Aerosols

1. Aerosols Sarah Lu Sarah.Lu@noaa.gov

2. Outline • Introduction • NEMS GFS Aerosol Component (NGAC) • NGAC V1.0 dust forecasting • Future work NEMS/GFS Modeling Summer School

3. 1. Introduction NEMS/GFS Modeling Summer School

4. Acknowledgements Development and operational implementation of the NEMS-GFS Aerosol Component represents a successful three-year “research to operations” project sponsored by NASA Applied Science Program, JCSDA (NESDIS) and NWS • EMC colleagues: • NEMS GFS team • AQ group • Project Collaborators • Arlindo da Silva, Mian Chin, and Peter Colarco (NASA GSFC) • Shobha Kondragunta and Xiaoyang Zhang (NOAA NESDIS) • Angela Benedetti, Jean Jacques Morcrette, Johannes Kaiser, Luke Jones (ECMWF) • Jeffrey Reid and Walter Sessions (NRL) NEMS/GFS Modeling Summer School

5. Radiation: Aerosols affect radiation both directly (via scattering and absorption) and indirectly (through cloud-radiation interaction) Hurricane forecasts: Dust-laden Saharan air layer reduces occurrence of deep convection and suppresses tropical cyclone activities Data Assimilation: Aerosols are one of key sources of errors in SST retrievals and an important component for accurate radiance data assimilation Regional air quality: Aerosol (lateral an upper) boundary conditions are needed for regional air quality predictions Aviation and visibility: Emissions from large wild fires and volcanic eruption affect aviation route planning and visibility forecasts Public Health: Fine particulate matter (PM2.5) is the leading contributor to premature deaths from poor air quality Why Include Aerosols in the Predictive Systems? NEMS/GFS Modeling Summer School

6. Aerosol-Radiation Feedback: Impact of Aerosols on Weather Forecasts Verification against analyses and observations indicates a positive impact in temperature forecasts due to realistic time-varying treatment of aerosols. • T126 L64 GFS/GSI# experiments for the 2006 summer period • PRC uses the OPAC climatology (as in the operational applications) • PRG uses the in-line GEOS4-GOCART% dataset (updated every 6 hr) #: 2008 GFS package %: In-line GEOS4-GOCART NEMS/GFS Modeling Summer School

7. Atmospheric Correction ‘Dust-Free ’ vs. ‘Dusty’ Granule Retrievals07/28/2011, 08/01/2011 IASI and CrIMSS NEMS/GFS Modeling Summer School MurtyDivakarla (NESDIS)

8. Long Range Dust Transport • Baseline CMAQ with static LBCs versus experimental CMAQ with dynamic LBCs from NGAC, verified against AIRNOW observations • The inclusion of LBCs from NGAC prediction is found to improve PM forecasts (e.g., reduced mean biases, improved correlations) NEMS/GFS Modeling Summer School Youhua Tang (NESDIS)

9. 2. NEMS GFS Aerosol Component NEMS/GFS Modeling Summer School

10. Developing an Interactive Atmosphere-Aerosol Forecast System • In-line chemistry advantage • Consistency: no spatial-temporal interpolation, same physics parameterization • Efficiency: lower overall CPU costs and easier data management • Interaction: Allows for aerosol feedback to meteorology • NEMS GFS Aerosol Component • Model Configuration: • Forecast model: Global Forecast System (GFS) based on NOAA Environmental Modeling System (NEMS), NEMS-GFS • Aerosol model: NASA Goddard Chemistry Aerosol Radiation and Transport Model, GOCART • NEMS GFS and GOCART are interactively connected using ESMF coupler components • Despite the ESMF flavor in how GOCART is implemented, GOCART is incorporated into NEMS GFS as a column process NEMS/GFS Modeling Summer School

11. GOCART Peter Colarco (GSFC) NEMS/GFS Modeling Summer School

12. Primary Integration Runstream • PHY2CHEM coupler componenttransfers data from phys export state to chem import state • Convert units (e.g., precip rate, surface roughness) • Calculations (e.g., soil wetness, tropopause pressure, relative humidity, air density, geopotential height) • Flip the vertical index for 3D fields from bottom-up to top-down Dynamics Dyn-Phy Coupler Physics Phy-Chem Coupler GOCART gridded component computes source, sink, and transformation for aerosols GOCART Phy-Dyn Coupler • CHEM2PHY coupler componenttransfers data from chem export state to phys export state • Flip vertical index back to bottom-up • Update 2d aerosol diagnosis fields Chem-Phy Coupler Dynamics NEMS/GFS Modeling Summer School

13. Challenges for Incorporating Aerosol Component into NEMS • NWP vs Chemistry Transport Model (CTM) modeling • Different focus for the same parameter • High wind speeds and heavy precipitation for NWP versus stagnant conditions and low intensity rain for CTM • Different approaches are needed for emission estimates • Climate projection versus NRT forecasts • Are experiences in NWP applicable to chemistry modeling? • Multiple model ensemble • Verification and evaluation • The use of NWP model to transport chemical species • Need mass conserving, positive definite advection scheme • Requirements in operational environments • Code optimization • Concurrent code development • Near-real-time global emissions NEMS/GFS Modeling Summer School

