P1.21 IMPLEMENTATION OF AN URBAN CANOPY PARAMETERIZATION IN MM5 FOR MESO-GAMMA-SCALE AIR QUALITY MODELING APPLICATIONS Tanya L. Otteu and Avraham Lacser2 NOAA Air Resources Laboratory, Research Triangle Park, North Carolina 10n assignment to the National Exposure Research Laboratory, US EPA, Research Triangle Park, NC. 2 On leave from Israel Institute for Biological Research, Ness Ziona, Israel. 1. introduction The U.S. Environmental Protection Agency {U.S. EPA) is extending its Models-3/Community Multiscale Air Quality (CMAQ) Modeling System to provide detailed gridded air quality concentration fields and sub-grid variability characterization at neighborhood scales and in urban areas. CMAQ is an advanced air quality modeling system that embodies a "one-atmosphere," multiple-pollutant philosophy (Byun and Ching, 1999). There are three primary models within Modeis-3/CMAQ: meteorology, emissions, and chemistry. The meteorology model used with CMAQ in this application is the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5; Grell etal. 1994). For fine-scale urban simulations (~1-km grid spacing), MM5 has been modified to include an urban canopy parameterization that accounts for drag exerted by the urban structures, the enhancement of turbulent kinetic energy (especially near the top of the buildings), and the energy budget at the street and roof levels. This refinement of MM5 is targeted to provide CMAQ with the means to capture the details of pollutant spatial distributions at these scales. One of the goals of this research is to demonstrate the capability of MM5 to simulate the effects of urban areas at the meso-gamma scale. This paper describes the suggested modifications to MM5 and presents preliminary results of using the urban canopy parameterization. 2. Urban Canopy Parameterization To consider urban effects in a numerical model with horizontal grid spacing on the order of 1 km, some parameterization is suggested to account for effects of the urban canopy (e.g., buildings) on the flow and on the heat budget. This urban canopy parameterization is applied to grid cells in MM5 that have a non-zero fraction of urban land use. 2.1 Momentum The horizontal components of the momentum equations were modified to account for the area average effect of the sub-grid urban elements following Brown (2000). The modifications were implemented in MM5 via the TKE-based Gayno- Seaman PBL parameterization scheme (e.g., Shafran etal. 2000). The momentum equations accounting for the urban elements are: fpFu -0.5UCaA(z)U {J2 +V2f5 fpFv-05fU!bCdA(z)V (J2 +V2f* = Fm£ + 0.5UCdA(z)(u2 +V2 + W2f where F are the general forcing terms in each equation; U, V, and W are the wind components; and TKE is the turbulent kinetic energy. In this formulation, it is assumed that the buildings affect the flow, but do not take up any volume within the grid cell. Cd is a drag coefficient (assumed to be constant and set to 1). The urban fraction of the grid cell is described by A(z) is the canopy area density, or the surface area of the obstacle (e.g., building) perpendicular to the wind, per unit volume of the urban canopy, expressed in nrf1. There are several approaches to describe A(z) (e.g., Uno etal. 1989, Brown 2000) where the function reaches its maximum at the ground level, but vanishes at the top of the obstacles (so the drag term vanishes also at that level). The integral of A(z) from the ground level to the top of the buildings is "kf, which corresponds to the ratio of the frontal area to the total surface area of the + Corresponding author address: Tanya L. Otte, U.S. EPA/NERL/AMD, Mail Drop 80, Research Triangle Park, NC 27711; e-mail: tlott0@hpcc.epa.gov ------- buildings. In general A(z) is a function of the location within the domain as it depends on building morphology. Ratti etal. (2001) suggests a method of obtaining and building height (H) from digital imagery. A(z) can then be estimated from lf and H. For simplicity, we initially assumed a linear functional form for <4(z), To solve the modified momentum equations (the added new term) we followed the analytical solution suggested by Byun and Arya (1986). The TKE equation was solved explicitly. To take proper account of the influence of A(z), the vertical resolution in MM5 was increased in the domain where the urban canopy was applied such that several prognostic layers are below H. 2.2 Energy Budget To account for the impact of urban settings on the energy budget, the anthropogenic heat flux is included in the heat equation and not in the surface energy budget (e.g., Chin etal. 2000). The heat equation also includes the heat contribution of the rooftops and city canyons. The surface energy balance will include in the urban part the effect of the net radiation reaching the ground in the city canyons. The energy budget has not yet been modified for the urban canopy. 