Effects of Using High-Resolution Urban Data Sets on WRF/Urban Coupled Model Simulations for the Houston-Galveston Areas Fei Chen, Shiguang Miao*, Mukul Tewari National Center for Atmospheric Research, Boulder, CO *Institute of Urban Meteorology, Beijing, China Jason Ching U.S. NOAA/EPA, Research Triangle Park, NC

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Next-Generation Mesoscale Modeling: The Weather Research and Forecasting Model Goals: To develop an advanced mesoscale forecast and assimilation system and to accelerate research advances into operations WRF R&D aims Advanced data assimilation and model physics Portable and efficient on parallel computers Well-suited for a broad range of applications Community model with direct path to operations WRF coupled to online chemistry and aerosols models: WRF-Chem Priority for 1-10 km grid applications WRF development is governed by 15 WRF Working Groups 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

Coupled through ‘urban fraction’ Man-made surface The Noah/UCM in WRF Noah LSM primarily for NWP, air pollution, and regional hydrology applications Noah in operational models NCEP WRF-NMM (June 2006) AFWA: WRF-ARW (July 2006) Single layer urban-canopy model (UCM, based on Kusaka 2001) 2-D urban buikding geometry Street canyons Shadowing from buildings and reflection of radiation Multi-layer roof, wall and road models Noah/UCM was in WRF and WRF-Chem V2.2 (Dec. 2006) (http://www.rap.ucar.edu/research/land/technology/urban.php) Natural surface Coupled through ‘urban fraction’ Man-made surface

Application of Coupled MM5/WRF Urban Models Salt Lake City: Diurnal wind direction (URBAN-2000) Oklahoma City: 2-m temperature (JU-2003) Beijing 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. Zhang, Chen, and Miao 2006: J Geophys. Res., in revision. Miao and Chen, 2007: Atm. Research, submitted 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

From Real World to urban modeling Urban model parameter space 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Motivation Urban fraction building height, ZR roughness for momentum above the urban canopy layer, Z0C roughness for heat above the urban canopy layer Z0HC zero-displacement height above the urban canopy layer, ZDC percentage of urban canopy, PUC sky view factor, SVF building coverage ratio (roof area ratio), R normalized building height, HGT drag coefficient by buildings, CDS buildings volumetric parameter, AS anthropogenic heat, AH heat capacity of the roof, wall, and road heat conductivity of the roof, wall, and road albedo of the roof, wall, and road emissivity of the roof, wall, and road roughness length for momentum of the roof, wall, and road roughness length for heat of the roof, wall, and road Major challenge: how to specify potentially vast number of parameters required to run urban models. NUDAPT high-resolution data provide an opportunity to Understand the impacts of uncertainty in characterizing urban on WRF/UCM and CMAQ simulations Develop a better approach for modeling and data integration. 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

WRF Model Configuration for Houston case 4 domains: 27, 9, 3, and 1 km Start at 0000UTC30AUG 2000, 36-hour simulation for a high pollution episode over the Houston area. Initial & Bdy conditions from EDAS data. WRFV2.2 physics: Dudhia shortwave, RRTM longwave, MYJ PBL, Noah LSM with one-layer UCM Numerical experiments: Ctrl: using table values SST: using NUDAPT hourly SST data BUILD: using NUDAPT 3D urban building morphological data ANTH: using NUDAPT hourly anthropogenic heating data. 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

Comparison between NUDAPT data and WRF table values Building Height (m) Daily mean anthropogenic heating rate (W/m2) WRF NUDAPT Except for downtown areas, NUDAPT has lower building height and AH rate

Surface observation stations and wind profiler site 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

Daytime variations of surface wind Observations WRF/UCM simulation Development of southerly (southeasterly) sea (bay) breezes counteract the initial northerly (northwesterly) flow, leading to stagnant wind in late afternoon 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

Nighttime variations of surface wind Observations WRF/UCM simulation Nighttime wind reversal - development of land breeze 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Validation of the WRF/UCM control simulation Comparison with wind profiler data at Houston Southwest Observations WRF/UCM simulation The timing and depth of wind reversal are well captured by WRF/UCM 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Effects of using 2-D building morphological data simulation BUILD -simulation CTRL: 2-m temperature Daytime average Nighttime average Mostly decrease 2-m T up to 1.5 K over urban areas 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Effects of using 2-D building morphological data simulation BUILD -simulation CTRL: 10-m wind speed Daytime average Nighttime average Mostly increase wind speed ~ 1 ms-1, nighttime changes are more confined in the urban areas. 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Effects of using 2-D building morphological data simulation BUILD -simulation CTRL: PBL depth Nighttime average Daytime average Mostly reduce PBLH in main urban areas, nighttime changes are more confined in the urban areas. 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Effects of using 2-D anthropogenic heating data simulation ANTH -simulation CTRL: 2-m temperature Daytime average Nighttime average Mostly reduce 2-m T in urban areas. 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Effects of using 2-D anthropogenic heating data simulation ANTH -simulation CTRL: 10-m wind speed Daytime average Nighttime average Effect on wind speed is smaller. 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Effects of using 2-D anthropogenic heating data simulation ANTH -simulation CTRL: PBL depth Daytime average Nighttime average Mostly reduce PBLH in main urban areas, nighttime impact minimal. 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC

Hit rate calculated from five sensitivity cases (two more cases by varying the lowest model level in red) Case No. Case name Number of Stations Hit rate T2 TC WS UC WSP10 1 CNTL 28 19 26 17 0.75 0.78 0.64 0.27 2 CNTL+SST 0.72 0.77 0.63 0.26 3 ANTH 0.69 0.76 4 BUILD 0.71 0.32 5 ANTH+BUILD+SST 6 CNTL+0.995 0.81 0.65 7 CNTL+SST.995 0.74 0.8 0.66 The first WRF sigma level in case1~case5 is 0.992. The first WRF sigma level in case6 and case7 is 0.995. Hit rate criterion for T < 2K, Wind speed (WP) < 1ms-1 BEST

6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC Summary Utilizing 2-D urban building data can affect WRF/UCM simulated surface weather variables and PBL depth. T ~ 1K U/V ~ 1-2 ms-1 PBL depth: ~ a few hundred meters 2-D anthropogenic heating data appear to have larger impact than 2-D building morphological data Limitations of the current study: Data-aggregation approach Single-layer UCM (whose parameters may have been well calibrated for Houston) Consistency among various NUDAPT data sets 6th Annual CMAS Conference, October 1-3, 2007, Chapel Hill, NC