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A Comparison of Observed and Simulated Long-Term Ozone Fluctuations and Trends Over the Northeastern United States. C. Hogrefe 1,2 , W. Hao 2 , E.E. Zalewsky 2 , J.-Y. Ku 2 , B. Lynn 3 , C. Rosenzweig 4 , M. Schultz 5 , S. Rast 6 , M. Newchurch 7 , L. Wang 7 , P.L. Kinney 8 , and G. Sistla 2 - PowerPoint PPT Presentation
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C. HogrefeC. Hogrefe1,21,2, W. Hao, W. Hao22, E.E. Zalewsky, E.E. Zalewsky22, J.-Y. Ku, J.-Y. Ku22, B. Lynn, B. Lynn33,,C. RosenzweigC. Rosenzweig44, M. Schultz, M. Schultz55, S. Rast, S. Rast66, M. Newchurch, M. Newchurch77, ,
L. WangL. Wang77, P.L. Kinney, P.L. Kinney88, and G. Sistla, and G. Sistla22
1Atmospheric Sciences Research Center, University at Albany, Albany, NY, USA
2New York State Department of Environmental Conservation, Albany, NY, USA3Weather It Is, LTD, Efrat, Israel
4NASA-Goddard Institute for Space Studies, New York, NY, USA5Forschungszentrum Jülich, Germany
6Max Planck Institute for Meteorology, Hamburg, Germany7University at Alabama, Huntsville, AL, USA
8Mailman School of Public Health, Columbia University, New York, NY, USA
CMAS Conference, Chapel Hill, NC, October 19-21, 2009
A Comparison of Observed and Simulated Long-Term Ozone
Fluctuations and Trends Over the Northeastern United States
Modeling System SetupModeling System Setup Simulation period: 1988 –2005Simulation period: 1988 –2005 Domain: Northeastern U.S.Domain: Northeastern U.S. Meteorology: MM5v3.7.2Meteorology: MM5v3.7.2 Emissions: NEI1990, 1996-2001, Emissions: NEI1990, 1996-2001,
OTC2002, OTC2009, processed by OTC2002, OTC2009, processed by SMOKESMOKE
Air Quality: CMAQv4.5.1, CB4, aero3Air Quality: CMAQv4.5.1, CB4, aero3 Grid resolution 36 km / 12 kmGrid resolution 36 km / 12 km Boundary Conditions for 36 km Boundary Conditions for 36 km
Grid:Grid: Time-invariant default Time-invariant default
climatological vertical profiles climatological vertical profiles (CMAQ/STATIC)(CMAQ/STATIC)
Derived from ECHAM5-MOZART Derived from ECHAM5-MOZART (CMAQ/ECHAM5-MOZART)(CMAQ/ECHAM5-MOZART)
2
Domain-Total Anthropogenic NODomain-Total Anthropogenic NOxx and VOC and VOC Emissions For the 1988 – 2005 CMAQ SimulationsEmissions For the 1988 – 2005 CMAQ Simulations
• Substantial reductions in NOx emissions from power plants starting in 1995
• Continuous reductions of NOx and VOC emissions, to a large extent driven by mobile source reductions 3
Observed and CMAQ/STATIC Simulated Ozone Variability and Trends
4
Overall Model Performance
Mean Observed
(ppb)
Mean CMAQ (ppb)
Bias (ppb)
RMSE (ppb)
Normalized Bias (%)
Normalized Error (%)
Correlation Coefficient
All Days May-Sep
1-hr DM
59.6 61.5 1.9 15.2 3.2 19.5 0.72
8-hr DM
51.4 55.9 4.5 14.5 8.9 22.0 0.70
95th %ile
1-hr DM
94.6 90.2 -4.4 9.8 -4.7 8.5 0.76
8-hr DM
82.4 81.1 -1.3 7.8 -1.6 7.7 0.75
5th %ile
1-hr DM
28.5 38.5 10.0 11.4 35.8 37.1 0.19
8-hr DM
22.7 34.9 12.3 13.4 55.8 56.8 0.16
Spectra Calculated from 18 years of Hourly Observed Spectra Calculated from 18 years of Hourly Observed and CMAQ Ozone Time Seriesand CMAQ Ozone Time Series
