11.4
IMPLEMENTATION OF AN URBAN CANOPY PARAMETERIZATION IN MM5
Avraham Lacser1 and Tanya L. Otte2+*
11srael Institute for Biological Research, Ness Ziona, Israel
2Atmospheric Sciences Modeling Division, NOAA ARL, Research Triangle Park, North Carolina
+On assignment to the National Exposure Research Laboratory, U.S. EPA
1.	INTRODUCTION
The Pennsylvania State University/National Center
for Atmospheric Research Mesoscale Model (MM5)
(Grell et al. 1994) has been modified to include an urban
canopy parameterization (UCP) for fine-scale urban
simulations (~1-km horizontal grid spacing). The UCP
accounts for drag exerted by urban structures, the
enhancement of turbulent kinetic energy (TKE)
especially near the tops of the buildings, and the
modification of the energy budget within the urban
canopy (i.e., from the surface to the tops of buildings).
This UCP is applied to grid cells in MM5 that have a
non-zero fraction of urban land use. This refinement of
MM5 is targeted to enable the Community Multiscale Air
Quality (CMAQ) Modeling System (Byun and Ching
1999) to capture the details of pollutant spatial
distributions in urban areas.
2.	URBAN CANOPY PARAMETERIZATION
2.1 Momentum
The horizontal components of the momentum
equations are modified to account for the area average
effect of the sub-grid urban elements following Brown
(2000). The modifications are implemented in MM5 via
the TKE-based Gayno-Seaman planetary boundary
layer (PBL) parameterization scheme (e.g., Shafran
et al. 2000). The momentum equations accounting for
the urban elements are:
^=Fu- 0.5furbCd /Kz)u(j2+V2Y
^f=Fv- 0.5furbCd Az)V(U2+V2y
STKE	/ 2 2 2^5
~~Qf~ = FtKE + 0.5furtPdA{z){^J +V +W )
where Fare 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 furb. 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 rrf1.
There are several approaches to describe A(z) (e.g.,
Uno et al. 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 tops of the tallest buildings (H) is Xf, which
corresponds to the ratio of the frontal area to the total
surface area of the buildings. In general A(z) is a
function of the location within the domain as it depends
on building morphology. A(z) can be estimated from
Xf and H assuming some functional form for P(z) \ here
we use a linear function.
To solve the modified momentum equations (the
added new term), we follow the analytical solution
suggested by Byun and Arya (1986). The TKE equation
is solved explicitly. To take proper account of the
influence of P(z), the vertical resolution in MM5 is
increased in the domain 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 et al. 2000). The anthropogenic heat
flux is set as a function of urban land use subcategory,
and it has a temporal weighting function (e.g., Taha
1999). The heat equation also includes the heat
contribution of the city canyons following Yamada
(1982); the contribution due to rooftops has not yet been
implemented. The surface energy balance includes the
shadowing/trapping effect of the net radiation reaching
the ground in the city canyons modified by extinction of
the radiation through the urban canopy using a simple
exponential function (e.g., Brown 2000).
2.3	Urban Morphology
Parameters that are required for the UCP (e.g., H
and Xf) can be extracted from digital imagery (e.g.,
Ratti et al. 2001) which is commercially available from
several vendors for various cities and with different
degrees of accuracy and precision. We did not have
access to a true urban morphology database for our
area of interest, so we modified the MM5 land use
database for our domain to have seven subcategories of
urban areas adapted from Ellefsen (personal
communication 2001). These categories crudely
represent urban zones such as high-rise, industrial, and
urban residential. Each of the urban subcategories has
a different value for H, Xf, canyon fraction, and
maximum anthropogenic heat flux.
3. PRELIMINARY RUNS
The unmodified MM5 was run in a one-way nested
mode for several days in July 1995 during which there
*Corresponding author address: Tanya Otte, U.S. EPA,
MD E243-03, RTP, NC 27711; otte.tanya@epa.gov

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was a high-ozone episode in the Northeastern U.S. that
coincided with a photochemical field study. The MM5
domains included a five-domain configuration (108, 36,
12, 4, and 1.33 km grid spacing). The first four domains
were run with 30 vertical layers (about 12 layers in the
PBL, and lowest level at 19 m) and physics options
appropriate for each resolution.
