The Impact of Long-range Transport on US PM

The Impact of Long-range Transport on US PM

The Impact of Long-range Transport on US PM Prediction Ho-Chun Huang, Youhua Tang, Dongchul Kim, Sarah Lu, Marina Tsidulko, Caterina Tassone, Jianping Huang, Jeff McQueen 1, William Lapenta1, Geoff DiMego1, Stephen Lord1, Ivanka Stajner2, Arlindo daSilva3, Mian Chin3, and Thomas Diehl4 SAIC 1 NOAA/NWS/NCEP/EMC 2 Noblis NASA/GSFC 3 4 UMBC

International Workshop on Air Quality Forecasting Research Boulder, Colorado December 2-3 2009 Outline Overview of NCEPs GFS-GOCART offline global aerosol modeling system Impact of trans-continental and Intercontinental aerosols transports Discussion and Summary GFS-GOCART Offline System GFS NCEP/EMC Global Forecast System (http:// wwwt.emc.ncep.noaa.gov/gmb/gdas) GOCART NASA Goddard Global Ozone Chemistry Aerosol Radiation and Transport Model (GFDL, ESRL FIM-Chem, GEOS-Chem; Chin et al., 2000, 2002, and 2004) GOALS

To serve as an initial benchmark for a planned inline implementation To provide modeled aerosol fields for assimilation of satellite and in-situ data To provide aerosol lateral boundary conditions for regional air quality forecasting (AQF) systems GOCART Aerosols Dust (in radius) 0.1 1.0 m 1.0 1.8 m 1.8 3.0 m 3.0 6.0 m black carbon

hydrophobic and hydrophilic Sulfate hydrophobic and hydrophilic organic carbon 6.0 10.0 m SO2, Sulfate, DMS, and MSA sea-salt aerosols (in radius)

0.1 0.5 m 0.5 1.5 m 1.5 5.0 m 5.0 10.0 m GOCART Processes Advection: flux form semi-Lagrangian (Lin and Rood 1996) Boundary layer turbulent mixing (2nd closure scheme; Helfand and Labraga 1988) Dry deposition: the resistance method (Wesely 1989; Walcek et al. 1986)

Wet deposition: rainout (Giorgi and Chameides 1986), washout (Dana and Hale 1976), convective scavenging with moist convection (Allen et al. 1996), and evaporation below the cloud Simple sulfur chemistry (Chin et al 2000) with prescribed OH, NO3, and H2O2 monthly averaged fields from IMAGES (Mller and Brasseur 1995) Impact of intercontinental transport of dust on AQ Period : May 1 to August 31, 2006 NCEP National Air Quality Forecasting System (CMAQ) *Older version of GFS meteorology

Episode 1 Episode 2 GFS-GOCART Impact on AQFC CONC (ug/m3) CONC CONC (ug/m3) (ug/m3) 30 20 10 0 60 50 40 Karnack C85, TX 2006 Observed CMAQ base run

CMAQ+GFS-GOCART LBC 4050 40 30 30 20 20 30 20 10 1010 0 00 29JUL 02AUG 06AUG

10AUG 80 70 60 50 40 30 20 10 0 50 CONC (ug/m3) 40 Thomas CorpusJefferson Christi - Sch, Nat, TX 2006 Observed

Observed CMAQ CMAQbasebaserunrun CMAQ+GFS-GOCART CMAQ+GFS-GOCARTLBCLBC Kaufman KarnackC71, C85,TXTX2006 2006 Observed Observed CMAQ CMAQbasebaserunrun CMAQ+GFS-GOCART CMAQ+GFS-GOCARTLBCLBC 40 30 CONC (ug/m3) 50

8060 7050 60 5040 4030 3020 20 1010 00 5060 Corpus Christi - Nat, TX 2006 Observed CMAQ base run CMAQ+GFS-GOCART LBC CONC CONC (ug/m3) (ug/m3) Inclusion of Saharan dust transport in LBCs reproduces enhancement of fine particular

matter (PM2.5) concentration in the 1st episode, and about half of the enhancement in the 2nd episode (right panels). 60 AQFC PM25 Conc. versus AIROW Obs. CONC (ug/m3) The GFS-GOCART aerosol simulations provide dynamic lateral boundary conditions (LBCs) to National Air Quality Forecast Capability (AQFC) to identify the intrusion due to long range transport. The intrusions can never be resolved by using present static LBCs. 20 10

0 29JUL 21AUG 25AUG 02AUG 29AUG 06AUG 02SEP 10AUG06SEP To identify the importance of Tran-boundary impact Submicron aerosol Mt. Bachelor, Oregon GFS-GOCART dust Mt. Bachelor data from D. Jaffe, U. of Washington-Bothell g/m3

Test case Test case Daily averages of Mt. Bachelor aerosol and GFS-GOCART dust Mt. Bachelor observatory is at 43.98N, 121.69W, ~2.7 km altitude Impact of long-range transport of biomass burning particles on AQ Period : May 1 to August 31, 2006 Emission : GFEDv2 8day AVG data GFS : Q1FY10 operational Impact from Mexico Fires Impact from Boreal Forest Fires Impact from Siberia Fires

GOCART Emissions Dust Driven by meteorology field Seasalt Driven by meteorology field Anthropogenic emissions Need global emissions database Biomass burning Need real-time global emissions for forecasting as well as type of fire and plume injection height Volcanic emissions Need real-time global emissions for forecasting

Challenge for PM Forecasting : Research versus Forecasting Global scale emissions and in nearreal time Network of global geostationary and orbital satellites (QFED, FLAMB, GFAS) Projection for future fire emissions Need to finish runs within specific time limit (wall-clock) Complexity of physical and chemical processes incorporated

Species mapping between global and regional Chemical-Transport Model (CTM) Improve forward model first guess with assimilated satellite aerosol information Summary The long-rang transport of aerosols has significant impact on the US PM forecast The need for the realistic estimation of emissions of various aerosols globally and in near real-time Continuous improvements of GFS-GOCART emissions and transport processes Include anthropogenic aerosols Include sea-salt aerosol Data Assimilation using satellite observations

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