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Emerging Modules for ASMs : Chemistry – Aerosols – Clouds

Emerging Modules for ASMs : Chemistry – Aerosols – Clouds. J-P Blanchet, É. Girard, C. Jones, P. Grenier, R. Munoz-Alpizar, T. Ayash, A. Stefanof, C. Stefanof, P. Du, A.Tatarevic, P. Dehasse, Y. Melin, D. Simjanoski, C. Jouan, J. Dorais, G. Dueymes S-A. Demers-Giroux, J.-N. Blanchet

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Emerging Modules for ASMs : Chemistry – Aerosols – Clouds

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  1. Emerging Modules for ASMs: Chemistry – Aerosols – Clouds J-P Blanchet, É. Girard, C. Jones, P. Grenier, R. Munoz-Alpizar, T. Ayash, A. Stefanof, C. Stefanof, P. Du, A.Tatarevic, P. Dehasse, Y. Melin, D. Simjanoski, C. Jouan, J. Dorais, G. Dueymes S-A. Demers-Giroux, J.-N. Blanchet Department of Earth and Atmospheric Sciences (SCTA) Institute of Environmental Sciences (ISE) University of Quebec at Montreal (UQAM) and collaboration with S. Gong MSC Presented at the International collaboration in Arctic System Modelling Workshop July 16–17 July, University of Quebec at Montreal Funding Agencies Partners

  2. River Flow Soil Moisture Permafrost Smoke ForestFires Snow Cover Bio aerosols Sea Ice Sea Ice Sea Ice Industrial Aerosols Cold WinterTemperatures DMS aerosol Sea Ice Export Aerosol Impact on the Weather and Climate System WarmSummer Forest To be completed … Environment Climate Hydrology Air Quality Human Activities L Wild Life

  3. AVHRR T 20 yr Summer Temperature Trend NASA/Goddard Space Flight CenterScientific Visualization Studio, Larry Stock, Robert Gersten based on data analysis by Joey Comiso (NASA) A rapidly declining perennial sea ice cover in the Arctic, Geophysical Research Letters, Vol. 29, No. 20, October 2002 http://svs.gsfc.nasa.gov/search/Keyword/Arctic.html Mean Annual Trend °C / yr Sea ice-albedo feedback (+) Snow-albedo feedback (+)

  4. AVHRR T 20 yr Winter Temperature Trend 1982-2002 NASA/Goddard Space Flight CenterScientific Visualization Studio, Larry Stock, Robert Gersten (2003) Mean Annual Trend °C / yr Raatz, 1991 CGCM1/IS92a-Winter 2040-60 minus 1975-95

  5. Evidences of aerosol alterations in the Arctic • Bigg (1980) observed sulfuric acid coating on nearly all other aerosol particles during winter • Boris observed reduced ice nuclei activity by 100 to 10000 fold in crystal counts during anthropogenic Arctic haze event. Reaction on calcium fluoride Ref.: Bigg, 1980

  6. CanadianAerosol Module Gong et al (1997, 2003) Mass Size NARCM: Aerosol Size-Specie Resolved 65 full 4D tracers 12 size bins X 5 species • Saltation • Sea spray • Chemistry • Incloud oxydation • DMS • Volcano • Anthropogenic • Nucleation • Condensation • Coagulation • Sedimentation • Wet deposition • dry deposition • Flexible model structure • Multi-components Simulations • Physically based size distribution • Numeric diffusion for particle growth • Computational intensive (large bin no.) Gong, Barrie and Blanchet et al. 2003, JGR

  7. + + Chemistry (GEM-AQ) Canadian Aerosol Module (CAM) + Level 2: Validation - Closure EarthCARE Instrument Simulator (Radar+Lidar+Rad+MLS) Level 1 A-Train: CloudSat-CALIPSO-MLS Standard Products Algorithms Model and Validation Structure Canadian Regional Climate Model (GEM-Arctic) + Mixed Phase Cloud Resolving (GEM-CRM) Laboratory Instrumented Flights PEARL / SHEBA / IPY New dedicated satellite instrument : TICFIRE

  8. A-Train : CloudSat – CALIPSO – AQUA – AURA – AIRS CALIPSO Ref.: CALIPSO Web site CloudSat

  9. PEARLab (CANDAC) at Eureka on Ellesmere Island in the Canadian Arctic(80 deg N, 86 deg W, 610 meters) Methodology: Compare Model Simulations to groundsite measurements from Eureka, Alert, Spitsbergen, and Barrow and satellite data… Cloud RadarLidar HSRL µwave Radiometer At sea level Also at 610m

  10. PEARL A-Train and PEARL Observations

  11. Observed Simulated Amount  Occurrence Monthly Mean Aerosol – Observed vs Simulated

  12. Statistics for TIC – AerosolsJanuary & July 2007 Ref.: Grenier, Blanchet and Munoz-Alpizar (JGR, 2009)

  13. Kabul Alaska Spain

  14. Kabul Alaska Spain

  15. Kabul TIC-1 TIC-2B TIC-2A Alaska Spain

  16. Is there a 4th General Circulation Cell during extreme cold pole conditions? A dynamics-aerosol-clouds-radiation Interaction on planetary scale Bring aerosol Form TIC Lows drift N Precipitate Av. Pot. Energy Rad-Cooling

  17. Summary • Aerosol links air chemistry to climate via alteration of cloud, precipitation, radiation and circulation in important ways. • Spreading over 5 orders of magnitudes, aerosol physics need adequate size and species resolution for treatment (6D). • Including explicit aerosol may now be optional, but will become essential for proper climate simulations. • Due to time and spatial scales, arctic aerosols are an important research topic.

  18. Further at MOCA-2009 • M 13.9 Stefanof et al (Monday 17h00) • M 13.10Grenier et al (Monday 17h15) • M 13.12Munoz et al (Monday 17h45) • J 03.17Blanchet et al (Tuesday 9h30) • J 02.5Blanchet et al (Wednesday 14h30) • M 12.1 Bertram et al (Thursday 10h30) • M 12.5Girard et al (poster M557 Thursday) • J 02.2Dorais et al (Poster J283 Wednesday) • J 02.1Simjanovski et al (Poster J282 Wednesday)

  19. Fast growing Ice Cold- Dry anomaly Aerosol index Aerosol lifting

  20. DT ≈ -10 to -20°C Process #1 – Adiabatic CoolingDynamics Time Scale : ~ 6 – 24 hours

  21. TIC-1 TIC-2B DT ≈ -3 to -8°C DT ≈ 0 to +2°C Process #2 – Direct IR CoolingEmission from Ice Clouds TIC-1 TIC-2B Time Scale : ~ 1 – 5 days

  22. DT ≈ -5 to -10°C Process #3 – Indirect IR CoolingEmission due to Lost Water Vapour PCP-Water ~ 1 mm Model Bias + 0.3 mm DRY Anomaly Time Scale : ~ 1 – 2 weeks

  23. Net Effect of all 3 Processes Dryadiabatic Process #1: Dynamics TIC-1 TIC-2B Process #2: Direct IR Dry radiation Process #3: Indirect IR Total Cooling ≈ -30 to -40°C

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