uMM5 simulations of urbanreforestation effects on Houston UHIs for ozoneSIP emissionreduction credit

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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_at_hotmail.com prese
nted at GMU Dispersion Conference Fairfax, VA ,
July 2005
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Acknowledgements

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

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OUTLINE

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

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Urbanization Techniques

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

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Within Gayno-Seaman PBL/TKE scheme
From EPA uMM5 Mason Martilli (by Dupont)
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_________
______
3 new terms in each prog equation
? Advanced urbanization scheme from Masson (2000)
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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 e, c?, a, etc.
• vegetation canopies, root zones, stomatal
  resistances

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uMM5 performance by CPU
? With 1 CPU MM5 is 10x faster than uMM5
With 96 CPU MM5 is still gaining, but MM5 has
ceased to gain at 48 CPU then it starts to
loose
? With 96 CPU MM5 is only 3x faster than uMM5
(lt 12 CPU not shown)
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Performance by physics
sound waves PBL schemes take most CPU in both
urban/PBL scheme in uMM5 takes almost 50 of all
time
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Wmax VS. NO. OF CPU DIFFERENCES AT 16 17 HR
COULD BE DUE TO CHANGES IN INTEGRATION TIME-STEP
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Martilli/EPFL results
Urbanization ? day nite on same line ?
stability effects not important
Non-urban
urban
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MESO-MET ATM-MODEL MUST CAPTURES ALL BC FORCING
IN CORRECT ORDER

• O3 EPISODES OCCUR ON A GIVEN DAY
• NOT B/C TOPO, EMISSIONS, OR SFC MESO-FORCING
  (EXCEPT FOR FOG) CHANGES
• BUT DUE TO CHANGES IN UPPER-LEVEL SYNOPTIC WX
  PATTERNS, WHICH
• COME FROM AN EXTERNAL MODEL WHICH
• ALTER MESO SFC-FORCING (i.e., TOPO, LAND/SEA,
  URBAN) VIA MESO-T AND THUS V
• MUST THUS EVALUATE ABOVE FACTORS
• UPPER LEVEL SYN Wx Patterns p then V
• TOPOGRAPHY (via grid spacing) V-channeling
• MESO SFC T then V

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SCOS Temps
RUN 1
RUN 5
03-Aug-96
04-Aug-96
05-Aug-96
06-Aug-96
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uMM5 for Houston O3 SIP

• GIS/RS gridded urban sfc parameters
• uMM5 reforestation ?
• reduced daytime max-UHI ?
• CMAQ/CAMx O3-model uMM5 output ?
• reduced emissions photolysis rates ?
• lower O3 ? emission-reduction credits ?
• big -savings

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From S. Stetson Houston zo data
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Coastal Cold-Core L on episode day at 3 PM for
Domains 1-3
L
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Domain 4 (3 PM) Note cold-core L off of Houston
on O3 day (25th)
? Episode day
L
L
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Domain 3 (12 km) 4 PM cold-core L (from
SST-eddy??)
L
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From Julie Pullen
L
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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

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Urbanized Domain 5 near-sfc 3 PM V on 4
successive days

• Episode
• day

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Base-case (current) vegetation cover (urban min)
Modeled increases in vegetation cover (urban
max) values are 0.1 of those above
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Soil moisture increase for Run 12 (entire area,
left) and Run 13 (urban area only, right)
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Run 12 (urban-max reforestation) minus Run 10
(base case) near-sfc ?T at 4 PMreforested
central urban-area cools surrounding deforested
rural-areas warm
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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
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CONCLUSIONS

• Need to capture changes in large scale forcing
• 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
• Urban trees can reduce daytime UHIs and thus ozone

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FUTURE EFFORTS

• Better urban meso-met models
• Better urbanization
• Better turbulence (Frank Freedmans work)
• Smaller horizontal grids
• WRF
• Urban meso-scale models linked with
• CFD urban canyon scale models
• BC as f (x, y, z, t)
• One and two way nesting
• Downscaling global climate-change model-results
• UHI and thermal stress
• Urban Wx (e.g., thunderstorms and flooding)
• Urban air quality

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The EndQuestions?