CORRECTABLE BC-ERRORS WITHIN MESO-MET MODELS

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CORRECTABLE BC-ERRORS WITHIN MESO-MET MODELS

• R. Bornstein
• San Jose State University
• San Jose, CA
• pblmodel_at_hotmail.com
• Presented at
• 86th AMS Annual Meeting, Atlanta, GA
• 30 January 2006

2
Acknowledgements

• H. Taha, Altostratus SJSU
• D. Hitchock P. Smith, State of Texas
• D. Byun, U. of Houston
• J. Ching S. Dupont, US EPA
• S. Stetson, SWS Inc.
• S. Burian, U. of Utah
• D. Nowak, USFS
• Funded by NSF, USAID, DHS, LBL, LMMS, NASA
• MY M.S. (ex) STUDENTS J. Cheng, C. Lozej, F.
  Freedman, T. Ghidey, K. Craig, S. Kasakseh, R.
  Balmori

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OUTLINE

• INTRODUCTION
• SYNOPTIC FORCING
• POORLY (AT BEST) KNOWN INPUT DATA
• DEEP SOIL TEMP IC/C
• SOIL MOISTURE IC
• SST IC/BC
• SFC/PBL FORCING
• NON-URBAN
• URBAN
• CONCLUSION

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Theme of TalkMESO-MET ATM-MODELS MUST CAPTURE
B.C. FORCINGS IN CORRECT ORDER (1 of 2)

• e.g., AN O3 EPISODES OCCURS ON A GIVEN DAY
• NOT FROM CHANGING TOPOGRAPHY EMISSIONS
• BUT DUE TO CHANGING (UPPER-LEVEL /OR SFC)
• GC/SYNOPTIC PRESSURE-PATTERNS, WHICH
• ENTER OUR MESO-SOLUTIONS FROM EITHER CORRECT OR
  IMPRECISE LARGER-SCALE MODEL-VALUES WHICH
• THUS ALLOW SCF MESO THERMAL-FORCINGS (i.e.,
  UP/DOWN SLOPE, LAND/SEA, URBAN, CLOUDS/FOG) TO
  DEVELOP CORRECTLY OR INCORRECTLY

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CORRECT ORDER (2 of 2)

• MUST THUS CORRECTLY REPRODUCE
• UPPER-LEVEL Syn/GC FORCING FIRST
• pressure (the GC/Syn driver), which
  produces Syn/GC winds
• TOPOGRAPHY NEXT
• grid spacing ? flow-channeling
• MESO SFC-CONDITIONS LAST
• temp (the meso-driver) sfc roughness ?
  Meso-winds

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Correct GC/Synoptic forcing

• Methodology
• Check large-scale forcing before simulations
• NWS charts vs. large-scale model input-fields
• If correct ? use analysis-nudging FDDA ?
• correct synoptic-trends
• Case studies
• SFBA Winter synoptic-storm (Lozej 1996)
• Atlanta urban-thunderstorm (Craig 2000)
• Ozone-episodes
• LA (Boucouvala et al. 2003)
• SFBA (Ghidey 2005)

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1996 SFBA Winter-Storm (Lozej)

• Obs storm went over SFBA
• Wrong input large-scale IC/BC caused storm to
• move too zonally and thus too fast
• pass (and precipitate) too far north
• Note IC/BC more important for synoptic storms
  than for meso-systems (they are driven by
  surface-conditions)
• Obs and MM5 next 3 slides

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SFBA
SFBA
GOES IR SFC NWS 12 March, 12 UTC Storm over
SFBA
9
11 March
L
12 March
L

• NCEP(2.50)/MM5 (27 km) (solid blue) ETA (dash
  pink)
• 500 mb heights (dam) at 12 UTC
• Left slight IC/BC errors in NCEP
• ETA digs deeper vs
• NCEP/MM5 more zonal
• Right storm goes too far N of SFBA moves too
  quickly

10
MM5 (upper) 3 hr precip max is thus N of
observed precip (lower) max (at 50-km S of
SFBA)
SFBA
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Atlanta Summer Thunderstorm (Craig)

• Obs weak-cold front N of Atlanta
• Large-scale IC/BC front S of city
• MM5 UHI-induced thunderstorm 5-km deep,
  wmax 6-m/s, 8-cm precip
• Should be 9-km, 12-m/s, 14-cm
• Source of problem
• MM5-storm formed in stable-flow from N not in
  unstable-flow from S
• Data MM5 results next slide

