SJSU Urbanized Mesoscale Atmospheric Modeling with uMM5

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SJSU Urbanized Mesoscale Atmospheric Modeling
with uMM5

• R. Bornstein, H. Taha
• F. Freedman, R. Balmori
• San Jose State University
• San Jose, CA
• e-mail pblmodel_at_hotmail.com
• Presented at
• Cost-728 Workshop
• UKMO, Exter
• 3-4 May 2007

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Acknowledgements

• Data from
• S. Burian, J. Ching
• TCEQ, USFS
• D. Byun
• Urbanization scheme from
• A. Martilli
• S. Dupont
• Funded by
• Past NSF, USAID, DHS
• Pending DTRA

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OUTLINE

• Introduction
• uMM5
• Formulation
• Applications
• Houston ozone episode
• NYC DHS street canyon tracer study
• (Future) uWRF
• Conclusion

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Recent Urbanization History

• Urbanize momentum, thermoynamic , TKE
• surface SBL diagnostic eqs
• PBL prognostic eqs
• From 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), Balmori et al. (2006) in
  uMM5

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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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S. Stetson Houston GIS/RS zo input
Values are too large, as they were f(h) and not
f(oh)
Values up 3 m
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uMM5 performance by CPU
? With 1 CPU MM5 is 10x faster than uMM5
1-96 CPU
Blow up of 12-96 CPU
With 96 CPU MM5 is still gaining, but MM5 has
ceased to gain at 48 CPU then it starts to
loose
Blow up of 12-96 CPU
? 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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Is it worth the effort? Martilli/EPFL q2-results
Urbanization ? day nite on same line ?
stability effects not important
Non-urban
urban
Urban model values gt rooftop max gt match obs
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uMM5 for Houston Balmori (2006)

• Goal Accurate urban/rural temps winds for Aug
  2000 O3 episode via
• uMM5
• Houston LU/LC urban morphology parameters
• TexAQS2000 field-study data
• USFS urban-reforestation scenarios ?
• UHI O3 changes

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uMM5 Simulation period 22-26 August 2000

• Model configuration
• 5 domains 108, 36, 12, 4, 1 km
• (x, y) grid pts 43x53, 55x55, 100x100, 136x151,
  133x141
• full-s levels 29 in D 1-4 49 in D 5 lowest ½
  s-level7 m
• 2-way feedback in D 1-4
• Parameterizations/physics options
• Grell cumulus (D 1-2) ETA PBL (D
  1-4)
• Gayno-Seaman PBL (D 5) simple ice
  moisture,
• urban module NOAH LSM RRTM radiation
• Inputs
• NNRP Reanalysis fields, ADP
  observational data
• urban morphology LIDAR building-data in D-5
  (from Burian) LU/LC modifications (from Byun )

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Episode-day Synoptics 8/25, 12 UTC (08 DST)
Surface
700 hPa
700 hPa sfc GC Hs at their weakest (no
gradient) over Texas ? meso-scale forcing (sea
breeze UHI convergence) will dominate
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Urbanized Domain 5 near-sfc 3 PM V on 4
successive days
H
C

• Episode
• day

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1 km uMM5 Houston UHI 8 PM, 21 Aug
UHI
UHI

• Upper, L MM5 UHI (2.0 K)
• Upper,R uMM5 UHI (3.5 K)
• Lower L (uMM5-MM5) UHI

Max change
LU/LC error
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8/23, 2-m daytime UHI obs vs uMM5 (D-5)
H
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Along shore flow came from Cold-Core L D-3 MM5
vs Obs Temps
H
Obs (18 UTC) gt Cold-core L (only 1 ob) gt
Urban area (blue-dot clump) retards cold-air
penetration

• MM5 produces coastal cold-core low

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UHI-Induced Convergence obs vs. uMM5 (d-5)
OBSERVED
uMM5
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Obs speeds (D-5) sfc roughness ?
speed-decrease in both urban-cores

-

-

-

V
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Base-case (current) vegetation cover in 0.1s
(urban min)
min
Modeled changed vegetation cover in 0.01s gt
Urban reforestation (green) gt Rural
deforestation (purple)
max increase
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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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DUHI(t) for Base-case minus Runs 15-18

• UHI Temp in Box-Urban minus Temp in Box-Rural
• Runs 15-18 different urban re-forestation
  scenarios
• DUHIRun-17 UHI Run-13 UHI (max effect, green
  line)
• Reduced UHI ? lower max-O3 (not shown) ?
• EPA emission-reduction credits ?

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Overall Lessons

• Models cant assumed to be
• gt perfect gt black boxes
• Need good large-scale forcing-model fields for a
  variety of synoptic conditions
• If obs not available, OK to make reasonable
  educated estimates, e.g., for rural
• gt deep-soil temp gt soil moisture
• Need data for comparisons with simulated fields
• Need good urban
• gt data gt urbanization schemes
• Need better rural-SBL parameterizations

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Pending FUTURE WORK uWRF

• uWRF with NCAR (F. Chen) for DTRA
• Martilli-Dupont urbanization
• Burian lidar urban-parameters as f(x,y)
• Taha stat-generalization of Burian
  urban-parameters for areas w/o lidar-obs
• Freedman PBL-turbulence scheme
• Zilitinkevich SfcBL stability-functions, zoh,
  etc.
• SST (x,y,t) from J. Pullen
• Application BC(x,y,t) to DTRA rapid ER model for
  Houston and perhaps NYC

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FUTURE WORK uWRF (cont.)

• One- and two-way linkage with CFD canyon models
  for ER applications
• Ozone-trends under climate-change conditions
• Calif
• NYC and Northeast
• Urban thunderstorms
• Initiation
• splitting
• Urbanized NWS Wx-forecasts

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APPROACH FOR LENGTH-SCALE PROG Freedman
Jacobson (2002 2003, BLM) Freedman at SJSU
2 prog Eqs. TKE DISSIPATION RATE e
__
__

• Where l ceE3/2/e
• Values of se sE are reversed in Mellor
  Yamada ?
• reversed in all atm models ?
• K TKE in upper-PBL were wrong!

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CALIBRATION TO NEUTRAL ABL l vs. z
Lines various values of ? ce2se/sE

• x COLEMAN (99) DNS
• New (R-panel) best-fit
• ? 1.3 (dashed line),
• w/ better results (l?) in
• upper PBL
• Standard approach
• (left panel) best fit
• with ? 2.5, w/ poor
• results in upper PBL

new
old
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Same, but for K(z)
x COLEMAN (99) DNS New (R-panel) best-fit
? 1.3 (dashed line), w/ better results in
lower PBL K? aloft Standard approach (left
panel) best fit with ? 2.5, w/ poor results
in lower PBL
new
old
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AMS Urban Conference

• Joint with AMS Coastal Conference
• Morning joint plenary sessions
• On coastal-urban topics
• Two 1.5 hour sessions each morning
• Eight invited keynote speakers (any suggestions?)
• Afternoon parallel sessions urban or coastal
• 10-13 Sept 2007 in San Diego, Calif.
• Abstracts due 11 May
• Organizers Bob Bornstein, Jason Ching, Dave
  Sailor (ametsoc.org)

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ThanksAny questions?