How well can we model air pollution meteorology in the Houston area? - PowerPoint PPT Presentation

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How well can we model air pollution meteorology in the Houston area?

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New metric of sea breeze correspondence shows improvement at all 7 surface sites ... Sea breeze correspondence is good at C45, closest to Bay and Gulf, with ... – PowerPoint PPT presentation

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Title: How well can we model air pollution meteorology in the Houston area?


1
How well can we model air pollution meteorology
in the Houston area?
Wayne Angevine CIRES / NOAA ESRL Mark Zagar Met.
Office of Slovenia Jerome Brioude, Robert Banta,
Christoph Senff, HyunCheol Kim, Daewon Byun
2
Orientation
  • Surface sites to be used for temperature and wind
    comparisons
  • LaPorte wind profiler in green

50km
Galveston Bay
55km
Gulf of Mexico
3
Orientation
  • Satellite image on 1 September 2006 1137 LST
  • Coasts low and sandy, little elevation change or
    terrain

4
Measurements and simulations
  • Texas Air Quality Study II (August-October 2006)
  • Surface meteorological and pollution monitoring
    sites
  • Mixing heights and winds from a radar wind
    profiler at LaPorte (on land)
  • WRF simulations

5
How can we tell if one model run is better than
another?
  • Need metrics that clearly show improved
    performance
  • Several approaches
  • Traditional bulk statistics
  • Case studies
  • Sea breeze and stagnation frequency
  • Plume locations

6
WRF simulations
  • 75 days, 1 August 14 October 2006
  • 5 km inner grid spacing
  • Three styles
  • FDDA of 3 wind profilers, reduced soil moisture,
    and hourly SST
  • FDDA of 3 wind profilers and reduced soil
    moisture
  • Reduced soil moisture only
  • All with ECMWF initialization every 24 hours (at
    0000 UTC)
  • Retrospective runs, not forecasts

7
Impact of FDDA on wind profile
  • Full run, all hours
  • FDDA reduces random error in direction
  • Note this is not an independent comparison (this
    data was assimilated)
  • Red is FDDA run
  • Blue has FDDA, 1-h SST, and reduced soil moisture
  • Green has reduced soil moisture only

8
Impact of FDDA on surface winds
  • Full run, all hours
  • FDDA reduces random error in direction (more
    clearly seen if only daytime hours are
    considered)
  • ECMWF has less speed bias at C35 and C45 and less
    random error in speed at all sites
  • ECMWF has similar direction bias and random error
    to WRF runs over all hours, but WRF w/FDDA is
    better in daytime
  • Red is FDDA run
  • Blue has FDDA, 1-h SST, and reduced soil moisture
  • Green has reduced soil moisture only
  • Black is ECMWF

9
Impact of FDDA and soil moisture on surface winds
  • Episode days (17) only
  • Site C45, southeast of Houston very near
    Galveston Bay
  • FDDA improves random error in both speed and
    direction
  • 1-h SST improves random error in the afternoon,
    but makes it worse at night
  • ECMWF has different but comparable errors, but
    WRF w/FDDA is better at hours 18 and 21 (and
    worse at hour 3)
  • Red is FDDA run
  • Blue has FDDA, 1-h SST, and reduced soil moisture
  • Green has reduced soil moisture only
  • Black is ECMWF

10
Impact of FDDA and soil moisture on surface
temperatures
  • When are the errors worst?
  • 10 days have at least one hour with temperature
    difference gt 5K at site C35 (28 hours total) in
    FDDA run
  • All differences gt 5K have model gt measurement
    (model too warm)
  • All 10 days have convection or a cold front in
    reality
  • Model also has clouds and fronts but different
    amount, timing, or location

11
New metricsSea breeze frequency
  • How often does a sea breeze occur in the
    simulation AND measurement?
  • Definition Northerly component gt1 m/s between
    0600 and 1200 UTC and southerly gt1 m/s after 1200
    UTC
  • FDDA or FDDA1hSST run closer to measurement at
    all 7 sites (at least a little)
  • Results not sensitive to threshold

Red is FDDA run Blue has FDDA, 1-h SST, and
reduced soil moisture Green has reduced soil
moisture only
12
New metricsNet trajectory distance
  • Trajectories starting midway along the Ship
    Channel at 1400 UTC each day, extending for 10
    hours at 190 m AGL
  • WRF run w/FDDA
  • Comparing total distance to net distance
  • A rough measure of recirculation
  • The lower left portion of the diagram is of most
    interest

