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1 Improvement on PM forecasting – Anthropogenic fugitive dust (primary PM emission) – modulated by snow/ice cover National AQ : Feb_10_to_12_2014, Durham,

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Presentation on theme: "1 Improvement on PM forecasting – Anthropogenic fugitive dust (primary PM emission) – modulated by snow/ice cover National AQ : Feb_10_to_12_2014, Durham,"— Presentation transcript:

1 1 Improvement on PM forecasting – Anthropogenic fugitive dust (primary PM emission) – modulated by snow/ice cover National AQ : Feb_10_to_12_2014, Durham, NC Pius Lee 1, Jeff McQueen 2, Ivanka Stajner 3, Daniel Tong 1,4,5, Jianping Huang 2, Hyuncheol Kim 1,4, Li Pan 1,4, Barry Baker 1,6, Sarah Lu 2, Jerry Gorline 7, Daiwen Kang 8,9,Sikchya Upadhaya 3,10 1 Air Resources Lab. (ARL), NOAA, NOAA Center for Weather and Climate Prediction (NCWCP), College Park, MD 2 Environmental Modeling Center, National Centers for Environmental Prediction (NCEP), NCWCP, College Park, MD 3 Office of Science and Technology, National Weather Service, Silver Spring, MD 4 Cooperative Institute for Climate and Satellite, University of Maryland, College Park, MD 5 Center for Spatial information Science and Systems, George Mason University, Fairfax, VA 6 Department of Physics, University of Maryland Baltimore County, MD 7 Meteorological Development Lab., NOAA, Silver Spring, MD 8 Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, NC 9 Computer Science Corp., Research Triangle Park, NC 10 Syneren Technologies Corporation

2 2 Networking with AQ managers and forecasters/researchers National AQ : Feb_10_to_12_2014, Durham, NC Good examples: Insights and inspiration Anne Gobin, Burear Chief, CT DEEP: improved NAM, NAQFC Jhih-Yuan Yu, EPA,Taiwan: 臺中國小 1044 µg m -3 Susan Wierman, CEO, MARAMA Natalie and Connor, San Lorenzo VH A great thank you to the conference organizers AIRNow

3 3 OUTLINE  Improve PM* forecast by 1 st principles  NCEP plans on 3 km horizontal grid spacing for CONUS  Q&A: Vertical and compositional distributions? -- intensive campaigns  Wind blown dust – primary PM emission  Anthropogenic fugitive dust  Real-time testing of modulation methodology  Summary and future work 3 National AQ : Feb_10_to_12_2014, Durham, NC Air Resources Laboratory * Fann et al. Risk Analysis 2011: PM risk ≥ O 3 risk

4 4 Finer horizontal grid resolutions  PBL processes  Convective & turbulent mixing  Land-Sea interaction  Fine features: e.g. terrain, urban “grid-2-obs verification and beyond” Kang et al., CMAS 2011 Emissions Meteorology Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

5 Forecasting support for DISCOVER-AQ SJV BW HOU 5 Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

6 6 Comparison of Wind along flight track of P3B on July Spirals over Wilmington and Edgewood Model under-predicted wind shear More frequent calm Bias in higher altitudes Less turbulence may not matter as PBL well-mixed, shallow-convection may matter. calm bias in PBL top venting Investigate processes near PBL top Heat-wave Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

7 12-km (cut from 5X CONUS) 4-km Houston domain Comparison of verification results for pm Finer descriptions helped TYPEOBS_MeanMOD_MEANRMSENMEMBNMBR All_12KM_Dmean All_4KM_Dmean Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

8 8 June 1 –July Science questions: “How do anthropogenic And biogenic emissions Interact and affect AQ And climate” --- Joost de Gouw Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

9 9 Comparison between 12 and nested 4 km forecast for June Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

10 10 Bias RMSE “grid-2-obs verification and beyond” Kang et al., CMAS 2011 Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

11 11 Push towards higher resolution at NCEP Expr productTargeted nextdateRemark GFST878L64 ~ 22kmApril 2014 GDAST574 Enk/GSI ~ 27 kmApril 2014 GEFST382L64 ~ 35 kmApril 2014~30 members NAM12 km North AmericaAlready in place NAM3 km CONUS nestJuly 2014 NAMOn demand basis 1.3 km limited domain Already in place Fire weather Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

12 12  Versatility of selecting a limited- area domain of interest  Limited-area domain forecasts are heavily influenced by boundary conditions and their derivation is critical e.g. exo-domain wild fire emissions ~21x ~12x 5x Agricultural burning prevails in the months of March and April in Mexico HMS wildfire detections during Apr Emission should include Exo- and intra-domain wild fires Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

