Urban boundary layer modeling and infrastructure issues. Jason Ching

Transcription

1 Joint Region 10 + States Meeting NW AIRQUEST Annual and MM5 Consortium meeting Seattle, Washington October 23-25, 2007 Urban boundary layer modeling and infrastructure issues Jason Ching ARL/NOAA NERL/USEPA Research Triangle Park, NC ching.jason@epa.gov

2 Presentation Overview I. Setting the stage Urban boundary layer developments Fit for purpose concepts II. Rationale for a database focus Content, concepts and implementation of Prototype Types of gridded datasets III Summary

3 Setting the stage: Modeling the UBL Multi-scale framework Model framework Sub-grid scale issues Fit for purpose considerations

4 Majority of pollutants are emitted inside the roughness sub-layer: Necessity to have a good precision on meteorological fields. Meso scale Neighborhood scale 1 km. Local scale Roughness Sub- Layer Rural Rural Urban

5 The ground conditions used by mesoscale model are not satisfactory at neighborhood scale: Drag-force approach, Microscale modeling parameterizations Meso scale Neighborhood scale 1 km. Local scale Roughness Sub- Layer Rural Rural Urban

6 Scales: Regional to Mesoscale: > 4 km RA Approach MM5, WRF, COAMPS,. Urban (Neighborhood scale < 4 km Canopy Approach Building Drag LU Mosaic Within Street canyon, Building or microscale <1km CFD

7 CHALLENGE for meso-to to-urban scale modeling drag anthropogenic heating radiation attenuation radiation trapping Urban Canopy Effects turbulence production canopy heating & cooling urban thermal properties Modeler s s need: To capture the grid average effect of detailed urban features in mesoscale atmospheric models Solution: Modelers have defined and implemented urban canopy parameterizations into their models (e.g., MM5, WRF, HOTMAC, RAMS, COAMPS )

8 ISSUE: Relating meso-urban to building scale Buildings distributed in 1 km grid. Mesoscale: Model produces single meteorology profile applicable to grid cell Results influenced by the presence and aggregated effects of buildings. Building scale: Intra-cell flow fields will be highly variable (horizontally and vertically), influenced by the individual buildings.

9 An implementation: DA-SM2-U in MM5 o Urbanization introduced at grid sizes of ~1km using drag approach (DA) o Land surface model (SM2-U) o Additional, within canopy layers Roughness approach Net radiation Drag-Force approach Sensible heat flux Latent heat flux Storage heat flux Anthropogenic heat flux R n pav H sens pav LE pav T s roof Precipitation roof Q wall natural soil T s pav G s pav T int bare soil Paved surface Surface layer Drainage outside the system water Drainage network Drainage Infiltration Root zone layer Deep soil layer Diffusion

10 Momentum equation = forcing terms (modification of vertical turbulent transport term) + momentum sources due to building horizontal surfaces (friction force) + momentum sources due to the pressure and viscous drag forces induced by the vegetation and the building vertical surfaces 2 ( k) < u ( k) > < u ( k) > + < u ( k) Cdj Afj i x y > j 2

11 TKE equation= forcing terms (modification of vertical turbulent transport) + shear production by building horizontal surfaces + buoyant production from the surface sensible heat fluxes + wake production due to the presence of vegetation and buildings ( ) ( 2 2 k < u > + < u ) Cdj Afj x y > j + dissipation due to the accelerated cascade of TKE from large to small scales due to the canopy elements ( ) ( 2 2 k < u > + < u ) 4C Afj x y > j dj E(k )

12 Heat equation = forcing terms (modification of vertical turbulent transport term) + sensible heat sources from surfaces + anthropogenic heat sources Humidity equation= forcing terms (modification of vertical turbulent transport term) + humidity sources from surfaces + anthropogenic humidity sources

13 Impact of land use, terrain Potentially large sub grid variations Land use schemes: USGS Use dominant LU schemes Adopt some weighting scheme Limited spatial resolution Mosaic Approach (Pleim) DA-SM2U NLCD (from Landsat) 30 m resolution 3 urban classes WRF-Urban