To include the influence of smaller obstacles, the
UCP was used on the 1.33-km domain with 40 layers
that included 10 new layers in the lowest 100 m (lowest
level at 2 m). Several simulations have been made with
the 1.33-km domain to determine the impact of the UCP
and the morphology on the simulation. As expected, the
UCP acted to increase the TKE at the top of the urban
canopy (near rooftops) and decrease wind speed within
the urban canopy. The TKE profile exhibited a peak at
the top of the canopy that is consistent with wind tunnel
measurements for a simulated urban area (e.g.,
Kastner-Klein and Rotach 2001). At urban points, the
UCP increased the surface temperature by ~2°C
overnight and ~0.5°C in late afternoon in the city center
compared to the runs without the UCP. In addition, the
UCP created an unstable temperature profile overnight
at urban points (not shown). At non-urban points, the
TKE, wind speed, and temperature profiles remained
largely unchanged.
Figure 1 shows a comparison of the surface (~2-m)
temperature for Philadelphia International Airport (PHL)
from runs with and without the UCP compared to
observations for 14 July 1995. This figure shows that
the experiment with the UCP had significantly better
temperatures overnight and somewhat better
temperatures during the day. Overall, the diurnal
temperature pattern of the simulation with the UCP
compares more favorably with observations.
4.	FUTURE DIRECTIONS
Additional comparisons against observational data
will be performed to assess the viability of the UCP for
air quality modeling applications. The parameterization
will be expanded to add the roof energy budget and to
use more detailed land use databases and morphology
databases so that the urban areas can be more
accurately characterized. Finally, the urban canopy
parameterization will be coupled with a land-surface
model and urban soil model.
Disclaimer. The information in this manuscript has been
prepared under funding 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. Mesoscaie
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 Models-3 Community
Multiscale Air Quality (CMAQ) Modeling System.
EPA-600/R-99/030, U.S. EPA.
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. Preprints, Third
Sym. on the Urban Environment, Davis, CA, Amer.
Meteor. Soc.
Grell, G., J. Dudhia, and D. R. Stauffer, 1994: A
description of the fifth-generation Penn State/NCAR
Mesoscale Model (MM5). NCAR Tech. Note,
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. Proceedings,
Third Int. Conf. on Urban Air Quality, 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.
Proceedings, Third Int. Conf. on Urban Air Quality,
Loutraki, Greece.
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.
Taha, H., 1999: Modifying a mesoscale meteorological
model to better incorporate urban heat storage: A
bulk parameterization approach. J. Appl. Meteor.,
38, 466-473.
Uno, I., H. Ueda, and S. Wakamatsu, 1989: Numerical
modeling of the nocturnal urban boundary layer.
Bound-Layer Meteor., 49, 77-98.
Yamada, T., 1982: A numerical model study of turbulent
airflow in and above a forest canopy. J. Met. Soc.
Japan, 60 (1), 439-454.
PHL Temperature — 14 July 1995
No UCP
UCP
o Obs
Time UTC
Figure 1. Temperature at PHL for 14 July 1995 for
observations and simulations with and without UCP.

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4. TITLE AND SUBTITLE: Implementation of an Urban Canopy
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6. AUTHOR(S)
A. Lacser and T.L. Otte*
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Israel Institute for Biological Research
Ness Ziona, Israel
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ORD, U.S. EPA, Research Triangle Park, N.C. 27711
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13. ABSTRACT (Maximum 200 words)
The Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) has been
modified to include an urban canopy parameterization (UCP) for fine-scale urban simulations (~1 -km horizontal grid spacing).
The UCP accounts for drag exerted by urban structures, the enhancement of turbulent kinetic energy (TKE) especially near
the tops of the buildings, and the modification of the energy budget within the urban canopy (i.e., from the surface to the tops
of buildings). This UCP is applied to grid cells in MM5 that have a non-zero fraction of urban land use. This refinement of
MM5 is targeted to enable the Community Multiscale Air Quality (CMAQ) Modeling System to capture the details of pollutant
spatial distributions in urban areas.
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