Post Date: 8 June 2026

Improving the Understanding and Modeling of Turbulent Transport Processes in the Atmospheric Boundary Layer Using Multi-scale Simulations

Abstract:

Accurate modeling of atmospheric boundary layer (ABL) dynamics is essential for understanding critical phenomena such as the urban heat island effect and air pollutant dispersion. However, capturing these dynamics in highly urbanized coastal environments like Hong Kong presents several challenges. Current numerical weather prediction (NWP) models suffer from inaccurate parameterizations of ABL due to an incomplete understanding of turbulent transport under varying atmospheric stabilities. Furthermore, traditional approaches struggle to represent the interactions between the ABL and dense urban canopies. The foundational Monin-Obukhov Similarity Theory (MOST) also remains largely unverified in such heterogeneous settings due to a scarcity of high-resolution observational data. Compounding these issues, the typical 1-km grid spacing of NWP models fails to resolve the fine-scale interactions between complex natural topography and built-up structures. To bridge these gaps, this doctoral research introduces a comprehensive multi-scale framework. By integrating observational analysis, mesoscale parameterization, and explicitly resolved microscale simulations, this work advances the modeling and physical understanding of atmospheric flows over complex urban terrains.

The research first addresses the representation of turbulent mixing in the ABL at the mesoscale by developing a novel non-local planetary boundary layer scheme (TKE-ACM2) in the Weather Research and Forecasting (WRF) model. By integrating a turbulent kinetic energy closure, the TKE-ACM2 scheme significantly improves the prediction of boundary layer structures. Subsequently, to explicitly resolve the drag and thermal impacts of heterogeneous building clusters, this scheme was coupled with a multi-layer Building Effect Parameterization (BEP). This integrated framework successfully mitigates long-standing biases in potential temperature and wind speed over urbanized regions.

Secondly, the research investigates the foundational assumptions of surface-layer meteorology over complex terrain using long-term high-resolution Doppler wind LiDAR observations. This analysis reveals several limitations in the classical Monin-Obukhov Similarity Theory (MOST), demonstrating that incorporating anisotropic roughness lengths and modified scaling parameters for realistic wind profile predictions.

Finally, high-resolution Large-Eddy Simulations (LES) were performed to investigate the non-linear interactions between realistic urban settings and heterogeneous topography. This fine-scale analysis revealed the phenomenon of kinematic fragmentation, where the buildings broke apart the macroscopic coherent structures induced by the natural terrain, shifting turbulent energy and scalar transport down to smaller canopy eddies. Ultimately, this work connects observations, theory, mesoscale modeling, and microscale simulations, offering robust predictive tools and physical insights into the urban boundary layer.