3. Preliminary Runs The unmodified MM5 was run in a one-way nested mode for several days in July 1995 during which there was a high-ozone episode in the Northeastern U.S. that coincided with a photochemical field study (e.g., Seaman and Michelson 2000). The MM5 domains included a five-domain configuration (108, 36,12, 4, and 1.33 km horizontal grid spacing) with 30 vertical layers (about 12 layers in the PBL, and lowest level at 19 m) and physics options appropriate for each resolution. As expected, the initial 1,33-km runs with the urban canopy showed that "buildings" below the lowest prognostic level did not have an impact on the flow. Thus, the 1,33-km domain was run with the urban canopy parameterization on a 40-layer configuration to include smaller obstacles and better simulate the increase in TKE near the tops of the buildings. The 40-layer run included 10 new layers in the lowest 100 m (lowest level at 2 m). Initially, the urban canopy assumed H = 40 m and kf= 0.4 for urban areas. In this application, MM5 is using the 24-category USGS land use database that has only one urban category (Figure 1); ideally, urban areas should be represented by several sub-categories. The 12- and 4-km runs provide a baseline for comparing the 1,33-km simulation with and without the urban canopy to observational data. Figure 1. The 1,33-km MM5 domain covering the Philadelphia metropolitan area, including parts of Pennsylvania, New Jersey, Delaware, and Maryland. Grid cells with "urban" land use are in black; all other land use categories are in gray. Figure 2 shows the difference between TKE fields from two 40-layer, 1,33-km MM5 runs with and without the initial urban canopy parameterization (urban canopy minus standard). The TKE fields are from the eighth horizontal level above the surface (-35 m), selected to be within the canopy and near the tops of the buildings (H). The frame is valid 1500 UTC 14 July 1995. As intended, the TKE increased with the urban canopy parameterization specifically over the urban areas (cf. Figures 1 and 2). Also as expected, there is a net decrease in wind speed within the urban canopy (Figure 3), and the impact of the urban area is felt in the surrounding areas. Figure 4 shows the vertical profiles of the TKE and wind speed differences (from the same two runs as in Figures 2 and 3) in the lowest 300 m AGL as a function of time at a point within the urban domain. In both sets of profiles, the absolute maximum difference occurs near the tops of the buildings (H), and the impact of the change decreases through the canopy and toward the surface. This tendency In the TKE and wind speed fields is similar to wind tunnel ------- measurements of a simulated urban area (e.g., Kastner-Klein and Rotach, 2001). Figure 5 shows the wind speed profiles from the model simulations with and without the urban Figure 2. Difference of TKE field, 8 levels above the surface (within the urban canopy and near the top of the buildings) between 1.33-km runs with and without the urban canopy parameterization. Valid 1500 UTC 14 July 1995, 15 hours into the simulation. Positive TKE differences with the urban canopy parameterization are in white; negative differences are in gray. Field values range from -0.30 to 4.75 m2 s . Figure 3. Same as Figure 2, but for wind speed. Decreases in wind speed with the urban canopy parameterization are in dark gray (absolute decrease greater than 1.5 m s'1) and white (zero to -1.5 ms"1); increases are shown in light gray. Field values range from -5.50 to 0.89 m s"1. canopy parameterization for the same grid point shown in Figure 4. As suggested by Figure 4, the urban canopy parameterization acts to reduce the wind speed in the urban areas, and the maximum reduction in wind speed is focused near the tops of the buildings, H. 4. Future Work The urban canopy parameterization will soon be upgraded to include the influences of the buildings and street canyons on the energy budget. In addition, detailed comparisons against observational data will be performed to assess the viability of the urban canopy parameterization for air quality modeling applications. Ultimately, the urban canopy parameterization will be expanded to use more detailed land use databases than currently available in MM5 (e.g., the EPA's National Land-Cover Date, Vogelman and Wickham 2000) so that the urban areas can be properly sub-categorized. In addition, the scheme will be modified to use better-resolved urban morphology to identify urban terrain zones. 300 250 200 »1S0 100 50 \\ \ \\ Ok -0.5 0.5 1 M2N2 1.5 2.5 300 2S0 200 in 150 100 50 0 A 4 n I ft f o ra/i Figure 4. Differences in TKE (top panel) and wind speed (bottom panel) between runs with and ------- without the urban canopy parameterization at a point in the center of the urban area in the 1.33-km domain. These vertical profiles are for the lowest 300 m AGL in each simulation. The curves are valid at 17 (a), 18 (y), and 19 (v) UTC 14 July 1995. Values greater than zero represent a net increase in the field using the urban canopy parameterization. 