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ATLANTA UHI-INITIATED STORM OBS SAT PRECIP
(UPPER) MM5 W PRECIP (LOWER)
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LA Summer O3-episode (Boucouvula)

• Obs of large scale IC/BC
• Shift of meso-700 hPa high ?
• upper-level flow from N ?
• NW-moving sea-breeze max-O3
• was blocked by sfc-flow from N
• stayed in San Fernando Valley
• MM5 analysis nudging ?
• got front and O3 right (next slide)

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Lower no analysis nudging ? MM5 sea-breeze
front O3-max not blocked from pass-ing to North
b/t 2 Mts, as N-S opposing large-scale flow is
weak
Mt
Mt
Upper analysis nudging ? MM5 sea-breeze front
(blue line) O3-max blocked from passing to-N
b/t 2 Mts by strong opposing N-S large-scale flow
(as in obs)
Mt
Mt
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SFBA Summer O3-episode (Ghidey)

• Obs daily max- O3 sequentially moved from
  Livermore to Sacramento to SJV
• Large scale IC/BC
• Shifting meos-700 hPa high ?
• shifting meos-sfc low ?
• changing sfc-flow ?
• max-O3 changed location
• MM5 (next 2 slides)
• good analysis-nudging ? good sfc-wind

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SAC episode day D-1 700 hPa Syn H moved to Utah
with coastal bulge L in S-Cal? correct SW
flow from SFBA to Sac
H
H
L
17
SJV episode day D-3 700 hPa Fresno eddy moved N
H moves inland? flow around eddy blocks SFBA
flow to SAC, but forces it S into SJV
L
H
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Topographic-Channeling (J. Cheng)

• Horiz grid-spacing too-large ?
• Mt-passes not resolved ?
• flow-direction is wrong
• Mt-passes are too wide ?
• speeds underestimated
• Solution
• decrease-spacing until wmax is unchanged
• Case study (not shown)
• SFBA Richmond toxic-spill

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MM5 Non-urban Sfc-IC/BC Issues

• Deep-soil temp BC
• Controls min-T
• Values unknown MM5-estimation is flawed
• Soil-moisture IC
• Controls max-T
• Values unknown MM5-table values too specific
• SST IC/BC
• Horiz coastal T-grad controls sea-breeze flow
• We usually focus only on land-sfc temp
• IC/BC SST values from large-scale model?
• too coarse not f(t)

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Summary for MM5 deep soil temp

• Calculated as average large-scale model input
  surface-T during simulation-period
• This assumes a zero time-lag b/t sfc and
  lower-level (about 1 m) soil-temps
• But obs show
• 2-3 month time-lag b/t these 2 temps
• Larger-lag in low-conductivity dry-soils
• Thus MM5 min-temps will always be too-high in
  summer and too-low in winter
• We need to develop tech (beyond current trial and
  error) to account for lag next 2 slides

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Mid-east Obs vs. MM5 2 m temp (Kasakech 06 AMS)
First 2 days show GC/Syn trend not in MM5, as
MM5-runs had no analysis nudging
Obs
Run 1
Run 4 Reduced Seep-soil T
July 29
August 1
August 2
obs
MM5Run 4
July 31
Aug 1
Aug2
Standard-MM5 summer night-time min-T, But lower
input deep-soil temp ? better 2-m T results ?
better winds ? better O3
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SCOS96 LA Temps (Boucouvual et al.)

• RUN 1 has
• No GC warming trend
• Wrong max and min T

RUN 5 corrected, as it used gt Analysis nudging
gt Reduced deep-soil T
3-Aug
4-Aug
5-Aug
6-Aug
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MM5 input-table values z0 problems

• Water z0 0.01 cm
• Only IC ? updated internally by eq f(MM5 u)
• But Eq only valid for open-sea smooth-swell
  conditions
• Observed values for rough-sea coastal-areas 1
  cm ?
• MM5 coastal-winds are over-estimated
• Urban z0 80 cm
• too low for tall cities obs up to 3-4 m
• Urban-winds too fast
• Must adjust input value or input GIS/RS f(x,y)
• See next 2 slides

