1. Applications of satellite observations for understanding, verifying, improving and prepositioning NAQFC TEMPO Workshop Huntsville July12-13 2016 Air Resources Laboratory 1 Pius Lee 1, Jeff McQueen 2, Ivanka Stajner 3, Shobha Kondragunta 4, Daniel Tong 1,5,6, Li Pan 1,5, Jianping Huang 2,7, Youhua Tang 1,5, Tianfeng Chai 1,5, Ho-Chun Huang 2,7, Greg Carmichael 8, Brad Pierce 9, Ted Russell 10, Dick McNider 11, Yang Liu 12, Jim Szykman 13, Ed Hyer 14, and David Edwards 15 1) NOAA ARL; 2) NOAA NCEP; 3) NOAA NWS/OSTI; 4) NOAA/NESDIS/STAR; 5) UMD CICS; 6) GMU CSISS; 7) IMSG, Rockville, MD; 8) U. of Iowa; 9) NOAA/NESDIS; 10) Georgia Tech.; 11) U. Alabama, Huntsville; 12) Emory U. 13) U.S. EPA Office R&D; 14). NRL, MMD; 15) NCAR, ACOM

2. NAQFC vital service U.S. air quality has improved dramatically, but 138.5 M people still live in areas where “pollution levels are too often dangerous to breathe” EPA NAAQS O 3 standards at 70 ppb since Dec 28 2015 2

3. 3 Constrained Satellite Products Global Assimilation http://acmg.seas.harvard.edu/aqast/projects.html 2013 – 2016 : AQAST Tiger Team: Air Quality Reanalysis ( Translating Research to Services ) 2011-2016 + AQ Assessments + State Implementation Plan Modeling + Rapid deployment of on- demand rapid- response forecasting; e.g., new fuel type,…, etc. + Health Impacts assessments + Demonstration of the impact of observations on AQ distributions + Ingestion of new AQAST products into operations TEMPO Workshop Huntsville July12-13 2016 Air Resources Laboratory 3

4. Tang et al., 2015: Using optimal interpolation to assimilate surface measurements and satellite AOD for ozone and PM2.5: A case study for July 2011, JAWMA, 65, 1206-1216 Color-shading for Surface PM 2.5 (μg m -3 ) a)12z July 2 2011 forecast valid for 18z on same day: NAQFC setup. Color bar for bias w.r.t. AIRNow (μg m -3 ) b)Same as a) but with data assimilation adjusted Initialization. Large reduction in underestimation of PM2.5 w.r.t. a) 4

5. 4 DISCOVER-AQ Campaigns Pickering and Lee, EM 2014; Garner, Thompson & Lee Atm Chem 2013 O3 and PM…. AGU Session 13333 Conveners: Newchurch, Langford, Johnson, & Sullivan AGU Session 12929 Conveners: Frost, Kopacz, & Wang Campaign AQ Forecasting winwin Win winwin TEMPO Workshop Huntsville July12-13 2016 5

6. NOAA’s Southeastern Nexus Study (SENEX) - June-July 2013 4 km domain nested within the 12 km NAQFC SENEX and GOAMAZON…. AGU Session 12627 Conveners: Joost de Gouw (NOAA) et al. AGU Session: 12821 Conveners: Jesse Kroll (MIT); Jennifer Kaiser, Frank Keutsch (Harvard U.) Campaign AQ Forecasting Win 6

7. PM 2.5 : NAQFC vs NAQFC-β Bases on GOES O 3 : NAQFC vs NAQFC-β Bases on AIRNow GOES Aerosol and Smoke Product (GASP)-based derived CSI for smoke-associated conc 6/1-7/5 2016 ( Operational vs Experimental) Verification – Satellite-based obs grid-2-grid TEMPO Workshop Huntsville July12-13 2016 Air Resources Laboratory 7

8. Difference between two PM2.5 predictions: with-minus-without fire emissions NOAA NESDIS Hazard Mapping System Fire and Smoke Analysis Intermittent emissions by satellite-based obs TEMPO Workshop Huntsville July12-13 2016 Air Resources Laboratory 8