CMAQ/STATIC appears to capture the variability in the diurnal and synoptic bands
CMAQ/STATIC underestimates variability in the high-frequency (intra-day) and low-frequency (seasonal and longterm) bands of the spectrum
6
Inter-Annual Variability (IAV) of Observed and Inter-Annual Variability (IAV) of Observed and CMAQ/STATIC 8-hr Daily Maximum OzoneCMAQ/STATIC 8-hr Daily Maximum Ozone
Observations CMAQ/STATIC
Percentiles of May – September 8-hr DM O3
• IAV is defined as (standard deviation) / mean
• IAV is calculated separately at each site for 5th, 25th, 50th, 75th, and 95th percentiles of May – September 8-hr DM O3
• The box plots show the distribution of IAV for a given percentile across all sites
• CMAQ/STATIC IAV is lower than observed IAV for all percentiles
7
Ratio of CMAQ/Observed Inter-Annual Variability (IAV) of Ratio of CMAQ/Observed Inter-Annual Variability (IAV) of 8-hr Daily Maximum Ozone8-hr Daily Maximum Ozone
The Median IAV Ratio Across All Sites is Shown for Each Percentile
CMAQ/STATIC IAV is lower than observed IAV for all percentiles, the underestimation is more pronounced for lower percentiles
8
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50 60 70 80 90
Percentile
Ra
tio
Mo
de
led
/Ob
se
rve
d IA
V
CMAQ/STATIC
Time Series of 5Time Series of 5thth, 50, 50thth, and 95, and 95thth Summertime Percentiles Summertime Percentiles Estimated From May – Sep 8-hr Daily Maximum Ozone, 1988 - Estimated From May – Sep 8-hr Daily Maximum Ozone, 1988 -
20052005Calculated for Domain-Wide Ozone Averaged Over All
Monitors
CMAQ/STATIC appears to capture the trend in the upper range of the ozone distribution rather well, but less so the mid and lower range
9
0
20
40
60
80
100
120
Observed 95th
CMAQ/STATIC 95th
Observed 50th
CMAQ/STATIC 50th
Observed 5th
CMAQ/STATIC 5th
Observed (top) and CMAQ/STATIC (bottom) Least-Squares Trends in the Observed (top) and CMAQ/STATIC (bottom) Least-Squares Trends in the 9595thth (left) and (left) and 55thth (right) Percentiles of May – September 8-hr Daily Maximum (right) Percentiles of May – September 8-hr Daily Maximum
Ozone, 1988 - 2005Ozone, 1988 - 2005
Good agreement between linear trends estimated for the 95th Percentile of observed and CMAQ summertime 8-hr DM ozone concentrations
10
Observations
CMAQ/STATIC
While the observed trends at almost all stations are upward for the 5th percentiles of summertime 8-hr DM ozone concentrations, CMAQ shows a mixture of upward and downward trends
Observations
CMAQ/STATIC
Observed and CMAQ/STATIC Least-Squares Trends (y-axis) vs. Observed and CMAQ/STATIC Least-Squares Trends (y-axis) vs. Percentiles of May – September 8-hr Daily Maximum Ozone, 1988 – Percentiles of May – September 8-hr Daily Maximum Ozone, 1988 –
20052005
Trends Were Calculated At Each Site, the Median Across All Sites is Shown Here The agreement
between the linear trends estimated from observations and CMAQ/STATIC is better for upper than lower percentiles
While typical observed trends at stations in the modeling domain tend to be upward for percentiles < 40 and downward for higher percentiles, CMAQ/STATIC trends tend to be downward at all percentiles
11