13
New metricsNet trajectory distance
  • Net distance was found by Banta et al. to
    correlate well with maximum ozone
  • Also holds for trajectories from WRF simulated
    winds, shown here
  • r -0.85, r2 0.72
  • Run with FDDA
  • Run with 1-h SST about the same
  • Total distance correlation much worse (r -0.57)

14
New metricsVector average wind
  • Averaging u and v vs. averaging speed
  • Over 10 hours 1400-2400 UTC
  • Interesting points are those below the 11 line
    since they have significant curvature
  • Run with FDDA and 1-h SST
  • Correlates well with measured wind (r gt 0.9) in
    either run with FDDA
  • Non-FDDA run not as good (r lt 0.85)

15
New metricsVector average wind
  • Good correlation with max ozone from airborne
    measurements
  • r -0.91, r2 0.83
  • Run with FDDA and 1-h SST
  • Runs without 1-h SST about the same
  • Without FDDA results are much worse
  • Scalar speed correlation slightly worse(?) (r
    -0.88) but still better than net trajectory
    distance

16
Lagrangian plume comparisons
  • FLEXPART dispersion model with real emissions
  • Met fields from WRF (red) and ECMWF (blue)
  • SO2 measurements from NOAA aircraft (black)
  • WRF result has much better resolution and plume
    locations, even if averaged to same grid

17
Conclusions
  • ECMWF model used for initialization is already
    quite good, making it difficult to demonstrate
    improvement with high-resolution simulations
  • Traditional statistics (bias and std. dev.) dont
    crisply display differences between runs,
    although they generally indicate improvement with
    FDDA
  • Different sites show different results
  • Looking at distribution of errors is useful
  • Large errors in temperature (gt5K) occur when
    moist convection is present
  • New metric of sea breeze correspondence shows
    improvement at all 7 surface sites with FDDA
  • Net trajectory distance correlates better with
    ozone than total distance
  • Vector average wind correlates still better with
    ozone, scalar average wind speed almost as good
  • Average wind (vector or scalar) shows clearly
    that FDDA makes an important improvement under
    high-ozone conditions
  • Improvement above the surface is easy to
    demonstrate (eg. by comparison with wind profiler
    data)
  • Lagrangian plume model provides clear information
    about directly relevant performance of the model,
    but how to encapsulate?
  • Uncertainty analysis is needed
  • How good is good enough?
  • What if we know we have improved the model, but
    cant show that we have improved the results?

18
Thanks to
  • Bryan Lambeth, Texas Commission on Environmental
    Quality
  • NOAA P3 scientists
  • Richard Pyle and Vaisala, Inc. for funding
  • and many others

19
New metricsSea breeze frequency
  • How often does a sea breeze occur in the
    simulation or measurement?
  • Definition Northerly component gt1 m/s between
    0600 and 1200 UTC and southerly gt1 m/s after 1200
    UTC
  • FDDA or FDDA1hSST run closer to measurement at 4
    of 7 sites

Red is FDDA run Blue has FDDA, 1-h SST, and
reduced soil moisture Green has reduced soil
moisture only Black is surface site measurement
20
New metricsStagnation frequency
  • How often does stagnation occur in the simulation
    or measurement?
  • Definition Wind speed lt 1 m/s at any
    hour between 1500 and 2300 UTC
  • FDDA or FDDA1hSST run closer to measurement at 3
    of 7 sites

Red is FDDA run Blue has FDDA, 1-h SST, and
reduced soil moisture Green has reduced soil
moisture only Black is surface site measurement
21
New metricsStagnation frequency
  • How often does stagnation occur in the simulation
    AND measurement?
  • Definition Wind speed lt 1 m/s at any
    hour between 1500 and 2300 UTC
  • No clear improvement with FDDA or FDDA1hSST
  • Results not sensitive to threshold

Red is FDDA run Blue has FDDA, 1-h SST, and
reduced soil moisture Green has reduced soil
moisture only
22
New metricsSea breeze and stagnation
  • Other things we can learn from these metrics
  • Sea breeze correspondence is good at C45, closest
    to Bay and Gulf, with high frequency
  • Even better sea breeze correspondence at C81 with
    lowest frequency
  • C45 has the lowest stagnation frequency

Red is FDDA run Blue has FDDA, 1-h SST, and
reduced soil moisture Green has reduced soil
moisture only
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