1. Conceptual database system for urban model development & applications Jason Ching ARL/NOAA –NERL/USEPA Research Triangle Park, NC ching.jason@epa.gov COST 728 Workshop Exeter, England May 3,4, 2007

2. Presentation outline CAVEAT: mostly generic but contains some USA perspectives Background: “Setting the stage” Rationale for a “database” focus Database content/concepts Prototype implementation of “NUDAPT” (National Urban Database and Access Portal Tools)

3. Guiding Principles Each model application is unique. The scale resolution of the modeling must be appropriate to the task (Use the right tools!) Current and future urban applications may require tools/techniques not yet available or under development; e.g., urban to local scale Hierarchical (nesting or adaptable gridding) approaches usually necessary. Appropriate data needed for modeling - both development and operational.

4. Addressing societal issues with urban modeling focus Air Quality –Health –Exposure assessments –Policy and Controls –Acute to chronic time scales Homeland security –Transport on episodic bases Urban impact on climate change –Growth –Urban heat island and its mitigation

5. Multi-scale AQ field (CMAQ) NO x (36km, 12km 4km and 1.3 km grid sizes)

6. Multiscale Ozone (see previous slide)

7. Background: The “Problem” To predict and characterize transport and concentration fields in urban areas –Models must be commensurate with scale of the transport and concentration gradients- Scale hierarchy –Current situation: Urban modeling too coarse a scale, boundary layer closure schemes, model descriptions were overly coarse and simplistic for real cities –Urban land use, land classification schemes limited, also overly simplistic –Urban complexities such as street canyons control exposures in urban areas –Urban areas evolve, some very rapidly Advanced modeling tools are needed for future urban application requirements; a myriad of problems remains unsatisfactorily addressable without adequate and or appropriate tools. –Data sets are not homogeneous (geospatial, activity, population, …) –Variety of model urbanization approaches have recently been implemented into mesoscale models. Testing, evaluation will lead to improved model description of physics and thermodynamics and model engineering and reutilization of database. –Operational urban models need to balance the overly simplistic to highly sophisticated parameterizations of urban features. Situation provides intriguing opportunities!

8. METHODOLOGY: Meso-urban scale modeling Modeler Needs: To capture the area- average effect of the urban area in mesoscale atmospheric models Solution: Modelers have implemented urban canopy parameterizations into their models (e.g., MM5, WRF, HOTMAC, RAMS, COAMPS…) Salt Lake City, UT (Don Green Photography)

9. 9 Rural Urban Rural Roughness Sub-Layer Neighborhood scale Local scale 1 km. Meso scale NEIGHBORHOOD SCALES Urban canopy details can not be represented: Parameterize the urban surface effects. Majority of pollutants emitted inside roughness sub-layer: Necessitates good precision on meteorological fields. Ground conditions in mesoscale model not satisfactory at neighborhood scale: apply drag-force and land use features at urban scales

10. 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. Buildings distributed in 1 km grid. ISSUE: Relating meso-urban to building scale

11. An implementation: DA-SM2U in MM5 (Gayno-Seaman sub-system) o Urbanization introduced at grid sizes of ~1km using drag approach (DA) o Land surface model (SM2-U) o Additional, within canopy layers

12. Wind tunnel and urban experiments provide guidance (Kastner-Klein and Rotach, 2001)

13. Urban canopy parameterization13 Roof area density Vegetation area density Building plan area density Vegetation plan area density Building frontal area density The knowledge of the vertical and horizontal distribution of the different urban land cover modes is necessary. Introduction of canopy concepts and urban morphology parameters make possible improved modeling

14. Frontal Area Index as a Function of Height

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

16.  ALTMS Normal Operating Parameters 30 km radius GPS Ground Station 915m AGL 210-240kph Swath width = 625m 10-30% overlap 3 m spacing 111,000 points/sq.km.

17. Profiling * Record Longest Return * Normally Rotary Wing * Continuous Ground Coverage

18. CANOPY UCPsBUILDING UCPs VEGETATION, OTHER UCPs Mean vegetation height Mean canopy heightMean HeightVegetation plan area density Canopy plan area densityStd Dev of heightsVegetation top area density Canopy top area densityHeight histogramVegetation 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 densityPlan area fraction surface covers Sky View FactorRooftop area density % connected impervious areas Frontal area densityBuilding material fraction Gridded (1 km) Urban Canopy Parameters (UCP) from high resolution data for urbanized MM5 *Parameters used in RA formulationsHeight dependent UCP

19. Selected Urban Canopy Parameters per 1 km 2 cells for Harris County, TX NOTE! Each grid cell has unique combination of UCPs

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

21. Air Quality Model (CMAQ) at fine scales Pollutant model simulations are sensitive to (and dependent on) grid resolution AQ simulations depend on outputs of meteorological models which in turn depend on model descriptions of physics and thermodynamics.

