1. Thoughts on the Summer 2004 Experiments UI/CGRER Focus: Improving Forecasting and Analysis through Closer Integration of Observations and Models Flight Planning Air Quality Quick- look Post- Mission Test: Our ability to forecast 4-dimensional distributions of ozone and PM The utility of forecasts of ozone, fine particles in flight planning and quick-look analysis The utility of why-cast products (e.g., O 3 -production, VOC vs NO x limited regions, influence functions, hydrocarbon reactivity….) in flight planning and analysis and air quality forecasting Our ability to assimilate surface chemical observations into the forecasts; the impact of assimilation on the forecasts (for a sub-region; e.g., the NE) Targeted measurements that explore the concept of aircraft as “mobile super- sites” Forecasting Analysis

2. Fine Chloride Fine Sulfate Total Extinction Fine Nitrate We Plan to Forecast Size + Chemically Resolved Aerosol Products STEM simulations with on-line SCAPE compared to measurements of ACE-ASIA C-130 Flight 6 Observations from PILS (Weber)

3. Impact of aerosols on photochemistry [Clarke] [Avery]

4. A Scenario during TRACE-P Is value-added by forecasts of additional species? CO NOx O3

5. STEM Forecast for ITCT2K2 The locations with maximum O 3 and CO may not be the same

6. Predicted sensitivity of O 3 to VOCs and NO x VOC-limited NO x -limited

7. Influence functions (over Cheju for O 3 concentrations at 0:0:00 UT, 3/07/01) wrt O 3, NO 2, HCHO at -48, -24, -12 hr

8. Combining Back Trajectory and CMB Analysis to Estimate Contributions to Fossil, Biofuel and Open Biomass Burning to Airmasses 2-D and 3-D analysis features for DC8 flight8 (March 9th) Left: same as previous figure, but (light blue: 3.4GMT, purple: 3.3GMT, red: 2.5GMT); Right: same as uppermost figure. Fly by animation

9. MOZART in ITCT 2K2 Forecast mode –Driven by NCEP AVN analysis + forecast –Run at NCAR once daily, output every 6 hours –Full gas-phase O 3 chemistry, “regional tracers” Analysis mode –Run after campaign, AVN analysis, higher res. –O 3 chemistry + tagged regional CO –Output every 3 hours

10. Lessons from ITCT 2K2 Importance of using timely met. forecasts Comparison of chemical transport model forecasts Identification of met. features associated with pollution / long-range transport

11. Examples from ITCT 2K2 May 05 Flight –Large long-range transport (LRT) event (CO) May 10 Flight –Stratospheric intrusion (O 3 )

12. May 05 Flight, CO (ppbv)

14. May 10 Flight, Ozone (ppbv)

16. MOZART for ITCT 2K4 Aerosol simulation –Sulfate, nitrate, ammonium, black carbon, organic carbon now included –Mineral dust, sea salt being added Full O 3 photochemistry plus tagged CO species Run at ~2 deg resolution [driven by NCEP GFS ~ 0.5 deg] Run forecasts 4 times per day out to 84 hours Output every 3 hours Automated plots of forecast results posted to web site Couple with regional model (STEM)

17. Issues for ITCT 2K4 (vs. 2K2) Long-range transport (LRT) less important –Should be “easier” for models –But, less lead time Emission inventories should be more reliable More emphasis on aerosols –Washout parameterization –Test understanding of organic aerosols Nighttime chemistry

18. Science Questions for ITCT 2K4 Transport –What other U.S. source regions impact pollutant levels in New England? –What are the major export pathways during summer? –Are these pathways well-simulated in models? Chemical transformations –Can we simulate the chemical evolution of air masses from source regions to the North Atlantic? (e.g., O 3 production, NO y partitioning) Aerosols –What is the composition of aerosols transported from North America to the North Atlantic? –Are aerosol aging and removal processes well-simulated in models? –What are the main sources of organic aerosols?

