Meteorology and air quality modeling with advanced urban data and canopy parameterizations for Houston, TX

We investigate the use of the canopy drag approach (DA), a boundary layer parameterization method developed to provide realistic meteorological and air quality modeling of urban areas. The method explicitly simulates the effects of buildings, street and tree canopies on the dynamic, thermodynamic structure and dispersion fields in urban areas. This approach is a major departure from the standard roughness approach (where boundary layer scaling of roughness and displacement height are ascribed a value associated with the dominant land use class in each grid). Here, the boundary layer parameterizations are based on actual surface distributions of urban morphological features. The method also incorporates within-grid land use variations with an advanced urbanized surface layer (soil-atmosphere) model (SM2-U). The implementation into the NCAR-Penn State Mesoscale Meteorological Model, Version 5 (MM5) called DA-SM-2U/MM5 requires gridded surface and vertical profiles of urban canopy parameterizations (UCP) and a canopy layer structure. This initial implementation used a set of UCPs of 1 km grid size derived from 3-D high resolution (order 1m) buildings and vegetation data from airborne lidar measurements, satellite data, high altitude photography, as well as detailed residential, commercial and industrial maps.

Standard MM5 runs were performed at 36,12 and 4 km grid sizes; the latter provided the initial and boundary conditions for both the standard, roughness-based, and the DA-SM-2U/MM5 simulations at 1 km grid size. These multi-scale meteorology fields were then used to simulate air quality using the USEPA's Community Multiscale Air Quality (CMAQ) Model. The 1 km grid simulations show considerable differences in the transport fields, in the character (strength and evolution) of the urban heat island, and in the air quality simulations. Observations support the use of this advanced approach.

Disclaimer: The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW13921548. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.