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
Improvement on PM forecasting – Anthropogenic fugitive dust (primary PM emission) – modulated by snow/ice cover. 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 , - PowerPoint PPT Presentation
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Pius Lee1, Jeff McQueen2, Ivanka Stajner3, Daniel Tong1,4,5, Jianping Huang2, Hyuncheol Kim1,4, Li Pan1,4, Barry Baker1,6, Sarah Lu2 ,Jerry Gorline7, Daiwen Kang8,9,Sikchya Upadhaya3,10
1Air Resources Lab. (ARL), NOAA, NOAA Center for Weather and Climate Prediction (NCWCP), College Park, MD2Environmental Modeling Center, National Centers for Environmental Prediction (NCEP), NCWCP, College Park, MD
3Office of Science and Technology, National Weather Service, Silver Spring, MD4Cooperative Institute for Climate and Satellite, University of Maryland, College Park, MD
5Center for Spatial information Science and Systems, George Mason University, Fairfax, VA6Department of Physics, University of Maryland Baltimore County, MD
7Meteorological Development Lab., NOAA, Silver Spring, MD8Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, NC
9Computer Science Corp., Research Triangle Park, NC10Syneren Technologies Corporation
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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
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OUTLINEImprove PM* forecast by 1st 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
3National AQ : Feb_10_to_12_2014, Durham, NC Air Resources Laboratory
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
19National AQ : Feb_10_to_12_2014, Durham, NC Air Resources Laboratory
Case Description of NAM CMAQ
Expr Current 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:CMAQ4.6CB05Aero4ACM2 PBLMobile6 NOx
para2 Upgrade of all of the above* As above
para3 Anthropogenic 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
20National AQ : Feb_10_to_12_2014, Durham, NC Air Resources Laboratory
Weather.com
Improved fidelity
21National AQ : Feb_10_to_12_2014, Durham, NC Air Resources Laboratory
1st 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