Sub-Facet Heterogeneity of the Urban Surface Energy Budget

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Tuesday, 4 February 2014: 3:30 PM
Room C212 (The Georgia World Congress Center )
Elie Bou-Zeid, Princeton University, Princeton, NJ; and P. Ramamurthy, J. Smith, M. L. Baeck, and C. Welty

Current urban canopy models mostly ignore the strong spatial variability in the properties and characteristic of the urban fabric. Only three types of surfaces associated with the three facets - roofs, walls, and ground - are captured. Observation data however strongly suggest that surface variability at the sub-facet scale is preponderant and has implications from the street-scale to the city-scale. The Princeton Urban Canopy Model (PUCM) was developed with the ability to represent this sub-facet heterogeneity.

In this study, PUCM and observational data are combined to study the urban surface energy budgets of individual homogeneous sub-facets composed of different materials, and how they aggregate to determine the city scale surface energy budget. The different surfaces and materials (asphalt, concrete, grass, black roofs, white roofs, etc.) are shown to have strikingly different responses to the diurnal variation in incoming radiation. Particular emphasis is placed on the role of water storage and evaporation from urban surfaces in modulating the energy budget.

Our analyses show that while all built surfaces convert most of the incoming energy into sensible rather than latent heat, sensible heat fluxes from asphalt and non-reflective rooftops are twice as high as those from concrete surfaces and light colored roofs. Another important and commonly observed characteristic of urban areas - the shift in peak time of sensible heat compared to rural areas - is shown to be mainly linked to concrete's high heat storage capacity. Our results also indicate that while evaporation from built surfaces is discontinuous and intermittent, overall, these surfaces accounted for nearly 16% of latent heat fluxes (LE) at the study site during the simulated period. More importantly, this contribution is mainly concentrated during the 48 hours following a rain event, and hence its accurate representation is critical to our understanding of the urban surface energy budget during wet periods.