13 13 The Dust Emission Model (FENGSA) Contribution attributable to ARL in CMAQ5.0 release  Modified Owen’s Equation ( source: Marticorena et al, 1997 ) :  Effect of non-erodiable elements (Drag partition) ( Marticorena et al, 1995 ):  Threshold Friction Velocities (u* t ) ( source: Gillette et al.1980, 1982,1988 ) : Soil type Sand (cm/s) Loamy Sand Sandy Loam Silt Loam Loam Sandy Clay Loam Silty Clay Loam Clay Loam Sandy Clay Silty Clay Clay Desert Land Agricultural  Effects of rain and snow ( Fecan et al, 1999 ): Air Resources Laboratory Tong et al., JGR, (in review) National AQ : Feb_10_to_12_2014, Durham, NC

14 Air Resources Laboratory 14 Windblown dust from agricultural land Washington --http://earthobservatory.nasa.gov/NaturalHazards 12:30 p.m, May 3,2010 Washington National AQ : Feb_10_to_12_2014, Durham, NC

15 ? Anthropogenic Unpaved Road Paved Road Construction Agriculture Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC

16 16 Fugitive Dust Tong et al., Environ. Int. 2009) Chemical Splitting of Fugitive Dust Dust Contribution to PM “Other” Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC Spring Fall

17 CMAQ vs. IMPROVE SW Observations (January 2002) Air Resources Laboratory 17  Two CMAQ runs: with and without anthropogenic dust emissions;  Dust contribution is calculated from the difference; Fugitive Dust contribution < 1  g/m 3 Fugitive Dust contribution > 2  g/m 3 National AQ : Feb_10_to_12_2014, Durham, NC Tong et al., Environ. Int. 2009)

18 18 National AQ : Feb_10_to_12_2014, Durham, NC Air Resources Laboratory NAM Physics/Assimilation Upgrades : June 2014  Replace legacy GFDL radiation with RRTM  Modified gravity wave drag/mountain blocking More responsive to subgrid-scale terrain variability Target : Improve synoptic performance w/o adversely impacting 10-m wind forecasts  New version of Betts-Miller-Janjic convection Moister convective profiles, convection triggers less Target : Improve QPF bias from 12-km parent  Ferrier-Aligo microphysics advection of rime factor  Modified treatment of snow cover/depth Moister convective profiles, convection triggers less Target : Improve QPF bias from 12-km parent  Reduce roughness length for 5 vegetation types Target : Improved 10-m wind in eastern CONUS  Hybrid variational-ensemble GSI analysis Courtesy: Eric Rogers, Environ. Modeling Center NCEP/NOAA

19 19 National AQ : Feb_10_to_12_2014, Durham, NC Air Resources Laboratory CaseDescription of NAMCMAQ ExprCurrent ops NAM:  Hanson Radiation,  simpler advection of hydrometeor,  no regional/categorical modification of snow cover and roughness, respectively,  less tuned gravity wave, convective schemes  3-D VAR assimilation system As current Expr:  CMAQ4.6  CB05  Aero4  ACM2 PBL  Mobile6 NOx para2Upgrade of all of the above*As above para3Anthropogenic fugitive dust emission modulated by snow and ice cover fed from NAM Binary on/off Real-time testing for up-coming implementation: Expr 2014 *Please see details on previous slide

20 20 National AQ : Feb_10_to_12_2014, Durham, NC Air Resources Laboratory Weather.com Improved fidelity

21 21 National AQ : Feb_10_to_12_2014, Durham, NC Air Resources Laboratory 1 st Principle approach to holistically improve PM forecast  Proactively looking into NCEP’s push for high resolution NWP: Participate actively in field campaigns e.g. DISCOVER-AQ and SOAS Guide vertical and speciation profiles by measurements  Proactively working with NCEP to understand NAM/GFS/NGAC changes Feedback responsively and responsibly to strengthen EMC/ARL partnership Integrate meteorological and chemical weather forecasting  Proactively contributing to CMAQ forum and module development Reinforce the culture e.g., dust module (2012) & fine resolution forecasting Complement the SIP and regulatory community with forecasting niche (e.g. D.A.)  Proactively promoting satellite products for dynamic emission modeling Improve climatology e.g. dust source region, forest fuel loading.. Improve methodology for dynamic adjustment: e.g. OMI NOx  Proactively seeking verification metric applicable for fine resolution forecast Overcome the hit or miss simplistic metric Overcome the single value criterion but open to stochastic and tendency metric Contact:

22 22 Acknowledgement  James Crawford, NASA, Langley, VA.  Christopher Loughner & Ken Pickering NASA, Greenbelt, MD.  Alex Guenther, NCAR, CO.  Eric Rogers, EMC, NCEP, NOAA 22 Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC Glossary can be found under

23 Monthly CO emission from wildfire 23 Air Resources Laboratory National AQ : Feb_10_to_12_2014, Durham, NC


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