vistas meteorological modeling 2002 simulation may 25, 2004 national rpo modeling meeting
DESCRIPTION
VISTAS Meteorological Modeling 2002 Simulation May 25, 2004 National RPO Modeling Meeting Denver, CO George Bridgers North Carolina Division of Air Quality. Introduction. MM5 v3.6.1+ (Sea Ice Differences Only) MM5 v3.6.2 Preprocessors Reisner 1 w/ Mixed Ice Physics - PowerPoint PPT PresentationTRANSCRIPT
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VISTAS Meteorological VISTAS Meteorological ModelingModeling
2002 Simulation2002 Simulation
May 25, 2004May 25, 2004
National RPO Modeling MeetingNational RPO Modeling Meeting
Denver, CODenver, CO
George BridgersGeorge Bridgers
North Carolina Division of Air QualityNorth Carolina Division of Air Quality
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IntroductionIntroduction• MM5 v3.6.1+ (Sea Ice Differences Only)MM5 v3.6.1+ (Sea Ice Differences Only)
• MM5 v3.6.2 PreprocessorsMM5 v3.6.2 Preprocessors• Reisner 1 w/ Mixed Ice PhysicsReisner 1 w/ Mixed Ice Physics• Kain-Fritsch 2 Cumulus ParameterizationKain-Fritsch 2 Cumulus Parameterization• ACM Planetary Boundary Layer (PBL) ModelACM Planetary Boundary Layer (PBL) Model• Pleim-Xiu Land Surface Model LSM (EPA’s MPP Pleim-Xiu Land Surface Model LSM (EPA’s MPP
version)version)– independent segments (cold start)-no INTERPPXindependent segments (cold start)-no INTERPPX
INTERPPXINTERPPX is used to initialize soil moisture, canopy is used to initialize soil moisture, canopy moisture, and soil temperature from a previous run when moisture, and soil temperature from a previous run when simulation time periods overlap.simulation time periods overlap.
– Using INTERPPX resulted in a significant wintertime cold bias Using INTERPPX resulted in a significant wintertime cold bias in sensitivity testing.in sensitivity testing.
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Introduction (cont.)Introduction (cont.)
• MM5 executed in 5.5 day MM5 executed in 5.5 day segmentssegments
• 76 total segments76 total segments• 00Z Dec 17, 2001 start00Z Dec 17, 2001 start
• dec17_01 date tagdec17_01 date tag• 12Z Jan 1, 2003 finish12Z Jan 1, 2003 finish
• Last hour of dec27_02 segmentLast hour of dec27_02 segment
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Evaluation ProceduresEvaluation Procedures• Full suite of evaluation products Full suite of evaluation products
available for each segmentavailable for each segment• Surface ProductsSurface Products
SpatialSpatial Time seriesTime series CombinationCombination
• Aloft ProductsAloft Products SpatialSpatial SoundingSounding ProfilerProfiler
• Statistical ProductsStatistical Products Surface time seriesSurface time series Aloft time seriesAloft time series TablesTables
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Evaluation ProceduresEvaluation Procedures
• Need to Summarize ResultsNeed to Summarize Results• Monthly ProductsMonthly Products
• Statistical TablesStatistical Tables• Spatial Summary PlotsSpatial Summary Plots• ““Bakergrams” (annual)Bakergrams” (annual)• ““Bakergrams” (monthly)Bakergrams” (monthly)• Spatial Statistical PlotsSpatial Statistical Plots
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Statistical ChartsStatistical Charts
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1.5m Temperature (C) Bias
-0.9-0.8-0.7-0.6-0.5-0.4-0.3-0.2-0.1
00.1
Jan
Feb
Mar
ch
Apr
il
May
June
July
Aug
Sep
t
Oct
Nov
Dec
Month
Bia
s 12 km
36 km
Monthly VISTAS StatisticsMonthly VISTAS Statistics
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1.5m Tempe rature (C) Bias
-0.70
-0.60
-0.50
-0.40
-0.30
-0.20
-0.10
0.00
djf* m am jja son
Bia
s 12km
36km
Seasonal VISTAS StatisticsSeasonal VISTAS Statistics
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1.5m Temperature (C) Bias
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 36kmDay/Night VISTAS Statistics, 36km
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1.5m Temperature (C) Bias
-1.4-1.2
-1-0.8-0.6-0.4-0.2
00.20.40.6
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 12kmDay/Night VISTAS Statistics, 12km
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Qv (g/kg) Bias
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
Jan
Feb
Mar
ch
Apr
il
May
June
July
Aug
Sep
t
Oct
Nov
Dec
Month
Bia
s 12 km
36 km