14 Fit for Purpose RA approach limited for urban and finer scales Urban scale canopy approach: Drag and land surface schemes. Introduces urban and land use features appropriately Building and urban features are virtual cannot resolve within canyon flows. (Makes model validation a big challenge) Drawback: requires large computer resource and specialized database Urbanized mesoscale (in WRF, not yet in MM5) Town Energy Budget approach (French, Canadian models) Use of CFD models: Ideal situation: drive CFD with Canopy model. (heavy computational requirements) Simplified approaches: QUIK modeling (Library of Phys modeling and CFD results) Approach: Balance model and computational requirements. Difference between operational and R&D

15 Part II: Model inputs for UBL High resolution definition of urban building and features (1m-5 m) Parameterization for models (UCPs) (250m-1km) Land Use (30 m-1km) Application specific databases NUDAPT facilitation

16 Background for NUDAPT Rqpid advancements in urban boundary layer formulations and measurements To support advancements in urban modeling a community framework urban modeler s database is proposed. Poll and Workshops: Overwhelming support from AMS, OFCM for this idea and the concepts underlying such a database. In 2005, EPA provided limited resources to develop and demonstrate a Prototype system. (We call it NUDAPT) Implementation of this (two year) Project was made possible with strong support and significant contributions from core group of Collaborators (20 to date) Prototype implemented as community-based system of data, processing and web-based tools. Nunn Lugar Bill: 133 City Study (NGA)

17 Prototypic Implementation The NUDAPT Framework Urban modeling is its major focus Adopts a community system paradigm- Encourages collaborations, accelerates model advancements with Portal technology Supports various meteorological modeling systems, others are possible Broad user base (Model developers to users) Extensible (to smaller scales, to current and future city structures, to revised sets of UCPs) Database consists of primary and derived parameters High resolution geospatial data: repository or links (133 cities in USA) Appropriate and complete set of parameterizations at urban grid scale Ancillary data (to facilitate applications) Allowance for evaluation, operational utility Features include basic processing methodologies and tools Selected cities serves as example prototypes to highlight capabilities and features e.g., Houston, Atlanta, Phoenix

18 High resolution urban morphological data can be derived from lidar mapping and photogrammetric techniques We have the technology and means for obtaining building data at high resolution; such data and ancillary data are becoming increasingly more available for our major cities

19 LIDAR Profiling * Record Longest Return * Normally Rotary Wing * Continuous Ground Coverage High resolution Data for 133 cities

20 Implementation of canopy concepts and urban morphology parameters for improved modeling The knowledge of the vertical and horizontal distribution of the different urban land cover modes is necessary. TAD PAD FAD VFAD VPAD Roof area density z Building plan area density z Building frontal area z density Vegetation area z density Vegetation plan area density z

21 Gridded (1 km) Urban Canopy Parameters (UCP) from high resolution data for urbanized MM5 CANOPY UCPs BUILDING UCPs VEGETATION, OTHER UCPs Mean vegetation height Mean canopy height Mean Height Vegetation plan area density Canopy plan area density Std Dev of heights Vegetation top area density Canopy top area density Height histogram Vegetation frontal area density Canopy frontal area density Wall-to Plan area ratio Roughness Length* Height to width ratio Mean Orientation of Streets Displacement height* Plan area density Plan area fraction surface covers Sky View Factor Rooftop area density % connected impervious areas Frontal area density Building material fraction Parameters used in RA formulations Height dependent UCP

22 Selected Urban Canopy Parameters per 1 km 2 cells for Harris County, TX; NOTE! Unique combination of UCPs/cell PAD Wall/Plan Area FAD Height/Width

23 WRF/Noah LSM/Urban-Canopy Coupled Model Single layer urban-canopy model (UCM, based on Kusaka 2001) 2-D urban geometry (orientation, diurnal cycle of solar azimuth) Street canyons with sky view factor Shadowing from buildings and reflection of radiation Anthropogenic heating Multi-layer roof, wall and road models

