1. Applications of the Integrated WRF/Urban Modelling System to Regional Air Quality
Fei Chen, Mukul Tewari, Kevin Manning: National Center For Atmospheric Research (NCAR), Boulder, CO
Hiroyuki Kusaka: University of Tsukuba, Japan
Shiguan Miao: Institute of Urban Meteorology, Beijing, China
Alberto Martilli: Centro de Investigaciones Energeticas, Madrid, Spain
Jason Ching: USEPA, Research Triangle Park, NC,
Susanne Grossman Clarke: Arizona State University, Tempe, AZ
XueMei Wang: Sun Yat-Sen University, Guangzhou, China
2009 CMAS Conference, 20 October 2009, Chapel Hill, NC.

2. Aspects to the urban environmental problems
Climate change and human health
Sea-level rise
Indoor and outdoor air quality
Human thermal stress
Water resources and management
Designing livable cities
Atmospheric transport of accidental or intentional releases of toxic material
Severe weather, flood

3. The factors that influence urban environmental risk
Population Increase/
City Growth
Regional and Global
Climate Change
and
Extreme Weather 3

4. Urban Physical Effects on Local Climate and Weather
The factors that influence urban environmental risk
Population Change
City Growth
Urban Physical Effects
on Local Climate and Weather
Regional and Global
Climate Change
and
Extreme Weather 4

5. The physical modeling system – A spectrum of coupled scales
Current technology for operational weather and climate prediction
Global Scales
Continental Scales
Regional Scales
Local Scales
Long Island
Urban Scales

6. Urban Modeling for Weather Research and Forecast (WRF) Model
WRF is widely used in both operational and research community.
We can now bridge the gap between traditional mesoscale (~ 10 km) and fine-scale urban transport and dispersion modeling (~ 10 m)
WRF, new generation NWP model, running with 1-4 km grid spacing
Availability of new data at urban scales, urban canopy models
Land data assimilation techniques
Techniques to couple mesoscale and CFD (LES) models.
Hence, the WRF model is able to deal with regional climate, fine-scale weather forecast, and urban scales air quality and transport and diffusion (T&D).

7. Integrated WRF Urban Modeling Framework
Meet both numerical weather prediction (NWP) and
air quality (including T&D) modeling requirements

8. The Noah Land Model
Noah LSM primarily for NWP, air pollution, and regional hydrology applications.
Noah has been implemented in NCEP, AFWA, and oversea-agency operational models.
Two urban canopy models (UCM)
Single layer urban-canopy model (SLUCM, based on Kusaka 2001). Released in WRF V2.2 (Dec. 2006).
Multi-layer UCM (Building Effect Parameterization, BEP) by Martilli et al. (2002). Released in WRF V3.1 (April 2009).
Natural surface
Coupled through ‘urban fraction’
Urban canopy models: Man-made surface
The core of this modeling system is the coupling of the natural surface through the community Noah land surface model with an urban canon model.
The coupled Noah with single-layer UCM developed by Dr. Kusaka has been in the community release of WRF since 2006.
Chen et al., 2009, Intl. J. Climatology

9. Indoor-outdoor exchange model
The Building Energy Model (BEM) is inlcued in the Multi-layer BEP
For each floor, BEM solves prognostic equations for indoor air temperature and air moisture by considering:
generation of heat due to the occupants and equipments.
radiation entering from the windows
interchange of heat and moisture with the exterior through ventilation
heat diffusion through the walls.
IU+1 IU
IU-1
Vertical levels in the UCP
BEM
!! We do not attempt to simulate a specific building, rather an average behaviour over the grid cell!! Salamanca and Martilli (2009, Theoreti. Appli. Climatol.)

