1. Observation & simulation of urban-effects on climate, weather, and air quality Bob Bornstein Dept. of Meteorology, SJSU Haider Tahabbb, Altostratus, Inc. pblmodel@hotmail.com presented at NCAR 8 August 2008

2. Acknowledgements Ex-students: – R. Balmori – S. Kasaksch – E. Weinroth Data – S. Burian, J. Ching – TCEQ, USFS – D. Byun Urbanization of – A. Martilli – S. Dupont Funds: NSF, USAID, DHS

3. OVERVIEW > URBAN MESO-MET MODELS – FORMULATION – APPLICATIONS Houston NYC Sacramento > FUTURE EFFORTS

4. GOOD MESO-MET MODELING MUST CORRECTLY REPRODUCE: – UPPER-LEVEL Syn/GC FORCING FIRST: pressure (“the” GC/Syn driver)  Syn/GC winds – TOPOGRAPHY NEXT: min horiz grid-spacing  flow-channeling – MESO SFC-CONDITIONS LAST: temp (“the” meso-driver) & roughness  meso-winds

5. Mid-east Obs vs. MM5: 2 m temp (Kasakech; USAID) July 29August 1August 2 July 31 Aug 1 Aug2 Standard-MM5 summer night-time min-T, But lower input deep-soil temp  better 2-m T results  better winds  better O 3 obs Run 1 MM5:Run 4 Obs Run 4: Reduced Seep-soil T First 2 days show GC/Syn trend not in MM5, as MM5-runs had no analysis nudging

6. Recent Meso-met Model Urbanization > Need to urbanize momentum, thermo, & TKE – surface & SfcBL diagnostic-Eqs. – PBL prognostic-Eqs. > Start: veg-canopy model (Yamada 1982) > Veg-param replaced with GIS/RS urban-param/data – Brown and Williams (1998) – Masson (2000) – Martilli et al. (2001) in TVM/URBMET – Dupont, Ching, et al. (2003) in EPA/MM5 – Taha et al. (2005, 08), Balmori et al. (2006) in uMM5: detailed input urban-parameters as f(x,y)

7. From EPA uMM5: Mason + Martilli (by Dupont) Within Gayno-Seaman PBL/TKE scheme

8.  Advanced urbanization scheme from Masson (2000) ______ _________ 3 new terms in each prog equation

9. New GIS/RS inputs for uMM5 as f (x, y, z)  land use (38 categories)  roughness elements  anthropogenic heat as f (t)  vegetation and building heights  paved-surface fractions  drag-force coefficients for buildings & vegetation  building H to W, wall-plan, & impervious-area ratios  building frontal, plan, & rooftop area densities  wall and roof: ε, cρ, α, etc.  vegetation: canopies, root zones, stomatal resistances

10. Urbanization  day & nite on same line  stability effects not important Martilli/EPFL q-results Martilli/EPFL q 2 -results Non-urban: urbanUrban-model values > rooftop max > match obs

11. uMM5 for Houston: Balmori (2006) Goal: Accurate urban/rural temps & winds for Aug 2000 O 3 episode via – uMM5 – Houston LU/LC & urban morphology parameters – TexAQS2000 field-study data – USFS urban-reforestation scenarios  UHI & O 3 changes

12. H H i) H L 14 UTC 15 16 17 18 19 21 23 j) At 2300 UTC & summary of N-max ---- 

13. uMM5 Simulation period: 22-26 August 2000 Model configuration – 5 domains: 108, 36, 12, 4, 1 km – (x, y) grid points: (43x53, 55x55, 100x100, 136x151, 133x141 – full-  levels: 29 in D 1-4 & 49 in D-5; lowest ½  level=7 m – 2-way feedback in D 1-4 Parameterizations/physics options > Grell cumulus (D 1-2)> ETA or MRF PBL (D 1-4) > Gayno-Seaman PBL (D-5) > Simple ice moisture, > urbanization module NOAH LSM > RRTM radiative cooling Inputs > NNRP Reanalysis fields, ADP obs data > Burian morphology from LIDAR building-data in D-5 > LU/LC modifications (from Byun)

14. Domain 4 (3 PM) : cyclone off-Houston only on O 3 -day (25 th ) L L  Episode day day

15. Urbanized Domain 5: near-sfc 3-PM V, 4-days  Episode day day Cold-L Hot Cool

16. 1 km uMM5 Houston UHI: 8 PM, 21 Aug Left: MM5 UHI = 2.0 K ; Right: uMM5 UHI = 3.5 K

17. UHI-Induced Convergence: obs vs. uMM5 OBSERVEDuMM5 C C C C

18. Base-case (current) veg-cover (0.1’s)  urban min (red)  rural max (green) Modeled changes of veg-cover (0.01’s) > Urban-reforestation (green) > Rural-deforestation (purple) min max increase

