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Title: Overview%20of%20urban%20models%20for%20simulation%20of%20urban%20climate,%20weather,%20and%20air%20quality


1
Overview of urban models for simulation of urban
climate, weather, and air quality
Prof. Bob Bornstein Dept. of Meteorology San Jose
State University San Jose, CA USA pblmodel_at_hotmail
.com presented at MEETING OF EXPERT TEAM ON
URBAN CLIMATOLOGY WMO, GENEVA, 23 MAY 2005
2
PROPOSED OUTLINE
  • HISTORY
  • CURRENT STATUS
  • NEW FORMULATIONS
  • PROBLEM AREAS
  • APPLICATIONS
  • WEATHER
  • CLIMATE
  • AIR QUALITY
  • OUTLOOK
  • FURTHER ADVANCEMENTS
  • LOCAL APPLICATIONS

3
HUMAN-HEALTH IMPACTS OF URBAN CLIMATEselling
points
  • UHI ? THERMAL STRESS
  • PRECIP ENHANCEMENT RUNOFF? FLOODS
  • CHANGED DISPERSION PATTERNS FOR
  • POLLUTION EPISODES
  • EMERGENCY RESPONSE

4
NEW URBAN TEMPS CAUSES THAT MUST BE MODELED
  • GRASS/SOIL ? CONCRETE/BUILDINGS ?
  • NEW SOIL MOISTURE CONTENT ?
  • NEW THERMAL INERTIA ?
  • ALTERED SFC HEAT MOSITURE FLUXES
  • FUEL CONSUMPTION ?
  • ATM POLLUTION, HEAT, AND MOISTURE
  • BUILDINGS (LOW SKY-VIEW FACTORS)
  • ATM POLLUTION?
  • ALTERED (SOLAR IR) RADIATIVE FLUXES

5
URBAN WX ELEMENTSbattles b/t conflicting
effects that must be modeled
  • TEMP PRECIP increased or decreased
  • VISIBILTITY decreased
  • WIND SPEED increased or decreased
  • WIND DIRECTION con- divergence
  • TURBULENCE increased (mechanical thermal)
  • PBL NIGHT STABILITY neutral
  • FRONTS (synoptic sea breeze) slowed
  • THUNDERSTORMS triggered or split

6
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7
New Urbanization Techniques
  • Urbanize surface, SBL, PBL (momentum,
  • thermo, TKE) Eqs
  • Allows prediction within UCL
  • From veg-canopy model (Yamada 1982)
  • Veg param replaced with urban (GIS/RS) ones
  • Brown and Williams 1998
  • Masson 2000
  • Sievers 2001
  • Martilli et al. 2001 (in TVM)
  • Dupont et al. 2003 (in MM5)

8
? From Masson (2000)
9
Sfc Energy Models SiB has new vegy-paramters
10
Within Gayno-Seaman PBL/TKE scheme
From EPA uMM5 Mason Martilli (by Dupont)
11
_________
______
3 new terms in each prog equation
? Advanced urbanization scheme from Masson (2000)
12
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, building plan, and rooftop
    area-
  • densities
  • wall and roof e, c?, a, etc.
  • vegetation canopies, root zones, stomatal
    resistances

13
From S. Stetson Houston zo data
14
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15
Performance by physics
sound waves PBL schemes take most CPU in both
urban/PBL scheme in uMM5 takes almost 50 of all
time
16
Urbanized meso-met model results
urban effect
_________________
17
Martilli/EPFL results
Urbanization ? day nite on same line ?
stability effects not important
Non-urban
urban
18
KEY IDEA IDEAL MESO-MET ATM-MODEL CAPTURES ALL
BC FORCINGS 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-FORCINGS (i.e., TOPO, LAND/SEA,
    URBAN) VIA MESO-TEMP AND THUS WIND
  • MUST THUS EVALUATE ABOVE FACTORS
  • UPPER LEVEL SYN WX Patterns pressure then
    winds
  • TOPOGRAPHY (via grid spacing) channeling of wind
  • MESO SFC temperature then winds

