1. uMM5 simulations of urban-reforestation effects on Houston UHIs for ozone-SIP emission-reduction credits R. Bornstein, H. Taha, R. Balmori San Jose State University San Jose, CA pblmodel@hotmail.com presented at GMU Dispersion Conference Fairfax, VA, July 2005

2. Acknowledgements D. Hitchock & P. Smith, State of Texas D. Hitchock & P. Smith, State of Texas D. Byun, U. of Houston D. Byun, U. of Houston J. Ching & S. Dupont, US EPA J. Ching & S. Dupont, US EPA Steve Stetson, SWS Inc. Steve Stetson, SWS Inc. S. Burian, U. of Utah S. Burian, U. of Utah D. Nowak, US Forest Service D. Nowak, US Forest Service NSF NSF

3. OUTLINE uMM5 uMM5 FORMULATION FORMULATION CLUSTER CLUSTER CURRENT APPLICATION CURRENT APPLICATION SYNOPTIC FORCING SYNOPTIC FORCING MESOSCALE INFLUENCES MESOSCALE INFLUENCES UHI IMPACTS UHI IMPACTS CONCLUSION CONCLUSION WHAT WE FOUND WHAT WE FOUND FUTURE EFFORTS FUTURE EFFORTS

4. Urbanization Techniques Urbanize surface, SBL, & PBL eqs. for momentum, thermo, & TKE Urbanize surface, SBL, & PBL eqs. for momentum, thermo, & TKE Allows prediction within UCL Allows prediction within UCL From veg-canopy model (Yamada 1982) From veg-canopy model (Yamada 1982) Veg param replaced with urban (GIS/RS) data Veg param replaced with urban (GIS/RS) data Brown and Williams, 1998 Brown and Williams, 1998 *Masson, 2000 *Masson, 2000 Sievers, 2001 Sievers, 2001 *Martilli et al., 2001 (in TVM) *Martilli et al., 2001 (in TVM) *Dupont et al., 2003 (in MM5) *Dupont et al., 2003 (in MM5)

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

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

7. 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 height-to-width, wall-plan, & impervious- area ratios  building frontal, plan, & and rooftop area densities  wall and roof: ε, cρ, α, etc.  vegetation: canopies, root zones, stomatal resistances

8. uMM5 performance by CPU  With 1 CPU: MM5 is 10x faster than uMM5  With 96 CPU: MM5 is only 3x faster than uMM5 (< 12 CPU not shown) With 96 CPU: MM5 is still gaining, but MM5 has ceased to gain at 48 CPU & With 96 CPU: MM5 is still gaining, but MM5 has ceased to gain at 48 CPU & then it starts to loose

9. Performance by physics sound waves & PBL schemes take most CPU in both urban/PBL scheme in uMM5 takes almost 50% of all time

10. W VS. NO. OF CPU: W max VS. NO. OF CPU: DIFFERENCES AT 16 & 17 HR COULD BE DUE TO CHANGES IN INTEGRATION TIME-STEP

11. Urbanization  day& nite on same line  stability effects not important Martilli/EPFL results Non-urban: urban

12. MESO-MET ATM-MODEL MUST CAPTURES ALL BC FORCING IN CORRECT ORDER O 3 EPISODES OCCUR ON A GIVEN DAY: O 3 EPISODES OCCUR ON A GIVEN DAY: NOT B/C TOPO, EMISSIONS, OR SFC MESO-FORCING (EXCEPT FOR FOG) CHANGES NOT B/C TOPO, EMISSIONS, OR SFC MESO-FORCING (EXCEPT FOR FOG) CHANGES BUT DUE TO CHANGES IN UPPER-LEVEL SYNOPTIC WX PATTERNS, WHICH BUT DUE TO CHANGES IN UPPER-LEVEL SYNOPTIC WX PATTERNS, WHICH COME FROM AN EXTERNAL MODEL & WHICH COME FROM AN EXTERNAL MODEL & WHICH ALTER MESO SFC-FORCING (i.e., TOPO, LAND/SEA, URBAN) VIA MESO-T AND THUS V ALTER MESO SFC-FORCING (i.e., TOPO, LAND/SEA, URBAN) VIA MESO-T AND THUS V MUST THUS EVALUATE ABOVE FACTORS: MUST THUS EVALUATE ABOVE FACTORS: UPPER LEVEL SYN Wx Patterns: p & then V UPPER LEVEL SYN Wx Patterns: p & then V TOPOGRAPHY (via grid spacing): V-channeling TOPOGRAPHY (via grid spacing): V-channeling MESO SFC: T & then V MESO SFC: T & then V

13. SCOS Temps RUN 1 03-Aug-9604-Aug-9605-Aug-9606-Aug-96 RUN 5

14. uMM5 for Houston O SIP uMM5 for Houston O 3 SIP GIS/RS gridded urban sfc parameters GIS/RS gridded urban sfc parameters uMM5 + reforestation  uMM5 + reforestation  reduced daytime max-UHI  CMAQ/CAMx O-model + uMM5 output  CMAQ/CAMx O 3 -model + uMM5 output  reduced: emissions & photolysis rates  lower O  emission-reduction credits  lower O 3  emission-reduction credits  big $-savings

15. From S. Stetson: Houston z o data

16. Coastal Cold- Core L on episode day at 3 PM for Domains: 1-3 L

17. Domain 4 (3 PM) : Note cold-core L off of Houston on O 3 day (25 th ) L L  Episode day day

18. Domain 3 (12 km) 4 PM: cold-core L (from SST-eddy??) L

19. From Julie Pullen L

20. SST and cold-core lows “Correct” wind direction + right angle coast  Sea-surface low-p eddy  Convergence  upwelling  Cold ocean-water  Cold-core atm low

21. Urbanized Domain 5: near-sfc 3 PM V on 4 successive days  Episode day day

22. Base-case (current) vegetation cover (urban min) Modeled increases in vegetation cover (urban max); values are 0.1 of those above

23. Soil moisture increase for: Run 12 (entire area, left) and Run 13 (urban area only, right)

24. 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

25. u1u1 seasea ru r u2u2 CMAQ ozone modeling for Houston SIP: 6 tree-planting scenarios  reduced UHIs (right) in urban-box 1 (left) for run 17  lower max-ozone  EPA emission-reduction credits Max impact

26. CONCLUSIONS Need to capture changes in large scale forcing Need to capture changes in large scale forcing Need to good urbanization for urban winds, temp (especially at sfc), turbulence, etc. Need to good urbanization for urban winds, temp (especially at sfc), turbulence, etc. Need to also have good SST, as it is the horiz temp-gradient that drives sea breezes Need to also have good SST, as it is the horiz temp-gradient that drives sea breezes Urban trees can reduce daytime UHIs and thus ozone Urban trees can reduce daytime UHIs and thus ozone

27. FUTURE EFFORTS Better urban meso-met models Better urban meso-met models Better urbanization Better urbanization Better turbulence (Frank Freedman’s work) Better turbulence (Frank Freedman’s work) Smaller horizontal grids Smaller horizontal grids WRF WRF Urban meso-scale models linked with Urban meso-scale models linked with CFD urban canyon scale models CFD urban canyon scale models BC as f (x, y, z, t) BC as f (x, y, z, t) One and two way nesting One and two way nesting Downscaling global climate-change model-results Downscaling global climate-change model-results UHI and thermal stress UHI and thermal stress Urban Wx (e.g., thunderstorms and flooding) Urban Wx (e.g., thunderstorms and flooding) Urban air quality Urban air quality

28. The End Questions?