Generating Urban-Scale Building Data to Support Climate Modeling

Cities are a spatial nexus for a host of environmental issues including global climate change, urban air pollution, energy management, flood control, exposure to hazards, and so on. Research on these topics and others often requires geographic data on the urban landscape and occupation patterns at appropriate time and space scales to understand processes and design responses. The World Urban Database and Access Portal Tools (WUDAPT) project was initiated to acquire, store and disseminate climate-relevant information on cities, globally (Ching et al., 2018). The key properties of WUDAPT is that it should contain internationally consistent information on urban landscapes (known as urban canopy parameters) and should be available at useful scales to support climate modelling and observation studies. Practically, it orgainises this data into levels of precision, the lowest (Level 0) of which uses the local climate zone (LCZ) scheme to describe neighbourhoods (>1km²) and their associated properties. The highest levels of urban data (Levels 1&2) provides information on the individual urban elements (especially buildings) that are significant drivers of climate and weather modification at urban scales. The WUDAPT project has made significant advances in generating L0 data (e.g. Demuzere et al, 2019) and the project is now focussed on higher level data such as the morphological properties (form) of buildings at a city block scales (Ching et al, 2019).

This paper uses a building typology approach (http://episcope.eu/) to acquire building level data on building material (fabric) and estimated energy demand. It applies this approach to create a geographic database of buildings in the city centre of Dublin (Ireland). The resulting Level 2 dataset can be used to generate UCPs on the thermal and radiative properties of the urban surface for climate models and to run urban building energy models (UBEM) that are capable of simulating neighbourhood scale energy use and evaluating energy policies (see Davila et al., 2016; Reinhart and Davila, 2016). This research contributes the development of a holistic urban modelling initiative by linking the indoor and outdoor climate perspectives, which are traditionally studied in separate disciplines but have shared information needs. In addition, this work contributes to the development of protocols for the generation of consistent and coherent information to support the WUDAPT project.

Ching, J. et al., 2018. WUDAPT: An urban weather, climate, and environmental modeling infrastructure for the anthropocene. Bulletin of the American Meteorological Society, 99(9), pp.1907-1924.

Ching, J. et al., 2019, Pathway using WUDAPT’s Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling. Urban Climate (28)100459.

Davila, C.C. at al., 2016. Modeling Boston: A workflow for the efficient generation and maintenance of urban building energy models from existing geospatial datasets. Energy, 117, pp.237-250.

Demuzere, M. et. al., 2019. Mapping Europe into local climate zones. PloS one, 14(4), p.e0214474.

Reinhart, C.F. and Davila, C.C., 2016. Urban building energy modeling–A review of a nascent field. Building and Environment, 97, pp.196-202.