Effects of high-resolution building and urban data sets on the WRF/urban coupled model simulations for the Houston-Galveston areas
Fei Chen, NCAR, Boulder, CO; and M. Tewari and J. Ching
Today's mesoscale numerical weather prediction (NWP) models are routinely executed at a grid spacing of 1~4 km and used to provide meteorological conditions for air quality, transport and dispersion model forecast for urban areas. It is critical for these high-resolution NWP models to capture influences of urban forcing on wind, temperature, and humidity in the atmospheric boundary layer structures, so that air dispersion and quality models will benefit from improved prediction of the urban meteorological conditions. Among the daunting challenges in mesoscale urban modeling is the description of urban surfaces, which are highly heterogeneous even at small scales. The efforts in developing gridded fine-scale data sets of buildings, vegetation cover, and other morphological features in metropolitan areas, under the National Urban Database and Access Portal Tools (NUDAPT), provide an excellent opportunity to address this challenge. This paper describes an investigation of influences of incorporating the NUDAPT data set in the coupled Weather Research and Forecast (WRF)ľurban canopy modeling system on short-term simulations for selected high ozone-pollution events of 25-31 August 2000 over the Houston-Galveston areas. Two baseline simulations are conducted: one using the traditional approach of specifying urban parameters through a look-up table in WRF, the other directly ingesting gridded NUDAPT data sets. The simulation results are evaluated with observations obtained from the Texas Air Quality Study 2000 (TexAQS2000) field program. Additional sensitivity tests are performed to explore the relative contribution of each individual data set such as building morphological data, vegetation fraction, and anthropogenic data. .
Session 6, National Urban Database and Access Portal Tools (NUDAPT)
Tuesday, 11 September 2007, 3:45 PM-5:45 PM, Toucan
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