19
SCOS Temp (full domain)
RUN 1
RUN 5
03-Aug-1997
04-Aug-1997
05-Aug-1997
06-Aug-1997
20
NYC (a) z0 vs UHI effect in z-section (upper L)
(b) Sea breeze obs (upper R), (b) no
barrier (lower L), with barrier (lower R)
21
ATLANTA UHI-INITIATED DAYTIME STORM (0BS) T V
(UPPER L) CONV (UPPER R) PRECIP (LOWER L)
CLOUDS (LOWER R)
22
MM5 simulation of previous storm UHI (upper L),
CONV (UPPER R) w (lower L), PRECIP (LOWER R)
23
uMM5 for Houston O3 SIP
  • GIS/RS gridded urban sfc parameters
  • uMM5 reforestation ?
  • reduced daytime max UHI ?
  • CMAQ O3 model uMM5 output ?
  • reduced emissions photolysis rates ?
  • lower O3 ? emission-reduction credits ?
  • big savings of

24
Coastal Cold-Core L on episode day at 3 PM for
Domains 1-3
L
25
Domain 4 (3 PM) Note cold-core L off of Houston
on O3 day (25th)
? Episode day
L
L
26
Urbanized Domain 5 near-sfc 3 PM winds on 4
successive days
  • Episode
  • day

27
Domain 5 end of daytime UHI (8 PM 21 Aug)
  • Upper L MM5
  • Upper R uMM5
  • Lower L uMM5-MM5
  • uMM5? 1.5 K warmer (stronger UHI)
  • Blob is LU/LC error

28
Domain 5 end of night UHI 9 AM 22 Aug
  • Upper L MM5
  • Upper R uMM5
  • Lower L MM5-uMM5
  • uMM5? 1.5 K cooler (weaker UHI)

29
Explanation of uMM5 UHI UCI
  • Wet soil TI gt urban TI gt dry soil TI
  • Urban area surrounded by wet soil ?
  • Daytime UHI (as urban area warms faster than
    soil)
  • Nighttime UCI (as urban area cools faster than
    soil)
  • Reverse true with dry rural soil
  • Current results thus consistent with wet rural
    soil (as expected) around Houston, as uMM5
    produced daytime warming nighttime cooling of
    Houston

30
Base-case (current) vegetation cover (urban min)
Modeled increases in vegetation cover (urban
max) values are 0.1 of those above
31
Soil moisture increase for Run 12 (entire area,
left) and Run 13 (urban area only, right)
32
Run 12 (urban-max reforestation) minus Run 10
(base case) near-sfc ?T at 4 PM shows
thatreforested central urban-area cools
surrounding deforested rural-areas warm
33
CMAQ ozone modeling for Houston SIP 6
tree-planting scenarios ? reduced UHIs (right)
in urban-box 1 (left) for run 17? lower
max-ozone ? emission-reduction credits from EPA
Max impact
34
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35
EMERGENCY RESPONSEgt INFO REQUIRED (IN
20-30 MIN)gt NEED URBAN-CANYON METgt QUESTIONS
TO BE ANSWERED
  • WHAT IT IS
  • WHAT IS ITS CONCENTRATION
  • WHERE IS ITS SOURCE
  • WHERE WILL IT GO
  • WHAT ARE ITS FUTURE
  • CONCENTRATION PATTERNS

36
REAL-TIME FORECASTS REQUIRE
  • FAST CPU
  • GOOD LARGE-SCALE WX-MODEL RESULTS
  • GOOD URBAN-CANYON MODULES IN MESO-MODELS
  • GOOD MESOSCALE (SFC UPPER AIR) OBS NETWORKS
  • REAL-TIME COMMUNICATIONS
  • SIMPLE MODELS FOR EMERGENCY RESPONSE

37
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38
NEIGHBORHOOD-SCALE RESEARCH MODELS
  • TYPES
  • EPA WIND TUNNEL
  • NOAA CFD (FLUENT)
  • INDOOR-OUTDOOR EXCHANGE (LBNL)
  • USES
  • SCIENTIFIC UNDERSTANDING
  • DEVELOP PARAMETERIZATIONS FOR RAPID RESPONSE
    MODELS

39
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40
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41
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42
QUIC Simulation dd 215 deg
MSG
wind vectors at 5 m height
43
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44
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45
LBNL Group
46
FUTURE TRENDS
  • Meso-met forecasts for
  • Regional air quality
  • Urban met
  • Better urban meso-met models
  • Faster computers
  • Better parameterizations
  • Smaller grids
  • Urban meso-scale models linked with
  • CFD urban canyon scale models
  • Downscaling of global-change model results

47
The EndQuestions?
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