14. Gibbs phenomenon: Simulations of Grimsvotn ashes T126 Gibbs phenomenon in NGAC, spurious oscillation in the vicinity of sharp gradients T382 High resolution run won’t help. NEMS/GFS Modeling Summer School

15. Dust Source Function Function of surface topographic depression, surface wetness, and surface wind speed (Ginoux et al. 2001) S : Source function sp: fraction of clay and silt size u10: wind speed at 10 m ut: threshold wind velocity p : particle diameter ρp, ρa : particle and air density A : constant=6.5 wt: surface wetness Source function: A static map for probability of dust uplifting, determined by the surface bareness and topographical depression features NEMS/GFS Modeling Summer School

16. Near-Real-Time Smoke Emissions • Globally, biomass burning is one of the primary sources of aerosols; burning varies seasonally, geographically and is either natural (e.g., forest fires induced by lightning) or human induced (e.g., agricultural burning for land clearing). • Satellites can provide smoke emissions information on a real time basis. • A joint NASA/GMAO-NESDIS/STAR-NWS/NCEP project to develop near real time biomass burning emissions product covering the whole globe from polar and geostationary satellites (Shobha Kondragunta and Xiaoyang Zhang, STAR; Arlindo da Silva, GMAO; Sarah Lu, NCEP) GBBEP-Geo • Hourly fire emissions for CO, OC, BC, CO2, SO2, PM2.5 • Limited coverage in high latitudes and no coverage in most regions across India and parts of boreal Asia 16 GOES-E and GOES-W METEOSAT MTSAT NEMS/GFS Modeling Summer School Shobha Kondragunta (STAR)

17. 3. NGAC V1.0 dust forecasting NEMS/GFS Modeling Summer School

18. Overview of NOAA GFS Aerosol Component (NGAC) • Model Configuration: • Forecast model: NEMS GFS • Aerosol model: GOCART • Phased Implementation: • Dust-only guidance is established in Q4FY12 • Full-package aerosol forecast after real-time global smoke emissions are developed and implemented • Near-Real-Time Dust Forecasts • 5-day dust forecast once per day (at 00Z), output every 3 hour, at T126 L64 resolution • ICs: Aerosols from previous day forecast and meteorology from operational GDAS NEMS/GFS Modeling Summer School

19. NGAC Product Suite and Applications NGAC provides 1x1 degree output in GRIB2 format once per day. Output files and their contents include: • ngac.t00z.aod_$CH, CH=340nm, 440nm, 550nm, 660nm, 860nm, 1p63um, 11p1um • AOD at specified wavelength from 0 to 120 hour • ngac.t00z.a2df$FH, FH=00, 03, 06, ….120 • AOD at 0.55 micron • Dust emission, sedimentation, dry deposition, and wet deposition fluxes • Dust fine mode and coarse mode surface mass concentration • Dust fine mode and coarse mode column mass density • ngac.t00z.a3df$FH, FH=00, 03, 06, ….120 • Pressure, temperature, relative humidity at model levels • Mixing ratios for 5 dust bins (0.1-1, 1-1.8, 1.8-3, 3-6, 6-10 micron) at model levels UV index forecasts DA and ensemble AVHRR SST AIRS retrievals Budget, ocean productivity Air quality Budget Atmospheric correction NEMS/GFS Modeling Summer School

20. WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS): Model Inter comparison BSC-DREAM8b MACC-ECMWF DREAM-NMME-MACC NMMB/BSC-Dust NCEP NGAC UKMO SDS-WAS Regional Centre for Northern Africa, Middle East, and Europe, hosted by Spain, conducts daily dust AOD inter comparison NEMS/GFS Modeling Summer School Median

21. NEMS/GFS Modeling Summer School

22. 4. Future Work NEMS/GFS Modeling Summer School

23. Future Operational Benefits Associated with NEMS GFS Aerosol Component • Enables future operational global short-range (e.g., 5-day) aerosol prediction • Provides a first step toward an operational aerosol data assimilation capability at NOAA • Allows aerosol impacts on medium range weather forecasts to be considered • Allows NOAA to exploe aerosol-chemistry-climate interaction in the Climate Forecast System (CFS) • Provides global aerosol information required for various applications (e.g., satellite radiance data assimilation, satellite retrievals, SST analysis, UV-index forecasts, solar electricity production) • Provides lateral aerosol boundary conditions for regional aerosol forecast system NEMS/GFS Modeling Summer School

24. Long Term Goal • With further development and resources, the NEMS GFS can be used for modeling and assimilation of reactive gases (including ozone) and aerosols (including volcanic ashes) on a global-scale • Enable global atmospheric constituents forecasting capability to provide low-resolution aerosols forecasts routinely as well as high-resolution air quality predictions and volcanic ash forecasts on-demand. • Provide quality atmospheric constituents forecast products to serve a wide-range stakeholders, such as health professionals, aviation authorities, policy makers, climate scientists and solar energy plant managers NEMS/GFS Modeling Summer School

25. Thank You Questions? NEMS/GFS Modeling Summer School