10. Requires detailed mappings of buildings
National Urban Database and Access Portal Tool (NUDAPT), led by Jason Ching (USEPA)
Example of NUDAPT gridded urban canon parameters for Houston, Texas.
Plan area density (PAD), frontal area density of the buildings (FAD).
Ching et al., 2009, Bull. American Meteorol. Soc. 10

11. Applications of Coupled WRF-Urban Models
Salt Lake City: Diurnal wind direction (URBAN-2000)
Oklahoma City: 2-m temperature (JU-2003)
Beijing, Taipei, and Tokyo: surface weather, precipitation
Houston: Diurnal cycle of wind profile (TexAQS-2000)
Hong Kong: 10-day surface wind
Liu, Chen, Warner, and Basara: 2006, J Appli. Meteorol.
Lo, Lau, Chen, and Fung, 2007: J. Appli. Meteorol.
Lo, Lau, Fung, and Chen, 2007: J Geophys. Res.
Miao and Chen, 2008: Atm. Res.
Lin et al., 2008: Atm. Environ.
Jiang et al. 2008: J Geophys. Res.
Miao et al., 2009: J. Appli. Meteorol. Climatol.
Zhang et al., 2009: J Geophys. Res.
Tewari et al., 2009: Atm. Res. .

12. WRF/urban 4-km regional climate simulation are able to capture urban heat islands
Monthly mean surface air temperatureat 2 m in the Tokyo area at 0500 JST in August averaged for
Observations
WRF-Slab land model
WRF-Noah-SLUCM
Kusaka et al., 2009, ICUC-7

13. Rapid Urban Growth in China
YRD: Yangtze River Delta region
PRD: Pearl River Delta region

14. Such urban growth resulted in ozone increase
WRF 12-km monthly (March 2001) averaged difference (urban - preurban)
of the surface ozone (in ppbv) and relative 10-m wind vectors
Daytime
Nighttime
Wang et al., 2009, Adv. Atmosp. Physics

15. 2000
Houston in 2000
How does future climate change and urban growth modify air pollution in Houston?
Urban expansion Impacts
meteorology:
Temperature
Boundary layer depth
Emissions
Biogenic emissions
Anthropogenic emissions
2030
Projected Houston growth in 2030
industrial or commercial
high intensity residential
low intensity residential

16. Results: Land-use change (urbanization) has similar effect on future 8-hour Ozone concentrations to climate change, based on 4-km WRF-Chem simulations.
Increase of surface ozone by climate change along
Increase of surface ozone by urban growth and climate change
Increase of surface ozone by urban growth
Jiang et al., 2008, JGR.

17. WRF downscale and upscale coupling strategies
WRF provides initial and lateral boundary conditions for EULAG in two modes
Isolated sounding data mode – short term, quasi steady conditions, small scale urban domain
Unsteady (temporal-based coupling) mode – linear interpolation of the WRF data in time and space
Building geometry flow features resolved explicitly with immersed boundary (IB) approach
Downscale data transfer
Mesoscale modeling system:
WRF-Noah/UCM forecast model
Urban T&D modeling system:
EULAG LES/CFD model
Coupler:
MCEL Library
Upscale data transfer:
Turbulence and wind fields explicitly resolved by EULAG are feedback to WRF-urban
EULAG fields are volumetrically averaged to (coarser) WRF mesh
WRF urban framework introduce source terms in the momentum and turbulence equations
The coupling impact urban and downstream weather forecast

18. Coupled WRF/urban-LES/CFD model results
CFD-urban use single sounding
CFD-urban use WRF 12-hforecast
Density of SF6 tracer gas (in parts per thousand) 60 minutes after the third release, CFD-urban simulations are contoured. The dots represent the observed density at sites throughout the downtown area of Salt Lake City, Utah. Tewari et al. (2009).
Dispersion footprint for IOP CDT release for Oklahoma City downtown area, Oklahoma) calculated with WRF/EULAG.

19. Summary
An international, collaborative effort has developed an integrated, cross-scale WRF/urban modeling capability, and evaluated it against surface and PBL observations obtained from major cities.
WRF/urban (WRF-Chem/uban) is a useful tool for addressing various indoor and outdoor air quality problems in cities.
Muck work remains to be done: identify model and parameter uncertainties, to incorporate urban canopy parameters (detailed building data, remote-sensing, and extrapolation approach.
The AMS 9th Symposium on the Urban Environment will be held in August 2010, Co-chaired by Fei Chen and Julie Lundquist.