Despite building energy use being one of the largest global energy consumers, building energy simulations rarely take the actual local neighborhood scale climate into account. In this talk, I introduce our recent work on a new globally applicable approach to support buildings energy design based on urban climate modeling. Specifically, we use ERA5 (European Centre Reanalysis version 5) data together with SUEWS (Surface Urban Energy and Water balance Scheme) to obtain an urban typical meteorological year (uTMY) that is usable in building energy simulations. In an application in London, the predicted annual energy demand (heating and cooling) for a representative four-storey residential apartment using uTMY is 6.9% less (cf. conventional TMY). New vertical profile coefficients for wind speed and air temperature in EnergyPlus are derived using SUEWS. EneryPlus simulations with these neighborhood scale coefficients and uTMY data, predict the top two floors have ~10% larger energy demand (cf. the open terrain coefficients with uTMY data). Vertical variations in wind speed have a greater impact on the simulated building energy than equivalent variations in temperature. This globally appliable approach has been integrated into our open-source urban climate modeling tools – SuPy (SUEWS in Python) and UMEP (Urban Multi-scale Environmental Predictor) – to provide a more accessible workflow for generating local meteorological data for building energy modeling. Such open tools not only allow more transparent and reproducible science in urban climate, but also facilitate the industrial applications of our research outcomes for improving urban landscape design.
Dr. Ting Sun is a climate scholar for cities with a multidisciplinary background in hydrology, meteorology, and built environment. His research interests include impact of weather and climate extremes (e.g., heat waves, extreme rainfall) in cities and urban climate modelling across scales (from neigborhood to globe) as well as their broad linkages with public health and building energy sectors. He holds a NERC Independent Research Fellowship to lead the project entitled, "Building Resilient Cities for Heat Waves." He is enthusiastic about urban climate modelling--in particular, in the role of lead developer in a state-of-the-art urban climate model SUEWS (Surface Urban Energy and Water balance Scheme) and its Python wrapper SuPy (SUEWS in Python) jointly with the micromet team led by Prof. Sue Grimmond at University of Reading. Besides, he is a core member of UMEP (Urban Multi-scale Environment Predictor) development team.