Fast urban heat island model for thermal comfort studies

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Wednesday, 5 February 2014: 8:30 AM
Room C212 (The Georgia World Congress Center )
Julien Le Bras, CNRM, Toulouse, France

The thermal comfort of urban residents is mainly affected by the Urban Heat Island (UHI) effect ( difference in air temperature between urban and surrounding area). This effect is caused by anthropogenic sources, low vegetated areas and heat stored in buildings and roads released during the night. In case of heat wave, strong UHIs occur and mortality rates can increase in towns. Indeed, the air temperature difference between the city center and the suburbs can reach 10K for the biggest urban areas. A tool to simulate UHI fast and with only a few meteorological information can be useful for the community studying the thermal comfort. Such a model will be presented. In our study, the surface is modeled by the SURFEX model. The SURFEX surface model contains an urban canopy model, TEB, a soil-vegetation-atmospheric transfer model, ISBA and a water surface models. SURFEX can be used on-line (coupled with a mesoscale atmospheric model) or off-line (forced with meteorological conditions above the canopy layer). The off-line approach has a low computational cost but needs meteorological information that only specialized professional community can obtain through mesoscale simulations or short- time experiments. In order to make urban climate predictions accessible to other communities such as building engineers or urban planner, a method to calculate meteorological forcing for surfaces models with weather data files from an operational measurement stations outside the city is presented. This method has multiple advantages. First, these files can easily be found for a lot of cities, in most case in airports. Second, the forcing temperatures calculated can be influenced by urban planning scenarios. Finally, the method is adapted for cities surrounded by plains or for coastal cities. The methodology presented integrates day-time and night-time boundary layers, impact of the wind and the sea. An iterative method is used to extrapolate measure information at the forcing level above the canopy. At each time-step, the UHI is calculated on a two dimensional grid with a 2km mesh-size. The energy budget of the whole boundary layer for each 4kmē grid mesh is computed. Note that the boundary layer height also evolves due to this energy budget. The mean temperature of a column with a height corresponding to the boundary layer height is calculated with the surface heat flux given by the surface model. In order to take into account wind effects, the 2D field of temperature is also advected with a 2D lagrangian advection model. The iterative method has bean validated with data of a 30 meter mast at the airport of Roissy, France, which provides temperature, humidity at 2m and 30m and wind at 10m and 30m. The UHI modeling has been simulated over the city of Paris, France and its suburbs. The method has been validated with an operational weather station network giving minimal temperatures over the region of Paris during the years 2001 to 2010. For coastal cities, the model has been validated by a mesoscale atmospheric model Meso-NH simulation and data of the field campaign ESCOMPTE in Marseille, France.