pauli Paasonen, Tuukka Petäjä, Victoria Sinclair, Sarath Guttikunda, and Shahzad Gani
Aasif Ahmad Wagay, Pauli Paasonen, Tuukka Petäjä, Victoria Sinclair, Sarath Guttikunda, and Shahzad Gani
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Short summary
Urbanization changes temperature, winds, and boundary layer height, affecting heat exposure and air quality. We develop a framework to quantify these changes across 20 global megacities using WRF simulations. Urban effects are generally stronger inland, while terrain and ocean can influence the apparent signal. Because these variables control atmospheric mixing and pollutant dispersion, understanding urban changes is essential for assessing air quality and exposure.
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