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