Mesoscale circulations in the urban-coastal environment: a modeling analysis and assessment of sensitivity to high-fidelity representation of the urban canopy

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Wednesday, 20 January 2010: 11:15 AM
B215 (GWCC)
Michael Carter, Mississippi State University, Mississippi State, MS; and J. M. Shepherd, S. Burian, and I. Jeyachandran

The unique characteristics of urban-coastal environments generate complex mesoscale circulations, which affect weather and climate as well as alter dispersion and transport in and around coastal cities. Proper characterization and prediction of thermodynamic and dynamic processes in such environments are warranted. This study reveals the complex interactions among the sea breeze, urban heat island, and urban-induced convergence/vertical velocity anomaly here called the “convective pump.” Using a coupled atmosphere-land surface-urban canopy modeling system the structure and evolution of these urban-coastal circulations are successfully simulated for Houston, TX. Results confirm that while coastal morphology can itself lead to complex sea breeze front structures, including preferred areas of vertical motion, the urban environment also has a large impact on the evolution of the sea breeze mesoscale boundary. Using traditional metrics for urban climate studies (e.g. temperature, convergence, and vertical velocity) and a new approach, the Bulk Richardson Number shear, the detailed interactions between Houston's urban land cover and the sea breeze life cycle are captured. A conceptual model of this process is also presented. Further, this study establishes the importance of high fidelity representation of the urban canopy to simulations of the urban-coastal environment. The inclusion of lidar-derived urban canopy parameters in the model's land surface representation led to significant differences in patterns of skin surface temperature, convergence, and vertical motion which have implications for all aspects of urban weather. In some locations, simulations with enhanced urban canopy parameters reduced bias in temperature measurements by 9.3% of a standard deviation when compared to in-situ measurements