300 250 200 100 m/s Figure 5. Wind speed profiles from the two model simulations shown in Figure 4. The profiles from the simulation with the urban canopy parameterization are shown in dashed lines; the standard parameterization is shown in solid lines. The profiles represent 18 (v) and 19(c) UTC 14 July 1995. Acknowledgments. We thank Drs. M. Brown (LANL) and D. W. Byun (NOAA/ARL) for their valuable suggestions. We also thank Dr. J. Pleim (NOAA/ARL) for his thorough review. Disclaimer. The information in this manuscript has been funded by the United States Environmental Protection Agency. It has been subjected to Agency review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. 5. References Brown, M. J., 2000: Urban parameterizations for mesoscale meteorological models. Mesoscale Atmospheric Dispersion. Ed., Z. Boybeyi. Byun, D. W., and S. P. S. Arya, 1986: A study of mixed layer momentum evolution. Atmos. Environ., 20, 715-728. Byun, D. W., and J. K. S. Ching, 1999: Science algorithms of the EPA Models3 Community Multiscale Air Quality (CMAQ) Modeling System. EPA/600/R-99/Q30. Chin, H. S., M. L. Leach, and M. J. Brown, 2000: A sensitivity study of the urban effect on a regional scale model: an idealized case. Third Symp. on the Urban Environment, August 2000, Davis, CA. Grell, G., J. Dudhia, and D. R. Stauffer, 1994: A description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5). NCAR/TN398+STR, 138 pp. Kastner-Klein, P., and M. W. Rotach, 2001: Parameterization of wind and turbulent shear stress profiles in the urban roughness layer. . Preprints, Third Int. Conf. on Urban Air Quality, March 2001, Loutraki, Greece. Ratti, C., S. Di Sabatino, R. E. Britter, M. J. Brown, F. Caton and S. Burian, 2001: Analysis of 3-D urban databases with respect to pollution dispersion for a number of European and American cities. Preprints, Third Int. Conf. on Urban Air Quality, March 2001, Loutraki, Greece. Seaman, N. L., and S. A. Michelson, 2000: Mesoscale meteorological structure of a high- ozone episode during the 1995 NARSTO- Northeast study. J. Appl. Meteor., 39, 384- 398. Shafran, P. C„ N. L. Seaman, and G. A. Gayno, 2000: Evaluation of numerical predictions of boundary layer structure during the Lake Michigan Ozone Study. J. Appl. Meteor., 39, 412-426. Uno, I., H. Ueda, and S. Wakamatsu, 1989: Numerical modeling of the nocturnal urban boundary layer. Bound-Layer Meteor,, 49, 77-98. Vogelman, J. E., and J. D. Wickham, 2000: Implementation strategy for production of National Land-Cover Data from the Landsat-7 thematic mapper satellite. EPA/600/R-00/051. ------- TECHNICAL REPORT DATA 5. report no. 2 . 3 4, TITLE AND SUBTITLE '' Implementation of an urban canopy parameterization in MM5 for meso-gamma-scale air quality modeling applications 5.REPORT DATE 6.PERFORMING ORGANIZATION CODE 7. AUTHOR(S) Tanya L. Ottc-' and Avraham Lacscr* 8.PERFORMING ORGANIZATION REPORT NO. I 9. PERFORMING ORGANIZATION NAME AND ADDRESS 'Same as Block 12 2Xsrael Institute for Biological Research, Nsss £io ns, ¦ Israel 10.PROGRAM ELEMENT NO. 11. CONTRACT/GRANT NO. 12. SPONSORING AGENCY NAME AND ADDRESS U.S. Environmental Protection Agency . Office of Research and Development National Exposure Research Laboratory Research Triangle Park, NC 27711 13.TYPE OF REPORT AND PERIOD COVERED Proceedings, FY-01 14. SPONSORING AGENCY CODE EPA/600/9 -15. SUPPLEMENTARY NOTES 16. ABSTRACT The United Slates Environmental Protection Agency (U.S. EPA) is extending its Models-3/Community Multiscaie Air Quality (CMAQ) Modeling System to provide detailed gridded air quality concentration fields and sub-grid variability characterization at neighborhood scales and in urban areas. CMAQ is an advanced air quality modeling system that embodies a "one-atmosphere," multiple-pollutant philosophy. The meteorological model used with CMAQ in this application is the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5). For fine-scale urban simulations (~S-km grid spacing), MM5 is being modified to include an urban canopy parameterization that accounts for the drag exerted by the urban structures on the flow, the enhancement of turbulent kinetic energy especially near the top of the buildings, and the energy budget at the street and roof levels. This refinement is targeted to provide CMAQ with the means to capture the details of pollutant spatial distributions at these scaies.One of the goals of this research is to demonstrate the capability ofMMS to simulate Ihe effects of urban areas at the meso-gamma scale. Preliminary experiments with the "off-the-shelf' MM5 were performed with various physics options in the coarseT domains (e.g., 36, 12, and 4 km) to provide a baseline for comparing with the 1.33-km simulations. This paper will show sensitivities of the predicted meteorological variables to grid sizes and illustrate the utility of the urban canopy parameterization through comparisons with measuremer.ts.Ultirr.ately, the urban canopy parameterization will be expanded to use more detailed land use databases than currently available in MM5, and it will include better-resolved urban morphology to identify urban terrain zones. 17. KEY WORDS AND DOCUMENT ANALYSIS a. DESCRIPTORS b.IDENTIFIERS/ OPEN ENDED TERMS c.COSATI 18. DISTRIBUTION STATEMENT RELEASE TO PUBLIC X 19. SECURITY CLASS (This Report) UNCLASSIFIED 21.NO. OE PAGES 20, SECURITY CLASS (This Fa ge) UNCLASSIFIED 22. PRICE ------- |