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Vegetation Integer Identification Vegetation Description Albedo() Albedo() Moisture Avail. () Moisture Avail. () Emissivity ( at 9 µ m) Emissivity ( at 9 µ m) Roughness Length (cm) Roughness Length (cm) Thermal Inertia (cal cm-2 k-1 s-1/2) Thermal Inertia (cal cm-2 k-1 s-1/2)
Vegetation Integer Identification Vegetation Description Sum Win Sum Win Sum Win Sum Win Sum Win
1 Urban 15 15 10 10 88 88 80 80 0.03 0.03
2 Drylnd Crop. Past. 17 23 30 60 98.5 92 15 5 0.04 0.04
3 Irrg. Crop. Past. 18 23 50 50 98.5 92 15 5 0.04 0.04
4 Mix. Dry/Irrg.C.P. 18 23 25 50 98.5 92 15 5 0.04 0.04
5 Crop./Grs. Mosaic 18 23 25 40 99 92 14 5 0.04 0.04
6 Crop./Wood Mosc 16 20 35 60 98.5 93 20 20 0.04 0.04
7 Grassland 19 23 15 30 98.5 92 12 10 0.03 0.04
8 Shrubland 22 25 10 20 88 88 10 10 0.03 0.04
9 Mix Shrb./Grs. 20 24 15 25 90 90 11 10 0.03 0.04
10 Savanna 20 20 15 15 92 92 15 15 0.03 0.03
11 Decids. Broadlf. 16 17 30 60 93 93 50 50 0.04 0.05
12 Decids. Needlf. 14 15 30 60 94 93 50 50 0.04 0.05
13 Evergrn. Braodlf. 12 12 50 50 95 95 50 50 0.05 0.05
14 Evergrn. Needlf. 12 12 30 60 95 95 50 50 0.04 0.05
15 Mixed Forest 13 14 30 60 94 94 50 50 0.04 0.06
16 Water Bodies 8 8 100 100 98 98 .01 .01 0.06 0.06
17 Herb. Wetland 14 14 60 75 95 95 20 20 0.06 0.06
18 Wooded wetland 14 14 35 70 95 95 40 40 0.05 0.06
19 Bar. Sparse Veg. 25 25 2 5 85 85 10 10 0.02 0.02
20 Herb. Tundra 15 60 50 90 92 92 10 10 0.05 0.05
21 Wooden Tundra 15 50 50 90 93 93 30 30 0.05 0.05
22 Mixed Tundra 15 55 50 90 92 92 15 15 0.05 0.05
23 Bare Grnd. Tundra 25 70 2 95 85 95 10 5 0.02 0.05
24 Snow or Ice 55 70 95 95 95 95 5 5 0.05 0.05
25 No data                    
25-MM5 category (USGS) vegetation categories and
physical parameters
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S. Stetson Houston GIS/RS zo input
Values up 3 m
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Importance of detailed SST as f(x,y,t)

• Theory
• Along-shore winds ?
• off-shore Ekman ocean-transport ?
• cold-water upwelling ?
• atm ocean cold-core Lows ?
• altered atm pollutant-transport
• Need detailed satellite SST-input
• Case studies see next 4 slides
• Houston (Balmori, 2006 AMS)
• NYC (Pullen et al., 2006 AMS)

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Houston MM5 2-m Temps at 4 PM cold-core L from
SST-eddy?
L
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MM5 2-m cold-core L (in 3 domains)?along-shore
coastal-V ? Houston ozone-episode
L
D-1
D-2
L
D-3
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NYC SST currents Pullen et al. (2006 AMS)
L
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Satellite SST Over Gulf of Mx lots of
detailshttp//www7333.nrlssc.navy.mil/
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Model-Urbanization Techniques

• 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. (2006b) in
  uMM5
• Detailed input urban-parameters as f(x,y)
• Next 2 slides

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Urbanized meso-met model TKE (z)
hc building top
max urban effect
_________________
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1 km uMM5 Houston UHI 8 PM, 21 Aug

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

LU/LC error
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Summary of how to obtain good meso-met model
results

• 1st capture trends in large-scale forcing via
• validated large-scale model input
• analysis nudging
• Then simulate correct meso sfc-T via correct
• IC/BC deep soil-T (for min-T)
• IC soil-moisture (for max-T)
• Get good SSTs (from obs or ocean-models) for good
  sea-breeze flows
• Use good urbanizations (scheme inputs) for good
  temps, turbulence, winds

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Overall Lessons

• Models cant be assumed to be
• perfect
• black boxes
• If obs not available, it is OK to make reasonable
  educated estimates, e.g., for
• Deep-soil temp
• Soil moisture
• Need data for comparisons with simulated fields
• Need good urbanization, e.g., uMM5
• Need to develop better PBL parameterizations

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Any questions?