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Applications of the Integrated WRF/Urban Modelling System to Regional Air Quality

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

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Applications of the Integrated WRF/Urban Modelling System to Regional Air Quality

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  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 andGlobal Climate Change and Extreme Weather

  4. 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

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

  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 Natural surface • 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). Coupled through ‘urban fraction’ Urban canopy models: Man-made surface Chen et al., 2009, Intl. J. Climatology

  9. Indoor-outdoor exchange model Vertical levels in the UCP BEM IU+1 IU IU-1 • 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. !! 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.

  11. Beijing, Taipei, and Tokyo: surface weather, precipitation Salt Lake City: Diurnal wind direction (URBAN-2000) Oklahoma City: 2-m temperature (JU-2003) Applications of Coupled WRF-Urban Models 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 2004-2007 WRF-Slab land model WRF-Noah-SLUCM Observations 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. Houston in 2000 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 urban growth and climate change Increase of surface ozone by climate change along 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 featuresresolved explicitly with immersed boundary (IB) approach Downscale data transfer Urban T&D modeling system: EULAG LES/CFDmodel Mesoscale modeling system: WRF-Noah/UCM forecast 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 IOP6 0900 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.

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