-1.4
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0 10 20 30 40 50 60 70 80 90
Percentiles
Ozo
ne
Tre
nd
(%
/yr)
Observations
CMAQ/STATIC
Impact of Chemical Lateral Boundary Conditions
12
13
Layer Midpoint Height (m)
O3 (ppb) NO (ppt) NO2 (ppt) HNO3 (ppt) PAN (ppt)
Static ECH Static ECH Static ECH Static ECH Static ECH
1 18 32 49 44 153 89 1,907 148 904 68 664
8 560 38 55 38 45 76 513 148 875 62 543
10 1,403 45 57 22 17 44 177 148 802 48 434
12 3,855 56 63 4 7 8 40 114 259 25 320
13 6,139 62 69 0 8 0 31 96 180 14 308
14 9,480 69 69 0 8 0 31 120 180 11 308
15 13,004 70 69 0 8 0 31 125 180 11 308
Comparison of Boundary Conditions for CMAQ/STATIC vs. Comparison of Boundary Conditions for CMAQ/STATIC vs. CMAQ/ECHAM5-MOZART for Selected Species and LayersCMAQ/ECHAM5-MOZART for Selected Species and Layers
““Static”: Used for CMAQ/STATIC simulationsStatic”: Used for CMAQ/STATIC simulations
““ECH”: Used for CMAQ/ECHAM5-MOZART simulations, based on ECH”: Used for CMAQ/ECHAM5-MOZART simulations, based on monthly average concentrations from archived 1960 – 2006 monthly average concentrations from archived 1960 – 2006 global ECHAM5-MOZART simulations performed as part of the global ECHAM5-MOZART simulations performed as part of the RETRO projectRETRO project
Impact of Boundary Conditions On Average Daily Impact of Boundary Conditions On Average Daily Maximum 8-hr Ozone Concentrations As Function Maximum 8-hr Ozone Concentrations As Function
of Day-of-Year, Layer 1, 1988 – 2005 Averageof Day-of-Year, Layer 1, 1988 – 2005 AverageObserved and Simulated
Average Daily Maximum 8-hr Ozone Concentrations, Averaged Over All Sites
Average Daily Maximum 8-hr Ozone Concentrations, CMAQ/ECHAM5-MOZART Minus CMAQ/STATIC,
Averaged Over All Sites
CMAQ/ECHAM5-MOZART generally yields higher concentrations, the differences can be as large as 12 ppb averaged over all sites
14
0
10
20
30
40
50
60
70
80
90
1 17 33 49 65 81 97 113
129
145
161
177
193
209
225
241
257
273
289
305
321
337
353
Day of Y ear
Dai
ly M
axim
um 8
-hr
Ozo
ne C
once
ntra
tion
(ppb
)
O bs ervations
C MAQ/S T AT IC
C MAQ/E C HAM5-MO Z AR T
0
2
4
6
8
10
12
14
1 9 17 25 33 41 49 57 65 73 81 89 97 105
113
121
129
137
145
153
161
169
177
185
193
201
209
217
225
233
241
249
257
265
273
281
289
297
305
313
321
329
337
345
353
361
Day of Y ear
Diff
eren
ce in
8-h
r D
aily
Max
imum
Ozo
ne
(ppb
)
Differences in Monthly Average Daily Maximum Differences in Monthly Average Daily Maximum Ozone Concentrations, CMAQ/ECHAM5-MOZART Ozone Concentrations, CMAQ/ECHAM5-MOZART
Minus CMAQ/STATIC, Layer 1, 1988 – 2005 Minus CMAQ/STATIC, Layer 1, 1988 – 2005 AverageAverage
The impact of different boundary conditions on monthly average daily maximum ozone decreases towards the interior of the domain, but still reaches 3-9 ppb in July for the regions typically exhibiting the highest observed ozone concentrations
15
16
Comparison of Observed and Simulated Vertical Comparison of Observed and Simulated Vertical Profiles at Ozonesonde SitesProfiles at Ozonesonde Sites
Location of Ozonesonde Sites 1988-2005 Data Coverage at Ozonesonde Sites
