Paper Conference

Proceedings of BSA Conference 2017: Third Conference of IBPSA-Italy

     

Investigating the Suitability of the WRF Model for Improving Prediction of Urban Climate Boundary Conditions

Kristopher Hammerberg, Oscar Brousse, Ardeshir Mahdavi

Abstract: Urban populations continue to increase in parallel with global temperatures. The result is an increasing number of people affected by increasingly severe urban heat conditions. Understanding these effects and being able to accurately account for the effects of the urban climate on building energy use is important for urban and architectural design decision making. This paper presents part of an on-going research effort to evaluate the Weather Research and Forecasting (WRF) model as a tool for improving prediction of boundary conditions in urban climates. WRF is a regional climate model that is capable of downscaling global weather data to a fine resolution and includes detailed urban canopy models. The use of a numerical model in urban climate studies would allow for computational experiments involving changes to the urban fabric and future climate scenarios. In this study, Vienna, Austria, was used as a test case. The weather was simulated over five 48-hour periods, which were selected using cluster analysis to best represent typical weather conditions in Vienna. The model results were then compared to data collected from a network of 170 weather stations throughout the region of interest. Additionally, the land-use classification and urban parameterization in the model domain were improved using high-resolution GIS data from the city of Vienna. Results show a great deal of variation in the accuracy of the model under different weather conditions. Although individual problems can be identified during specific intervals, there is no obvious trend or bias to the variation across all time periods. The extent of the variation indicates the model results are not suitable for use as boundary conditions for building performance models throughout an entire year.
Pages: 411 - 419
Paper:
bsa2017_9788860461360_52