9. Implemented 2016/02 Suppression emission of fugitive dust over Ice/snow in Jan 2015 Implemented 2016/02 Account for wind blown dust sources in May 2014 PM 2.5 (μg m -3 ) Modulation of emissions by satellite-based obs Snow dust 9 Air Resources Laboratory TEMPO Workshop Huntsville July12-13 2016

10. 12 UTC May 9 Sahara dust event May 9-11 2015 VIIRS AOD 12 UTC May 10 12 UTC May 11 Intruded dust plumes by satellite-based obs TEMPO Workshop Huntsville July12-13 2016 Air Resources Laboratory 10

11.  NOx Data sources  Satellite remote sensing (OMI-Aura NO2).  Ground monitoring (EPA AQS NOx);  Emission data ( NAQFC emissions);  Deriving the trend: (Y2–Y1)/Y1×100%  Selection of urban areas  Emission Indicator – Urban NOx in Summer  Short lifetime  proximity to emission sources  Urban NO2 dominated by local sources;  High emission density  low noise/signal ratio; Satellite-obs enable rapid refresh for emission Monthly averaged CMAQ modeled NOx using NEI2011 TEMPO Workshop Huntsville July12-13 2016 11 Air Resources Laboratory TEMPO Workshop Huntsville July12-13 2016

12. One of four sensors on the EOS-Aura platform (OMI, MLS, TES, HIRDLS) Launched on 07-15-04 Courtesy of OMAR Torres Data Quality Control - VCD quality flag; - Cloud fraction; - Row Anomaly; - Outliners (5% at each end) Instrument Characteristics -Nadir solar backscatter spectrometer -Spectral range 270-500 nm (resolution~0.6 nm ) -Spatial resolution: 13X24 km footprint -Swath width: 2600 km (global daily coverage) -13:45 (+/- 15 min) Local equator crossing time (ascending node) Satellite-obs considerations TEMPO Workshop Huntsville July12-13 2016 Air Resources Laboratory 12

13. OMI Observed NOx Change (July) Courtesy: Lok Lamsal 13 TEMPO Workshop Huntsville July12-13 2016

14. Inter-Comparison of OMI, AQS and NAQFC Atlanta Boston DallasHouston NOx Change from 2005 Level (%) 14 (Source: Tong et al., AE, 2015) TEMPO Workshop Huntsville July12-13 2016

15. Rapid Refresh of NO x Emissions Question: Can satellite and ground data be used to rapidly refresh NOx emissions? Fusing AQS & OMI OMI weighs 1/100* AQS State-level Projection Factors (2005 to 2012) AQS stations TEMPO Workshop Huntsville July12-13 2016 15 (Source: Tong et al., GRL, 2016)

16.  Chemical Analysis: homogeneously generated fields over multiple years  NAQFC in finer resolutions: Chemically, spatially and temporally  Tight linkage with global CTMs e.g. NGGPS  Air chemistry as one of the NOAA Earth Modeling System Framework components – an integrated holistic earth modeling system Pre-position NAQFC via NUOPC example TEMPO Workshop Huntsville July12-13 2016 Air Resources Laboratory 16

17. Summary Applications of satellite observations to:  UNDERSTAND AQ modeling through verification, chemical data assimilation; and corroboration with vertically-resolved AQ campaign intensives;  EXPLORE the efficacy of using observation to capture, modulate and quantify intermittent internal or external emissions for NAQFC;  QUANTIFY NO 2 changes to allow rapidly adjusting NOx over EPA NEIs;  USE NEMS Global Aerosol Component (NGAC) as an global CTM to guide refinement of the vertical grid of NAQFC and linkage to large scale forcing;  LEVERAGE the NUOPC opportunity: CMAQ joins the ESMF world via the National Unified Operational Prediction Capability (NUOPC). ARL has succeeded to couple NAM per sync time-step (5 minutes) with CMAQ5.1 via NUOPC. The developed NUOPC modules can easily be adapted for a similar in- line NGGPS-CMAQ. This preposition NAQFC as an potential entity in an earth modeling system – a multiple disciplinary, multiple-feedback integrated earth modeling system. 17 TEMPO Workshop Huntsville July12-13 2016 Air Resources Laboratory 17