Developing an integrated urban modeling
system for the WRF model
NCAR/RAP
Abstract:
Rapid
expansion of urban areas caused many adverse effects on air quality,
energy and water supply/demand, and emergency response. Meanwhile,
today’s numerical weather prediction (NWP) models run with grid spacing
of 1 km, and at such fine scales, the role of urban land-use in local
and regional weather needs to be represented.
It is important for NWP models to capture the effects of urban areas on
wind, temperature, and humidity in the boundary layer and their
influences on the boundary layer depth. Air dispersion and quality
models will benefit from improved prediction of the urban
meteorological conditions. We are developing an integrated
urban modeling system coupled to the WRF/Noah land surface model as a
tool to address urban environmental issues and to study
urban-atmospheric interactions. This urban modeling system consists of
different methods to parameterize urban land use, a consistent
treatment of canopy resistance for both NWP and
air-pollution applications, surface biogenic and anthropogenic
emissions maps, remote-sensing land-use and characteristics at urban
scale, and a companion high-resolution land data assimilation system.
It was applied to various metropolitan areas (Houston, Oklahoma City,
Hong Kong, Tokyo) and evaluated against urban-scale
observations, which showed that representing the urban heat island
effects is critical to correctly capture mesoscale and urban-scale wind
fields. The predictions produced by the coupled WRF/Noah/urban model
with 0.5-km grid spacing were used to drive a
computational-fluid-dynamic (CFD)-model-based transport
and dispersion model for a case study during the Urban 2000 field
experiment conducted in the Salt Lake City. The statistical results
indicate that the use of the WRF forecast data in conjunction with the
quasi-steady CFD-Urban model has resulted in a significant improvement
(by four or five times) in micro-scale transport
and dispersion model accuracy over using single sounding data.