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Sunlit fractions on urban facets: impact of spatial resolution and approach

Lindberg, F., Grimmond, C. S. B. and Martilli, A. (2015) Sunlit fractions on urban facets: impact of spatial resolution and approach. Urban Climate, 12. pp. 65-84. ISSN 2212-0955

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To link to this article DOI: 10.1016/j.uclim.2014.11.006

Abstract/Summary

The extent of the surface area sunlit is critical for radiative energy exchanges and therefore for a wide range of applications that require urban land surface models (ULSM), ranging from human comfort to weather forecasting. Here a computational demanding shadow casting algorithm is used to assess the capability of a simple single-layer urban canopy model, which assumes an infinitely long rotating canyon (ILC), to reproduce sunlit areas on roof and roads over central London. Results indicate that the sunlit roads areas are well-represented but somewhat smaller using an ILC, while sunlit roofs areas are consistently larger, especially for dense urban areas. The largest deviations from real world sunlit areas are found for roofs during mornings and evenings. Indications that sunlit fractions on walls are overestimated using an ILC during mornings and evenings are found. The implications of these errors are dependent on the application targeted. For example, (independent of albedo) ULSMs used in numerical weather prediction applying ILC representation of the urban form will overestimate outgoing shortwave radiation from roofs due to the overestimation of sunlit fraction of the roofs. Complications of deriving height to width ratios from real world data are also discussed.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Soil Research Centre
Central Services > Chief Operating Officers Group > IT Services
Central Services > Academic and Governance Services > Library
Interdisciplinary centres and themes > Centre for Technologies for Sustainable Built Environments (TSBE)
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:38731
Publisher:Elsevier

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