24 UCPs in NUDAPT MM5 Mean and standard deviation of building and vegetation height Plan-area area weighted mean building and vegetation height Building height histograms Plan area fraction and frontal area index at ground level Plan area density, top area density, and frontal area density Complete aspect ratio Building area ratio Building height-to to-width ratio Sky view factor at ground level and as a function of height Aerodynamic roughness length and displacement height (Raupach( Raupach, Macdonald, Bottema) ) coefficients Mean orientation of streets Surface fraction of vegetation, roads, rooftops, water and impervious area, directly connected impervious area, albedo and building material using remote sensing WRF Urban fraction Building height, ZR Roughness for momentum above the urban canopy layer, ZoC Roughness for heat above the urban canopy layer ZoHC 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

25 More robust model applications. It can make a significant difference! Urbanized MM5 UBL prediction differ significantly from standard version Model sensitivity studies show significant response to improved urban modeling e.g., air quality Advanced models provide bases for urban design, investigations of urban heat island mitigation Resource capable of supporting a variety of modeling systems

26 Sensitivity study: Comparison of results using DA-SM2U (UCP version) Standard MM5 (RA) MM5 Sensible Heat Flux (w/ucp) MM5 PBL w/ucp MM5 Sensible Heat Flux (RA) MM5 PBL (RA)

27 Air Quality Model (CMAQ) at fine scales Pollutant model simulations are sensitive to (or dependent on) grid resolution Neighborhood scale modeling paradigm: Sub-grid variability (SGV) is universally inherent to all grid models Represent SGVs stochastically or modeled deterministically. Link to a dispersion model (e.g., AERMOD..)

28 Ozone (1 km grid CMAQ 2100 GMT UCP noucp Difference (UCP-noUCP) Significant differences in the spatial patterns shown between UCP and noucp runs (titration effect occurs in both sets) Flow, thermodynamics & turbulent fields differ between the UCP and noucp simulations & contribute to differences

29 NUDAPT Portal: Two systems, Quickplace One Whole Powerful, flexible collaboration suite Built-in security controls, file sharing ability Leverages existing EPA Lotus Domino technology Data Download Portal Delivers server-side data processing, minimizing or eliminating the need for desktop GIS Responsive data exploration map viewer Relies on ESRI s ArcGIS Server technology

30 NUDAPT Tools Generalized methodology for alternative sets of UCPs Spatial allocation for (generalized regridding and grid geo-referencing capability Portal system and Internet collaboration

31 NUDAPT ancillary data Anthropogenic heating (250m grid) (Sailor) Gridded (3-D) Daily Diurnal Seasonal Population (25m grid) (Exposure applications) (Brown and McPherson) Day Night Advanced land use data, systems (Model evaluation, urban planning applications) 100 City studies (ASU) Transims (Links) (LaNL)

32 Gridded Anthropogenic Heating (Courtesy of David Sailor, NUDAPT Collaborator) 35 Q f (W/m 2 ) Q f (w/m 2 ) Qf (W/m^2) Local Time Houston: Month=08, Hour=20

33 Population Courtesy of McPherson and Brown (2007) Prototype: LANL Day/Night population (250 m resolution, Nationwide Future: LANL database including indoor/outdoor? Night time Population Daytime Population

34 SUMMARY NUDAPT provides: Platform for advancing state of urban modeling- accomodates new modeling systems, new (sets of) parameterizations Community framework facilitates collaborations Urban model focussed system Several tools including regridding and remapping to different size & map projections Prototypes provide strategic means for extensibility of its capability (copycat principle) Is non-stagnant (cities grow), can accommodate finer resolution data, data refresh cycle. Facilitates handover from model development to application deployment Extensibility on International bases, e.g., EU sponsored Megacity studies, prototypes

35 The End Thanks for your attention Disclaimer: The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.