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 1 Atmospheric Sciences Research Center, University at Albany, Albany, NY, USA 2 New York State Department of Environmental Conservation, Albany, NY, USA 3 Weather It Is, LTD, Efrat, Israel 4 NASA-Goddard Institute for Space Studies, New York, NY, USA 5 Forschungszentrum Jülich, Germany 6 Max Planck Institute for Meteorology, Hamburg, Germany 7 University at Alabama, Huntsville, AL, USA 8 Mailman 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 Setup Simulation period: 1988 –2005 Simulation period: 1988 –2005 Domain: Northeastern U.S. Domain: Northeastern U.S. Meteorology: MM5v3.7.2 Meteorology: MM5v3.7.2 Emissions: NEI1990, , OTC2002, OTC2009, processed by SMOKE Emissions: NEI1990, , OTC2002, OTC2009, processed by SMOKE Air Quality: CMAQv4.5.1, CB4, aero3 Air Quality: CMAQv4.5.1, CB4, aero3 Grid resolution 36 km / 12 km Grid resolution 36 km / 12 km Boundary Conditions for 36 km Grid: Boundary Conditions for 36 km Grid: Time-invariant default climatological vertical profiles (CMAQ/STATIC) Time-invariant default climatological vertical profiles (CMAQ/STATIC) Derived from ECHAM5-MOZART (CMAQ/ECHAM5-MOZART) Derived from ECHAM5-MOZART (CMAQ/ECHAM5-MOZART) 2

Domain-Total Anthropogenic NO x and VOC Emissions For the 1988 – 2005 CMAQ Simulations Substantial reductions in NO x emissions from power plants starting in 1995 Continuous reductions of NO x 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 hr DM th %ile 1-hr DM hr DM th %ile 1-hr DM hr DM

Spectra Calculated from 18 years of Hourly Observed and 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 CMAQ/STATIC 8-hr Daily Maximum Ozone Observations CMAQ/STATIC Percentiles of May – September 8-hr DM O 3 IAV is defined as (standard deviation) / mean IAV is calculated separately at each site for 5 th, 25 th, 50 th, 75 th, and 95 th percentiles of May – September 8-hr DM O 3 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 8-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

Time Series of 5 th, 50 th, and 95 th Summertime Percentiles Estimated From May – Sep 8-hr Daily Maximum Ozone, Calculated 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

Observed (top) and CMAQ/STATIC (bottom) Least-Squares Trends in the 95 th (left) and 5 th (right) Percentiles of May – September 8-hr Daily Maximum Ozone, Good agreement between linear trends estimated for the 95 th 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 5 th 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. Percentiles of May – September 8-hr Daily Maximum Ozone, 1988 – 2005 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

Impact of Chemical Lateral Boundary Conditions 12

13 Layer Midpoint Height (m) O 3 (ppb)NO (ppt)NO 2 (ppt)HNO 3 (ppt)PAN (ppt) StaticECHStaticECHStaticECHStaticECHStaticECH , , , , , , Comparison of Boundary Conditions for CMAQ/STATIC vs. CMAQ/ECHAM5-MOZART for Selected Species and Layers “Static”: Used for CMAQ/STATIC simulations “Static”: Used for CMAQ/STATIC simulations “ECH”: Used for CMAQ/ECHAM5-MOZART simulations, based on monthly average concentrations from archived 1960 – 2006 global ECHAM5- MOZART simulations performed as part of the RETRO project “ECH”: Used for CMAQ/ECHAM5-MOZART simulations, based on monthly average concentrations from archived 1960 – 2006 global ECHAM5- MOZART simulations performed as part of the RETRO project

Impact of Boundary Conditions On Average Daily Maximum 8-hr Ozone Concentrations As Function of Day-of-Year, Layer 1, 1988 – 2005 Average Observed 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

Differences in Monthly Average Daily Maximum Ozone Concentrations, CMAQ/ECHAM5-MOZART Minus CMAQ/STATIC, Layer 1, 1988 – 2005 Average 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 Profiles at Ozonesonde Sites Location of Ozonesonde Sites Data Coverage at Ozonesonde Sites

Observed and Simulated Vertical Profiles at Huntsville (left) and Wallops Island (right), Concentrations (top) and Standard Deviation (bottom)

The CMAQ/ECHAM5- MOZART simulations capture more interannual variability than the CMAQ/STATIC simulations Observations CMAQ/STATIC CMAQ/ECHAM5-MOZ 18 Impact of Boundary Conditions on CMAQ Interannual Variability Observed and Simulated IAV for , defined as (standard deviation) / mean

19 Ratio of CMAQ/Observed IAV by Percentiles; Median Across All O 3 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 Impact of Boundary Conditions on CMAQ Trend Estimates and Interannual Variability Linear Trends in Summertime 8-hr DM Ozone by Percentiles; Median Across All O 3 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

Summary  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 estimates 20