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Modeling BC Sources and Sinks - research plan

This research plan outlines the objective and approach to enhance the capacity of GEM-MACH in forecasting BC in the Arctic region, incorporating science from NETCARE and using measurement data to validate the model. It also aims to better understand the sources and sinks of BC in the Arctic, focusing on relative contributions of various sources and long-range transport.

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Modeling BC Sources and Sinks - research plan

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  1. Modeling BC Sources and Sinks- research plan Charles Q. Jia and Sunling Gong University of Toronto and Environment Canada @ 1st annual NETCARE workshop

  2. Outline • Objective and approach • GEM-MACH • Canadian Aerosol Module (CAM) • An example: Arctic BC seasonal variation

  3. Objective and Approach • To enhance the capacity of GEM-MACH in forecasting BC in the Arctic • incorporating the science from NETCARE to better represent BC processes in the CAM (e.g. BC aging) • using the measurement data from NETCARE to validate the model • To better understand the sources and sinks of BC in the Arctic region • using the enhanced GEM-MACH • focusing on relative contributions of various sources (e.g. natural vs. anthropogenic) and long-range transport

  4. GEM-MACH Global Environmental MultiscaleModeling Air Quality and CHemistry • GEM: Global Environmental Multi-scale Model • An operational numerical weather forecasting model • Developed by Meteorological Service of Canada (MSC) [Cote et al., 1998; Yeh et al., 2002]. • MACH: Two air quality modules (ADOM and CAM) • The Acid Deposition and Oxidants Model (ADOM) is an integrated gas-phase chemistry module [Venkatram et al., 1988]. • The Canadian Aerosol Module (CAM) simulates physical and chemical processes of size-resolved aerosol in the atmosphere [Gong et al., 2003]

  5. GEM-MACH Structure SMOKE Regional Data Canada & US Gas Phase Chemistry GEM Meteorology Transport Emission Interface Chemistry Interface CAM Canadian Aerosol Module Global Emissions

  6. Canadian Aerosol Module (CAM) • Simulates physical and chemical processes of aerosols in the atmosphere [Gong et al., 2003] • Emissions, in-cloud and below-cloud scavenging, dry deposition, coagulation, condensation, nucleation et al. • Size-resolved: 12 particle size bins (0.01 to 41 μm in diameter) • Multi-component: 5 species (BC, OC, sulphate, sea salt, soil dust)

  7. An example: importance of depositional processes in seasonal variation of the Arctic BC(Huang L. et al., JGR, V115, D17207, 2010)

  8. Barrow Zeppelin Alert Seasonal Variation of the Arctic BCModel Simulation vs. Observation (surface BC) BC (pptm) Obs. (Sharma et al., 2006) Red- IMPROVE site at Barrow (1996-1998) 11-model predictions [Shindell et al., 2008]

  9. Enhanced In-cloud Scavenging Parameterization Original (empirical) [Giorgi and Chameides, 1986] Enhanced F– GEM cloud cover P – GEM precipitation

  10. Effects of Enhanced Parameterization of In-cloud Scavenging Observations at Zeppelin: Eleftheriadis et al., 2009

  11. Enhanced below-cloud scavenging parameterization Original Valid when Re < 0.1 Enhanced , (any Re) Re – [Feng, 2007]

  12. Effects of Enhanced Parameterization of Below-cloud Scavenging

  13. Thanks!

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