Observed and Simulated Vertical Profiles at Observed and Simulated Vertical Profiles at Huntsville (left) and Wallops Island (right), Huntsville (left) and Wallops Island (right),
Concentrations (top) and Standard Deviation Concentrations (top) and Standard Deviation (bottom)(bottom)
0
1000
2000
3000
4000
5000
6000
7000
0 20 40 60 80
Ozone C onc entration (ppb)
Hei
ght A
bove
Gro
und
(m)
O bservations
C MAQ/S T AT IC
C MAQ/E C HAM5-MO Z AR T
0
1000
2000
3000
4000
5000
6000
7000
0 10 20 30 40 50 60 70
Ozone C onc entration (ppb)
Hei
ght A
bove
Gro
und
(m)
O bservations
C MAQ/S T AT IC
C MAQ/E C HAM5-MO Z AR T
0
1000
2000
3000
4000
5000
6000
7000
0 5 10 15 20 25
Ozone S tandard Deviation (ppb)
Hei
ght A
bove
Gro
und
(m)
O bservations
C MAQ/S T AT IC
C MAQ/E C HAM5-MO Z AR T
0
1000
2000
3000
4000
5000
6000
7000
0 5 10 15 20 25
Ozone S tandard Deviation (ppb)
Hei
ght A
bove
Gro
und
(m)
O bservations
C MAQ/S T AT IC
C MAQ/E C HAM5-MO Z AR T
• The CMAQ/ECHAM5-MOZART simulations capture more interannual variability than the CMAQ/STATIC simulations
ObservationsCMAQ/STATICCMAQ/ECHAM5-MOZ
18
Impact of Boundary Conditions on CMAQ Interannual VariabilityImpact of Boundary Conditions on CMAQ Interannual Variability
Observed and Simulated IAV for 1988-2005, defined as (standard deviation) / mean
19
Ratio of CMAQ/Observed IAV by Percentiles; Median Across All
O3 sites in domain, 8-hr DM
Both simulations underestimate observed IAV (ratios < 1), but deriving boundary conditions from ECHAM5-MOZART significantly improves the representation of IAV for mid and low percentiles
-1.6
-1.4
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0 10 20 30 40 50 60 70 80 90
PercentilesO
zon
e T
ren
d (
%/y
r)
Observations
CMAQ/STATIC
CMAQ/ECHAM5-MOZART
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50 60 70 80 90
Percentile
Ra
tio
Mo
de
led
/Ob
se
rve
d IA
V
CMAQ/STATIC
CMAQ/ECHAM5-MOZART
Impact of Boundary Conditions on CMAQ Trend Estimates and Impact of Boundary Conditions on CMAQ Trend Estimates and Interannual VariabilityInterannual Variability
Linear Trends in 1988-2005 Summertime 8-hr DM Ozone by Percentiles; Median Across All
O3 sites in domain
•The choice of boundary conditions strongly influences the CMAQ trend estimates
•CMAQ/ECHAM5-MOZART shows a stronger downward trend than either CMAQ/STATIC or observations
SummarySummary The 1988 – 2005 CMAQ simulations with boundary
conditions derived from the time-invariant default climatological vertical profile exhibit the following features: An underestimation of interannual variability by 30% - 50%
depending on the percentiles of the distribution A tendency to capture the trends at the high end of the ozone
distribution but not for the central and lower portions
The 1988 – 2005 CMAQ simulations with boundary conditions derived from ECHAM5-MOZART show: Significant differences in mean ozone concentrations in all seasons
throughout the domain, both at the surface and aloft
Improved representation of interannual variability
Possible propagation of model biases from global to regional scale, especially for lower percentiles of the ozone distribution
A strong impact of boundary conditions on trend estimates20