Monthly VISTAS StatisticsMonthly VISTAS Statistics
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Qv (g/kg) Bias)
-0.60
-0.50
-0.40
-0.30
-0.20
-0.10
0.00
0.10
0.20
djf* mam jja son
Bia
s 12 km
36 km
Seasonal VISTAS StatisticsSeasonal VISTAS Statistics
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Qv (g/kg) Bias
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 36kmDay/Night VISTAS Statistics, 36km
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Qv (g/kg) Bias
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 12kmDay/Night VISTAS Statistics, 12km
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RH (%) Bias
-6-5-4-3-2-101234
Jan
Feb
Mar
ch
Apr
il
May
June
July
Aug
Sep
t
Oct
Nov
Dec
Month
Bia
s 12 km
36 km
Monthly VISTAS StatisticsMonthly VISTAS Statistics
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Rh (%) Bias
-4.00-3.50-3.00-2.50-2.00-1.50-1.00-0.500.000.501.00
djf* mam jja son
Bia
s 12 km
36 km
Seasonal VISTAS StatisticsSeasonal VISTAS Statistics
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RH (%) Bias
-15
-10
-5
0
5
10
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 36kmDay/Night VISTAS Statistics, 36km
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RH (%) Bias
-10
-5
0
5
10
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 12kmDay/Night VISTAS Statistics, 12km
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WS reg (m/s) Bias
00.1
0.20.3
0.40.5
0.60.7
Jan
Feb
Mar
ch
Apr
il
May
June
July
Aug
Sep
t
Oct
Nov
Dec
Month
Bia
s 12 km
36 km
Monthly VISTAS StatisticsMonthly VISTAS Statistics
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WS reg (m/s) Bias
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
djf* mam jja son
Bia
s 12 km
36 km
Seasonal VISTAS StatisticsSeasonal VISTAS Statistics
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WS reg (m/s) Bias
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 36kmDay/Night VISTAS Statistics, 36km
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WS reg (m/s) Bias
-0.20
0.20.4
0.60.8
11.2
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 12kmDay/Night VISTAS Statistics, 12km
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WS no calm (m/s) Bias
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
Jan
Feb
Mar
ch
Apr
il
May
June
July
Aug
Sep
t
Oct
Nov
Dec
Month
Bia
s 12 km
36 km
Monthly VISTAS StatisticsMonthly VISTAS Statistics
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WS no calm (m/s) Bias
-0.30
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
djf* mam jja son
Bia
s 12 km
36 km
Seasonal VISTAS StatisticsSeasonal VISTAS Statistics
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WS no calm (m/s) Bias
-0.7-0.6-0.5-0.4-0.3-0.2-0.1
00.10.20.3
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 36kmDay/Night VISTAS Statistics, 36km
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WS no calm (m/s) Bias
-0.4-0.3
-0.2-0.1
00.1
0.20.3
0.40.5
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 12kmDay/Night VISTAS Statistics, 12km
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WS minicalm (m/s) Bias
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
Jan
Feb
Mar
ch
Apr
il
May
June
July
Aug
Sep
t
Oct
Nov
Dec
Month
Bia
s 12 km
36 km
Monthly VISTAS StatisticsMonthly VISTAS Statistics
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WS minicalm (m/s) Bias
0.000.050.100.150.200.250.300.350.400.45
djf* mam jja son
Bia
s 12 km
36 km
Seasonal VISTAS StatisticsSeasonal VISTAS Statistics
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WS minicalm (m/s) Bias
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 36kmDay/Night VISTAS Statistics, 36km
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WS minicalm (m/s) Bias
-0.2
0
0.2
0.4
0.6
0.8
1
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 12kmDay/Night VISTAS Statistics, 12km
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CLD (%) Bias
-10-8
-6-4
-20
24
68
Jan
Feb
Mar
ch
Apr
il
May
June
July
Aug
Sep
t
Oct
Nov
Dec
Month
Bia
s 12 km
36 km
Monthly VISTAS StatisticsMonthly VISTAS Statistics
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CLD (%) Bias
-10.00
-8.00
-6.00
-4.00
-2.00
0.00
2.00
4.00
6.00
djf* mam jja son
Bia
s 12 km
36 km
Seasonal VISTAS StatisticsSeasonal VISTAS Statistics
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CLD (%) Bias