19. Run 12 (urban-max reforestation) minus Run 10 (base case): near-sfc ∆T at 4 PM reforested central urban-area cools & surrounding deforested rural-areas warm warmer cooler

20. DUHI(t): Base-case minus Runs 15-18 DUHI(t): Base-case minus Runs 15-18 UHI = Temp in Urban-Box minus Temp in Rural-Box UHI = Temp in Urban-Box minus Temp in Rural-Box Runs 15-18: urban re-forestation scenarios Runs 15-18: urban re-forestation scenarios D UHI = Run-17 UHI minus Run-13 UHI  D UHI = Run-17 UHI minus Run-13 UHI  max effect, green line Reduced UHI  lower max-O 3 (not shown)  Reduced UHI  lower max-O 3 (not shown)  EPA emission-reduction credits  $ saved  Max-impact of –0.9 K of a 3.5 K Noon-UHI, of which 1.5 K was from uMM5 URBAN RURAL

21. NYC DHS Urban Dispersion Study: Emergency Response

22. NYC/UDS MSG & MIDTOWN DHS/STRA From: J. Allwine

23. uMM5 for NYC DHS MSG UDS Goal: Accurate urban/rural temps & winds for 9-15 March ‘05 tracer releases via – uMM5 – NYC LU/LC & urban morphology parameters from S. Burian – DHS MSG UDS field-study data met tracer (not used as of yet)

24. NYC uMM5 DHS UDS MSG: 9-15 March ‘05 Model configuration – 4 domains: 36, 12, 4, 1 km – (x, y) grid points: (110x85, 91x91, 91x91, 33x33) – full-  levels: 29 in D 1-3 & 48 in D-4; lowest ½  level=7 m – 2-way feedback in D 1-3 Parameterizations/physics options > Grell cumulus (D 1-2)> ETA or MRF PBL (D 1-4) > Gayno-Seaman PBL (D-5) > Simple ice moisture, > urbanization module NOAH LSM > RRTM radiative cooling Inputs > NNRP Reanalysis fields, ADP obs data > Burian morphology from LIDAR building-data in D-5 > LU/LC modifications (from Byun)

25. NWS 700 hPa 3/10/05: 00 & 12 UTC 00 UTC = 19 EST on 3/9/05 High speed zonal flow from Low N of NYC 12 UTC = 07 EST on 3/10/05

26. 1 km uMM5 Domain MM5 moved Low away too fast

27. 1 km uMM5 Domain

28. Summary of uMM5 MSG flow field Low level high speed (& thus weak UHI) roughness- induced deceleration  convergence  upward motion Upper level (“return flow”) compensating down motion  acceleration  divergence

29. 1 km uMM5 Speed (flag = 5 m/s) & T (K) 09 EST, 3/10/05, 4 levels WeakUHI

30. 1 km uMM5 Speed (flag = 5 m/s): 10 EST, 3/10/05, 4 levels SLOW FAST

31. 1 km uMM5 Speed (flag = 5 m/s) & Con/Div (1/s) 11 EST, 3/10/05, 4 levels CON DIV

32. 1 km uMM5 Speed (flag = 5 m/s) & w (m/s) 11 EST, 3/10/05, 4 levels UP Down

33. Urban Ocean-Atmosphere Observatory (UOAO) by Jorge E. González 1, Mark Arend 1, Fred Moshary 1 Alan F. Blumberg 2 Stuart Gaffin 3, Cynthia Rosenzweig 3 Dave Robinson 4 Brian Colle 5 Robert D. Bornstein 6,1 1 City College of New York (CCNY) 2 Stevens 3 NASA Goddard Institute for Space Studies (GISS) 4 Rutgers University 5 State University of NY (SUNY) at Stonybrook 6 San José State University (SJSU) Presented to 3 rd Annual Interagency Workshop, NYC 15 July 2008

34. CCNY Met-Net: roof top sites, sodars, lidar

35. 190020002080 UHI GW NYC Heat Burden: Past, Present, & Projected (Columbia University & GISS) ~7 o C / 13 o F 2oC2oC 7 days above 90 o F 14 days above 90 o F 3-4 days above 95 o F Most of Summer above 90 o F 17-50 days above 95 o F GW = Global Warming UHI = urban heat island

36. 36 Modeling and applications of urbanized MM5 (uMM5) for Houston, Sacramento, and SoCAB by Haider Taha Altostratus Inc.

