1. Impacts of Assimilation of Air Quality Data from Geostationary Platforms on Air Quality Forecasts Gregory Carmichael(1), Pablo E. Saide (NCAR), Meng Gao (1), Maryam Abdioskouei (1), Arlindo da Silva (NASA GSFC), R. Brad Pierce (NOAA NESDIS-STAR), David G. Streets (ANL), Jhoon Kim, and Myungje Choi (Yonsei University), Chul H. Song (GIST), Greg Thompson, Trude Eidhammer (NCAR), and KORUS-AQ team (1) Center for Global & Regional Environmental Research, University of Iowa, Iowa City, Iowa, USA

2. Models Constrained with Observations Play increasing Important Roles in Research and Applications Need for More aerosol and atmospheric composition data for use in assimilation 2

3. Good News: The global observing systems for atmospheric composition are growing Ground-based stations Airplanes Satellites Ships Trains Balloons …

4. Models Constrained with Observations Play increasing Important Roles in Research and Applications Need for More aerosol and atmospheric composition data for use in assimilation New observations streams are in the pipe-line … Are our modeling & assimilation systems ready to use these data? 4

5. Application: Impacts of Geostationary AOD Assimilation (Are we “ready “ to see an impact?) Objective: Assess performance of assimilating Geostationary GOCI AOD into a system already assimilating MODIS AOD System: WRF-Chem - GSI for MOSAIC sectional aerosol model (Saide et al., ACP 2013) allows assimilation of multiple data Experiments: GSI AOD assimilation every 3 hours, MODIS only, MODIS+GOCI. (Only over-sea AOD used) Aug 27-29, 2012 5 GOCI AOD Saide et al., GRL, 2014 Near future more assets, e.g., GEMS, TEMPO!

6. Application: Impacts of Application: Impacts of Geostationary AOD Assimilation (Are we “ready “ to see an impact?) Objectives: Assess performance of assimilating Geostationary GOCI AOD into a system already assimilating MODIS AOD System: WRF-Chem - GSI for MOSAIC sectional aerosol model (Saide et al., ACP 2013) allows assimilation of multiple data Experiments: GSI AOD assimilation every 3 hours, MODIS only, MODIS+GOCI. (Only over-sea AOD used) Aug 27-29, 2012 WRF-Chem NO Assim WRF-Chem MODIS+GOCI Assim 6 GOCI AOD Saide et al., GRL, 2014 Near future more assets, e.g., GEMS!!

7. Prediction Impact of GOCI on PM10 Prediction Fractional Bias reduction (GOCI + MODIS) (MODIS only)

8. Assimilation Technique along with GOCI Assimilation Changes 4-d Fields -- OBS Prior Factor Change LIDAR Back Scat., Seoul Nat. U.

9. KORUS-AQ forecasting system WRF-Chem with MOSAIC aerosols and a Reduced Hydrocarbon chemistry (Pfister et al. JGR 2014), including simplified SOA formation (Hodzic and Jimenez, GMD 2011) GFS and MACC meteorological and chemical boundary conditions KORUS-AQ anthro (Jung-Hun Woo) and QFED fire emissions AOD data assimilation using GSI (Saide et al., ACP 2013). MODIS and GOCI data were assimilated simultaneously every three hours. First NRT system assimilating GEO AOD Four days of forecasts were available for the outer domain, 2 days for the inner domain

10. Day-1 Day-2 Day-3 Example of AOD assimilation impact during KORUS-AQ Observed AOD (GOCI) WRF-Chem Day-1

11. WRF-Chem Forecast Evaluation vs MODIS and AERONET AOD KORUS-AQ Forecast Briefing 11 Terra/Aqua NNR WRF-Chem AOD 2 nd Day PM2.5

12. WRF-Chem Forecast Evaluation vs MODIS and AERONET AOD KORUS-AQ Forecast Briefing 12 Terra/Aqua NNR WRF-Chem AOD PM2.5 All sites in Korea

13. 13 Impact of Assimilation on AOD Forecasts (2 nd Day) All sites in Korea

14. Impact of Assimilation on PM Forecasts 14 All sites in Korea PM10 PM2.5

15. Impact of Assimilation on PM Forecasts 15 All sites in Korea PM10 PM2.5 Further work needed to improve linkages between AOD and PM2.5

16. Surface Ozone Predictions 16

17. Technique already Extended to include Assimilation of Surface PM2.5 Observations enable improved Predictions Health impacts from winter haze; e.g., Gao et al., Science Tot. Env., (2015) R no DA 0.67 R no DA 0.67 R DA 0.95 R DA 0.95 Impacts of assimilating surface PM 2.5 Mean over all surface observation Haze JAN 2013 PM2.5 Observations are growing rapidly

18. Constraining biomass burning emissions for improved prediction skill and assessing smoke-weather interactions WRF with aerosol-aware microphysics (AAM) (Thompson and Eidhammer, 2014) and WRF-Chem emissions. Inversion based on Saide et al. (GRL 2015b) using WRF tracers (no adjoint, no ensembles) Plans for using it operationally for the NASA ORACLES and NOAA FIREX field experiments Run 2 forecasts needed by the inversion method (with and without feedbacks) so that aerosol feedbacks impacts are also forecasted

19. Moving Forward Add assimilation of both surface and satellite obs. (with new retrievals). Add estimate of emissions. Include assimilation of met data. Assimilation of additional atmospheric composition observations. Additional assimilation techniques, including WRF-Chem 4dVar and hybrid methods.

20. The Growing Interest in Improving Air Quality Predictions/Services and the Role of Atmospheric Composition in Weather and Climate Applications Offer Great Opportunities for Our Community 20 Improved Predictions Requires Evolving Obs Systems Improved Forward Models & Assm. Sys. ImprovedEmissions Continuous Research Enhanced Data Management & Discovery Systems

21. Evaluation vs GOCI AOD KORUS-AQ Forecast Briefing 21 00 UTC GOCI WRF-Chem 03 UTC 06 UTC

22. Evaluation vs GOCI AOD KORUS-AQ Forecast Briefing 22 00 UTC GOCI WRF-Chem 03 UTC 06 UTC

23. Illustrations of Impact of Assimilation on AOD Forecasts 23 All sites in Korea

24. Day-1 Day-2 Day-3 Example of AOD assimilation impact during KORUS-AQ

25. WRF-Chem Forecast Evaluation vs MODIS and AERONET AOD KORUS-AQ Forecast Briefing 25 All AERONET over Korea Terra/Aqua NNR WRF-Chem All AERONET over China

26. Emission Inversion method Simultaneously improve the model fit to various measurements: – SEAC4RS in-situ (OA, CO, extinction) and remote sensing (DIAL-HSRL Extinction) from 2 flights – AERONET AOD – Ground based CO – Satellite AOD Constrain hourly RIM fire emissions Performed at 4km resolution, for 2 met boundary conditions (FNL, NARR) Airborne Ground Satellite Full Chemistry Hourly Tracers WRF-Chem Tracer Sensitivities OBS Sensitivities Variational Inversion Correction factors 12km 4km Observations Saide et al., GRL, 2015

27. Impact of Assimilation on PM Forecasts 27

28. Impacts of constrained emissions Maximum changes shown comparing simulation with initial and constrained emissions Impacts can be substantial 28