1. Recent Advances in the Use of Chemical Transport Models in Atmospheric Chemistry Studies G. Carmichael, I. Uno, Y. Tang, J. Woo, D. Streets, G. Kurata, N. Thongbooncho, S. Guttikundi

2. Integration

3. Models are an Integral Part of Atmospheric Chemistry Studies Flight planning Provide 4-Dimensional context of the observations Facilitate the integration of the different measurement platforms Evaluate processes (e.g., role of biomass burning, heterogeneous chemistry….) Evaluate emission estimates (bottom-up as well as top-down) Tool for air quality management (emissions scenario evaluation & forecasting)

4. CFORS/STEM-2K1 Model Data Flow Chart Large-scale Meteorological Fields (JMA, NCEP, ECMWF CFORS/RAMS STEM-2K1 On-Line TUV wind velocities, temperature, pressure, water vapor content, cloud water content, rain water content and PV etc. Dust, Sea Salt, Lightning NO x Biogenic Emisisons Emission Preprocessor Biomass Emissions Volcanic SO 2 Emissions Anthropogenic Area Emissions Fuel/activity info Large Point Sources Satellite Observations (fire counts, ozone columns, sea surface temperature, etc.) Forecasts Or Post Analysis Tracers/Markers: SO2/SulfateDMS BCOC VolcanicMegacities CO fossilCO-Biomass EthaneEthene Sea SaltRadon Lightning NOx Dust 12 size bins

5. Ace-Asia & Trace-P Focused on Asian Outflow March 2, 2001 March 7, 2001 March 6, 2001 March 5, 2001 March 4, 2001 March 3, 2001 March 10, 2001 March 9, 2001 March 8, 2001

6. Frontal outflow of biomass burning plumes E of Hong Kong Observed CO –Sacshe et al. Observed aerosol potassium - Weber et al. Biomass burning CO forecast Longitude 100 ppb

7. The Importance of Fossil, Biofuels and Open Burning Varies by Region -- Richness of Emissions Data Base Can be Exploited

8. Using Measurements and Model – We Estimate Contributions of Fossil, Biofuel and Open Burning Sources The Informatics Problem: ”Chemical Mass Balance” Source Information Air Mass Markers Model Runs w/wo Source Sectors

9. What does this tell us about the model – Model deficiency? Emissions problem? Data: Trace-P Science Team

10. Back Trajectories from High CO points. --- CO > 700 --- CO > 600 --- CO > 500 --- CO > 450 --- CO > 400

11. Back Trajectories from High CO point (Zoom & CO > 500 ppbv) --- CO > 700 --- CO > 600 --- CO > 500

12. P-3B SO2 Large-Scale Structure is Captured – But Peaks are Underestimated Data: Kondo et al., Thorton, Sacshe

13. A C B D E F Bias in Sampling also is an Issue Perfect sampling

14. Comparing Modeled and Measured Ratios: We extract all points associated with a specified city and plot measured ratios and plot modeled ratios.  BC/  CO This analysis suggests we need to look for improvements in a specific sector

15. Comparing Modeled and Measured Ratios: We extract all points associated with a specified city and plot measured ratios and plot modeled ratios.  BC/  CO This analysis suggests we need to look for improvements in a specific sector Domestic ??

16. Surface reflection Ice cloud Water cloud EP/TOMS Total Ozone (Dobson) Dust Black Carbon Organic Carbon Sulfate Other PM2.5 and Other PM10 Sea Salt absorption by gas-phase species O 3, SO 2 and NO 2 Inputs from STEM 3-D field STEM TOP 15km O 3 (Dobson) below STEM top height TUV TOP 80km Overtop O 3 = Output: 30 kinds of J-values for SAPRC99 mechanism Framework for Analyzing Chemistry/Aerosol Interactions: Model (STEM+TUV) + Laboratory Studies + Field Experiment Heterogeneous rxns on dust for NO x, O 3, SO 2, HNO 3

17. Cloud Top Temperature (°C) Flight Altitude (m) A example: TRACE-P flights on March 27 DC-8 #15 P-3 #17 P-3 flight #17: volcanic plume observation DC-8 flight #15: frontal study DC-8 J[NO 2 ] P-3 J[NO 2 ] Data: Shetter et al., NCAR

18. Figure 13. Observed and simulated ozone concentrations under the three conditions along with the flight paths of P3 #17 from 2 to 4 GMT Aerosol Effects Modulate Ozone Formation Under This Case Data: M. Avery, NASA,LRC

19. Aerosols Exert An Integrated Impact Ozone Production – And It is Often Larger Than That of Clouds!!

20. April 11 & 12– Best Conditions for Observing Dust Effects. Twin Otter and C-130 Sampled This outflow Dust BC Sulfate Data: Tony Clarke

21. Averaged Dust Heterogeneous Influences (%) below 1km Sulfate HONO Ozone HNO3 4-14 April Calculated Mean Perturbation due to Heterogeneous Rxns on Dust

22. How well should we be able predict trace gases and aerosols? Predictability – as Measured by Correlation Coefficient Data: Trace-P Science Team

23. The Future – Better Integration of Models and Measurements Solid lines represent current capabilities. Dotted lines represent new analysis capabilities that arise through the assimilation of chemical data.

24. Time Serial Evolution of O 3 Influence Function over O 3 Concentration

25. U. Iowa/Kyushu/Argonne/GFDL With support from NSF, NASA (ACMAP,GTE), NOAA, DOE, JST