37. 37  Nested grids – two-way feedback  Drag coefficients – vegetation and buildings / shape-dependent  Multiple directions FAD-related wind and TKE computations  Multiple directions FAD / TAD directional grid-cell z o computations  Canyon orientation / urban radiation (and air flow, see next item)  Microscale model nest and feedback in grids of interest (e.g., high-rise or pollution/dispersion application)  Species-specific spatially-varying vegetation albedo  Spatiotemporally-varying indoor air temperature, as function of building type, season, and heating/cooling loads  Watering schedules in evapotranspiration calculations uMM5 updates (1 of 3)

38. 38  Modifications to input generation techniques, processing, and data ingestion in model  Non-LULC-based input: remote-sensing, externally processed data, surveys, location-specific  Alternative UCP / morphology generation approach (using earth-PRO data)  Adaptation for UHI studies; sets of surface modification scenarios uMM5 updates, cont’d

39. 39  Surface physical properties of roofs, walls, pavements, etc. (i.e., material, construction type, age, albedo, emissivity, etc.)  Surface types (i.e., flat roofs, sloped roofs, geometrical features, green/garden roofs, parking structures)  Canyon orientation (e.g., gridded 15º binned canyon lengths)  Vegetation-specific information: LAI (function of season), geometry, albedo, age, evergreen/deciduous, potential evapotranspiration, proximity to buildings  4-D anthropogenic heat flux (LULC-independent), source location (3-D)  4-D latent heat flux / water vapor sources, e.g., cooling towers uMM5 updates, cont’d

40. 40 e.g., per-LULC vertical profile averages in Downtown Sacramento (representative of that area only). Red: commercial, Brown: mixed, Light blue: industrial/commercial, Blue: residential, Yellow: industrial Building PAD profiles as basis for extrapolation into non- UCP regions of Greater Sacramento area. PAD then used in computing other parameters, e.g., FAD, TAD, h2w, w2p, mean building height, and SVF Extrapolation to non-data regions: Vertical profiles of building and vegetation canopies Plan-area densityTop-area density Frontal-area density Plan-area density Taha, H. 2008c, Atmospheric Environment

41. 41 Sacramento nighttime heat island Sacramento morning cool island for Sacramento, 1 August 2000 Meso-urban modeling; fine-resolution meteorological features Taha, H. 2008c, Atmospheric Environment

42. 42 Downtown Sacramento Fine-resolution photochemical simulations Sacramento 1-km uMM5 domain, 1300 PDT, 31 July 2000 Taha, H. 2008c, Atmospheric Environment

43. Change in sfc temp (top left) from increased urban surface albedo, compared to building PAD function at 1m AGL (top right). Air temp change at a randomly selected location (bottom left). PAD (m 2 /m 3 )  T (surface)  T (air) 43 e.g., impacts from UHI mitiga-tion: Sacramento Domain 5

44. August 1 st, simulated ozone at a location in Sacramento (top of graph) and changes resulting from UHI control (bottom of graph) Top: Simulated daily max 8-hour average ozone in Sacramento (at Folsom / Natoma monitor). Bottom: reduction (%) in daily max as RRF from UHI control.n Potential air-quality improvements from UHI control Taha, H. 2008c, Atmospheric Environment

45. C053 (urban residential)C010 Texas City (open) C603 sub-urban industrial C034 Galveston (open) C607 (urban industrial) KGLS Scholes Field (open) Performance of uMM5 (base case) Houston Observed and simulated air temperature at sampling height for selected stations (subset from 26 monitors). bold line=observed, thin line=uMM5 Near-shore stations: Note absence of characteristic diurnal signal Urban stations: Locations are relatively removed from shore & exhibits diurnal pattern Taha, H. 2008a, Boundary-Layer Meteorology

46. Overall Lessons > Models can’t assumed to be > perfect > black boxes > Need good large-scale forcing-model fields > If obs not available, OK to make reasonable educated estimates, e.g., for rural > deep-soil temp > soil moisture > Need data for comparisons with simulated-fields > Need good urban > morphological data > urbanization schemes > Need better rural-SfcBL parameterizations

47. FUTURE WORK uWRF – Martilli-Taha-Chen urbanization – SST (x,y,t) from J. Pullen – S. Zilitinkevich, et al. SfcBL stability-functions (convective to wave-q 2 ) z oh Sea-sfc z o – D. Steyn diagnostic h i (x,y) scheme – PBL-turbulence of: S. Zilitinkevich, F. Freedman, B. Galperin, L. Mahrt

48. FUTURE WORK (cont.) > Applications – Linkage (1- & 2-way) BC (x,y,t) for CFD & rapid-ER canyon-models for NYC – UHI and heat-stress trends under climate-change conditions & Q f (x,y,z,t) (with D. Sailor for Portland) – Urban thunderstorms (with NSF): initiation & splitting – urban Wx-forecasts (with NWS): stat & uWRF – Participation in EU MEGAPOLI urbanization project – With J. Gonzales: Silicon V. NSF Center of Excellence (SCU); NYC UOAO (CCNY), San Juan UHI (UPR); & UHI impacts on Calif. coastal cooling with uRAMS (SCU) re O 3 (with CARB), energy with CCEC), ag. (Wine Board)

49. Thanks for listening! Time for discussion/questions