20. Development of a General Computational Framework for the Optimal Integration of Atmospheric Chemical Transport Models and Measurements Using Adjoints (NSF ITR/AP&IM 0205198 – Started Fall 2002) A collaboration between: Greg Carmichael (Dept. of Chem. Eng., U. Iowa) Adrian Sandu (Dept. of Comp. Sci., Mich. Inst. Tech.) John Seinfeld (Dept. Chem. Eng., Cal. Tech.) Tad Anderson (Dept. Atmos. Sci., U. Washington) Peter Hess (Atmos. Chem., NCAR) Dacian Daescu (Inst. of Appl. Math., U. Minn.) Goal: To develop general computational tools, and associated software, for assimilation of atmospheric chemical and optical measurements into chemical transport models (CTMs). These tools are to be developed so that users need not be experts in adjoint modeling and optimization theory.

21. Approach: Develop efficient algorithms for 4D-Var data assimilation in CTMs; Develop software support tools for the construction of CTM adjoints; Apply these techniques to: (a) analysis of emission control strategies; (b) integration of measurements and models to produce optimal analysis data sets for field experiments; (c) inverse analyses to produce a better estimate of emissions; (d) design observation strategies to improve chemical forecasting

22. Iowa/GFDL/Argonne STEM Model Deployment Mesoscale Meteorological Model (RAMS or MM5) MOZART Global Chemical Transport Model STEM Prediction Model with on-line TUV & SCAPE Anthropogenic & biomass burning Emissions TOMS O 3 Chemistry & Transport Analysis Meteorological Dependent Emissions (biogenic, dust, sea salt) STEM Tracer Model (classified tracers for regional and emission types) STEM Data- Assimilation Model Observations Airmasses and their age & intensity Analysis Influence Functions Emission Biases

23. Through a NSF ITR Grant we are developing data assimilation tools – we have a 3-d version ready for application

24. Thoughts on the Summer 2004 Experiments UI/CGRER Focus: Improving Forecasting and Analysis through Closer Integration of Observations and Models Flight Planning Air Quality Quick- look Post- Mission Test: Our ability to forecast 4-dimensional distributions of ozone and PM The utility of forecasts of ozone, fine particles in flight planning and quick-look analysis The utility of why-cast products (e.g., O 3 -production, VOC vs NO x limited regions, influence functions, hydrocarbon reactivity….) in flight planning and analysis and air quality forecasting Our ability to assimilate surface chemical observations into the forecasts; the impact of assimilation on the forecasts (for a sub-region; e.g., the NE) Targeted measurements that explore the concept of aircraft as “mobile super- sites” Forecasting Analysis

25. We Plan to Look for Ways to Improve the Quality of the Emission Inventories by Close Integration with Modeling Activities Anticipated Activities: Refine PM Inventories Refine/Add species to aid in analysis (e.g., OCS, halocarbons, ethanol…). We look for input on species of interest. Possible other activities: trends, consistent N- Hemisphere inventory, forecasts of emissions,…

26. Surface reflection Ice cloud Water cloud EP/TOMS Ozone (Dobson) SCAPE Aerosol Equilibrium Module Aerosols absorption by gas-phase species O 3, SO 2 and NO 2 Inputs from STEM 3-D field STEM TOP O 3 (Dobson) below STEM top TUV TOP 80km Overtop O 3 = Heterogeneous reactions on BC for NO 2, O 3, SO 2, HNO 3 Outputs: Aerosol composition (size-resolved), Aerosol heterogeneous influences, J-values STEM schematics for on-line TUV and on-line SCAPE

27. ITCT2K2 Post-Run with MOZART Boundary Conditions Top and Lateral Boundary Conditions from MOZART II every 3 hours STEM 80x70 domain 13.4km mapped species: O 3, CO, ethane, ethene, propane, propene, ethyne, HCHO, CH 3 CHO, H 2 O 2, PAN, MPAN, isoprene, NO, NO 2, HNO 3, HNO 4, NO 3, and MVK Lateral boundary conditions of other species, included SO 2 and sulfate still come from the large-scale CFORS tracer model

28. May 05 Flight

29. May 10 Flight