B33E-0765
Validation of a Fast-Response Urban Micrometeorological Model to Assess the Performance of Urban Heat Island Mitigation Strategies
Wednesday, 16 December 2015
Poster Hall (Moscone South)
Daniel Nadeau1, Pascale Girard2, Matthew Overby3, Eric Pardyjak4, Rob Stoll II5, Peter Willemsen3, Brian Bailey4 and Marc B Parlange6, (1)Laval University, Civil and Water Engineering, Quebec City, QC, Canada, (2)Laval University, Quebec City, QC, Canada, (3)University of Minnesota Duluth, Duluth, MN, United States, (4)University of Utah, Mechanical Engineering, Salt Lake City, UT, United States, (5)University of Utah, Salt Lake City, UT, United States, (6)Swiss Federal Institute of Technology Lausanne, Lausanne, Switzerland
Abstract:
Urban heat islands (UHI) are a real threat in many cities worldwide and mitigation measures have become a central component of urban planning strategies. Even within a city, causes of UHI vary from one neighborhood to another, mostly due the spatial variability in surface thermal properties, building geometry, anthropogenic heat flux releases and vegetation cover. As a result, the performance of UHI mitigation measures also varies in space. Hence, there is a need to develop a tool to quantify the efficiency of UHI mitigation measures at the neighborhood scale. The objective of this ongoing study is to validate the fast-response micrometeorological model QUIC EnvSim (QES). This model can provide all information required for UHI studies with a fine spatial resolution (up to 0.5m) and short computation time. QES combines QUIC, a CFD-based wind solver and dispersion model, and EnvSim, composed of a radiation model, a land-surface model and a turbulent transport model. Here, high-resolution (1 m) simulations are run over a subset of the École Polytechnique Fédérale de Lausanne (EPFL) campus including complex buildings, various surfaces properties and vegetation. For nearly five months in 2006-07, a dense network of meteorological observations (92 weather stations over 0.1 km2) was deployed over the campus and these unique data are used here as a validation dataset. We present validation results for different test cases (e.g., sunny vs cloudy days, different incoming wind speeds and directions) and explore the effect of a few UHI mitigation strategies on the spatial distribution of near-surface air temperatures. Preliminary results suggest that QES may be a valuable tool in decision-making regarding adaptation of urban planning to UHI.