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

23. Fundamental urban model engineering design requirements Urban morphological structures: –Form and pressure drag from obstacles –Reflective, radiative and thermodynamic properties of buildings, roofs, paved surface areas, street canyons Land surfaces: –Soils –Vegetative canopy –Degree of imperviousness to moisture –Surface propertiesThermal resistivities, ground storage Land cover classes: –Apt model descriptors and classifications –Grid coverage: Dominant vs fractional area methodology Anthropogenic heating

24. Database Concepts Bases for implementing descriptive parameterizations at appropriate scales –High resolution building and other urban morphological features –Sets of urban canopy parameterizations for various advanced meteorological modeling –Tools to generate UCPs for generalized gridding and reference systems –Community based, flexible and encouraging of collaborative studies to improving urban scale modeling and facilitating their scientific acceptance –Supports hierarchical (nesting) approaches from mesoscale (regional) to urban scale to applications requiring CFD type approaches –Provide for evaluation- at appropriate scales Facilitates advanced, scale dependent applications –Transboundary to regional to urban to neighborhood –Forecast WX and air quality in urban areas –Air quality (Transboundary-regional-urban–to local) –Dispersion (vectors to agents) –Exposure (personal, population, air pollutants, agents) –Urban planning (mitigating intensity of heat islands)

25. 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

26. NUDAPT Portal: Two systems, One Whole Quickplace –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

27. Quickplace Welcome

28. Quickplace Summary Collaboration tool – what the group gets out depends on what the individual puts in Easy to share documents, model results, smaller datasets (less than 200MB), presentations, etc Available calendar/task management tools Help build consensus on UCP methods and strategies Tool lets you manage the collaboration

29. Data Download Portal Map –AJAX for smooth dragging and zooming –Built-in identify, measure, and magnify tools –Dynamic table of contents Data repository –Quickly import data, add to map, publish to web –Tightly integrated with windows security –GIS tools allow fast, easy data pre-processing

35. Data Download Tool Inputs Input Raster or Basket of Rasters Clip Extent Output Coordinate Reference System Resampling Method Output Cell Size Output File Format

36. Clip Extent Draw extent directly on the map Tool uses bounding box envelope Envelope projected into spatial reference of raster and output Could investigate taking extent input in Lat/Long instead

37. Output Coordinate Reference System Initially contains only four systems, all NAD83 –Geographic Latitude/Longitude –UTM Zone 15N –USGS Albers Equal Area –South Central Texas State Plane (Feet) ESRI Library contains hundreds, all could be added in a few minutes Also have option of leaving all rasters in source projection

38. Resampling Method Nearest Neighbor Bilinear Interpolation Cubic Convolution

39. Download Processing Flow Input Raster Input Extent Polygon Output Coordinate System Resampling Method Output Cell Size Output File Format Get Feature Envelope Clip Extent Clip Raster Clipped Raster Project Raster Projected Raster Clip Raster Clipped Raster Convert Raster to Other Format Output Raster Zip Output Zip File Project Feature Projected Envelope Get Feature Envelope Projected Clip Extent

40. Output Cell Size All rasters will be resampled to user-specified output cell size If no cell size specified, all rasters will remain at source resolution Regardless of input, no output will have smaller cell size than the minimum output resolution cutoff (15m) Minimum resolution determined by security restrictions

41. Output File Format Available formats are: –NetCDF –ASCII –Floating Point –Imagine Image –GeoTiff All output files (rasters, header files, metadata) are zipped for download Binary results “key” allows you to pick up output later

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

43. Extrapolating UCPs to Areas Without Data More than 90% grids in the modeling domain do not have UCP data. CPs correlated to underlying land use in areas where base data existed and then extrapolated to other areas by area- weighted averaging (from ChingUCPs correlated to underlying land use in areas where base data existed and then extrapolated to other areas by area- weighted averaging (from Ching, Burian). Building UCPs correlated to population (e.g., day, night, worker) at 250-m and 1-km resolution (Burian).Building UCPs correlated to population (e.g., day, night, worker) at 250-m and 1-km resolution (Burian). GIS Extrapolation Tool are programmed with models selected based on fit to data, testing results, and judgment to estimate UCPs based on population and land use (Burian).

44. NUDAPT ancillary data resources Anthropogenic heating (component of model thermodynamics) –Gridded (3-D) –Daily –Diurnal –Seasonal Population (Exposure applications) –Day –Night Advanced land use data, systems (Model evaluation, urban planning applications) –100 City studies –Transims

45. UCPs for MM5 (see earlier)  Mean and standard deviation of building and vegetation height  Plan-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-width ratio  Sky view factor at ground level and as a function of height  Aerodynamic roughness length and displacement height (Raupach, Macdonald, Bottema, Coefficient)  Mean orientation of streets  Surface fraction of vegetation, roads, rooftops, and water and impervious area, directly connected impervious area, albedo and building material using remote sensing

46. UCPs for urbanized WRF 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 Emissive 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

47. Other model systems Canadian model based on TEB Global model with urban features COAMPS Advanced urbanized WRF with canopy- drag formulations Others?

48. Prototypes- by urban area Houston –High resolution building data base –DA-SM2U/MM5; uMM5, urbanized WRF, urban components in Global, urbanized COAMPS, Canadian (TEB) –Coastal, bay breeze geo-climate –FDDA sea surface temperatures –Anthropogenic heating –Day-night population –Model evaluation databases TEXAS 2000, 2006 –Model sensitivity studies to input of urbanized met model fields CMAQ AQ studies Dispersion (HPAQ and HySplit) Exposure assessments (AQ –hospital admissions study) Phoenix –Mountain valley flow regime –Rapid urbanization –Urbanized DA-SM2U/MM5 –Urban heat island mitigation studies –Utilizes MODIS and ASTER data Atlanta –Either urbanized MM5 or WRF –Application of TRANSIMS –Exposure assessments

49. SUMMARY: Urban database conceptual design provides: Platform for advancing state of urban modeling- accomodates new modeling systems, new (sets of) parameterizations Community framework facilitates collaborations Modeler’s focused system Several tools including regrid and remap 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 EU sponsored Megacity study and its databases can be incorporated and accommodated as a special prototype

50. 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 DW13921548. 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.