-20
-15
-10
-5
0
5
10
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 36kmDay/Night VISTAS Statistics, 36km
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CLD (%) Bias
-10
-5
0
5
10
15
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/Night VISTAS Statistics, 12kmDay/Night VISTAS Statistics, 12km
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CLD2 (%) Bias
-6-4-202468
101214
Jan
Feb
Mar
ch
Apr
il
May
June
July
Aug
Sep
t
Oct
Nov
Dec
Month
Bia
s 12 km
36 km
Monthly VISTAS StatisticsMonthly VISTAS Statistics
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CLD2 (%) Bias
-4.00
-2.00
0.00
2.00
4.00
6.00
8.00
10.00
12.00
djf* mam jja son
Bia
s 12 km
36 km
Seasonal VISTAS StatisticsSeasonal VISTAS Statistics
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CLD2 (%) Bias
-15
-10
-5
0
5
10
15
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/night VISTAS Statistics, 36kmDay/night VISTAS Statistics, 36km
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CLD2 (%) Bias
-10
-5
0
5
10
15
20
25
Janu
ary
Feb
ruar
y
Mar
ch
Apr
il
May
June
July
Aug
ust
Sep
tem
ber
Oct
ober
Nov
embe
r
Dec
embe
r
Month
Bia
s day
night
Day/night VISTAS Statistics, 12kmDay/night VISTAS Statistics, 12km
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Monthly VISTAS StatisticsMonthly VISTAS Statistics
WDIR dbias
-1
0
1
2
3
4
5
Jan
Feb
Mar
ch
Apr
il
May
June
July
Aug
Sep
t
Oct
Nov
Dec
Month
dB
ias 12 km
36 km
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WDIR dbias
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
djf* mam jja son
dB
ias 12 km
36 km
Seasonal VISTAS StatisticsSeasonal VISTAS Statistics
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Annual BakergramsAnnual Bakergrams
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Monthly BakergramsMonthly Bakergrams
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Spatial PlotsSpatial Plots
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Performance SummaryPerformance Summary
• Modeling Results Are as ExpectedModeling Results Are as Expected• Cold Bias in WinterCold Bias in Winter
• Soil initialization procedure needs Soil initialization procedure needs improvement (beyond scope of project)improvement (beyond scope of project)
• 10-day soil time scale too long?10-day soil time scale too long?• Precip amounts in summer overdone in SE USPrecip amounts in summer overdone in SE US• Best performance in VISTAS region for most Best performance in VISTAS region for most
variables… variables… • Performance is quite good compared with Performance is quite good compared with
other modeling exercisesother modeling exercises• Characteristics of the 36km and 12km Characteristics of the 36km and 12km
domains are generally similar, but interesting domains are generally similar, but interesting differencesdifferences
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What’s Next What’s Next For VISTAS’ Meteorological For VISTAS’ Meteorological
TeamTeam• Survey VISTAS states regarding:Survey VISTAS states regarding:
• Performance zones evaluationPerformance zones evaluation• What are other RPO’s doing?What are other RPO’s doing?• Awaiting results of CART analysisAwaiting results of CART analysis
• State by State (VISTAS) evaluation State by State (VISTAS) evaluation • To support PM2.5 SIP workTo support PM2.5 SIP work
• Formatting files for CALMET/CALPUFFFormatting files for CALMET/CALPUFF• To support state permit modelingTo support state permit modeling
• Transfers available… Want it? Need 1.2 TB Transfers available… Want it? Need 1.2 TB storagestorage
• 2003 episodic modeling ?2003 episodic modeling ?• Episodes could be identified by CART analysisEpisodes could be identified by CART analysis
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Contact InformationContact Information
• http://vistas-sesarm.org/http://vistas-sesarm.org/• http://www.baronams.com/projects/http://www.baronams.com/projects/
VISTAS/VISTAS/
[email protected]@ncmail.net
919-715-3743919-715-3743
[email protected]@ncmail.net
919-715-6287 919-715-6287
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Mammoth CaveMammoth CaveTime SeriesTime Series
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ShenandoahShenandoahTime SeriesTime Series
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