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Simulation of the Aerosol Indirect Effect in GCM

1 st. and. 2 nd. Aerosol Indirect Effect. Simulation of the Aerosol Indirect Effect in GCM. Radiative Transfer. Microphysics. Onset of Précipitation. CCN Activation. Précipitation Evaporation. Cloud Dynamics. CLOUDNET J. L. Brenguier Météo-France.

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Simulation of the Aerosol Indirect Effect in GCM

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  1. 1st and 2nd Aerosol Indirect Effect Simulation of the Aerosol Indirect Effect in GCM Radiative Transfer Microphysics Onset of Précipitation CCN Activation Précipitation Evaporation Cloud Dynamics CLOUDNET J. L. Brenguier Météo-France

  2. ACE-2 Field Campaign June-July 1997 Experimental Strategy To select cloud systems with similar LWP and morphology, but with different aerosol prop. To sample an area of 60 km, about the GCM spatial resolution To synchronize in situ and remote sensing for column closure experiments Nact=50 cm-3 Nact=250 cm-3 Surface Site Tenerife Morocco CLOUDNET J. L. Brenguier Météo-France

  3. ACE-2 Field Campaign June-July 1997  Multi-disciplinary: aerosol chemistry and physics, cloud microphysics cloud radiative transfer  First experiment with detailed characterization of aerosols and simultaneous measurements of cloud microphysics in situ and radiative properties from above  Observation area of 60 km side sampled during 4 hours: robust statistics BUT  Measurements at noon local time  No radar/lidar  No vertical profile, No diurnal cycle ACE-2 Special Issue of Tellus 2000 JLB et al. JAS 2000 CLOUDNET J. L. Brenguier Météo-France

  4. ACE-2 Field Campaign June-July 1997 JLB et al. 2003 CLOUDNET J. L. Brenguier Météo-France

  5. PACE Cooperative Study between ACE-2 Experimentalists and GCM Modellers for Testing/Developing GCM Parameterizations on the ACE-2 data set Meteo-France: J.L. Brenguier FUBerlin: L. Schüller U Warsaw: H. PawlowskaU Wyoming: J. Snider MPI: J. FeichterHadley: D. Roberts U Dalhousie: U. LohmannU Columbia: S. Menon PNNL: S. Ghan U Michigan: J. Penner LMD: J. Quaas PACE Special Issue of JGR August 2003 (Data Analysis Menon et al. JGR 2004 (Model Parameterizations) CLOUDNET J. L. Brenguier Météo-France

  6. PACE METHODOLOGY •  Series of Closure experiments at a scale relevant to GCM • (60 km) on - aerosol activation • - radiative transfer • - precipitation formation • Identify variables relevant to GCM parameterization of AIE and establish relationship with physical variables • Build a data base for initialisation and validation of SCM versions of the GCMs (8 ACE-2 case studies) • Examine the predictability of the selected variables • Test parameterizations and examine feedback processes CLOUDNET J. L. Brenguier Météo-France

  7. 1st Aerosol Indirect Effect CCN Activation Microphysics Well known since 50 years from - in situ measurements - & 1D to 3D modelling CLOUDNET J. L. Brenguier Météo-France

  8. N=75 cm-3 Droplet Mean Volume Diameter versus Height above Cloud Base (Pawlowska et al. 2000) 51 134 114 208 256 178 134 CLOUDNET J. L. Brenguier Météo-France

  9. Can we predict CDNC at the GCM resolution scale from predicted aerosol properties and a diagnostic of updraft intensity qc(h)>0.9 qcad(h) Ndrizzle< 2cm-3 0.4H < h < 0.6H Pawlowska et al. 2000 CLOUDNET J. L. Brenguier Météo-France

  10. CCN Activation Microphysics Closure Experiments State of the Art CDNC predicted with detailed process models initialised with measured aerosol physico-chemical properties and w OVERESTIMATES measured CDNC Snider et al. 2003 CLOUDNET J. L. Brenguier Météo-France

  11. State of the art in GCM simulation of AIE Menon et al. 2004 CLOUDNET J. L. Brenguier Météo-France

  12. CCN Activation Microphysics CONCLUSIONS : NOT SO BAD • Discrepancies attributed to • incomplete characterization of aerosol properties • and biased vertical velocity • GCM Parameterization of activation is NOT AN ISSUE • except subgrid scheme to derive local w from grid TKE • and better representation of aerosol physico-chemical properties CLOUDNET J. L. Brenguier Météo-France

  13. 1st Aerosol Indirect Effect Radiative Transfer Microphysics • Numerous experimental evidences • from multispectral radiances • - satellites • close remote sensing • BUT • Very few that discriminate between • impact of microphysics • and impact of LWP CLOUDNET J. L. Brenguier Météo-France

  14. 1st Aerosol Indirect Effect Radiative Transfer Microphysics Measured reflectances in VIS and NIR, with H-N grid N remotely retrieved values versus Nact CLOUDNET J. L. Brenguier Météo-France

  15. CLOUDNET J. L. Brenguier Météo-France

  16. CLOUDNET J. L. Brenguier Météo-France

  17. Radiative Transfer Microphysics Closure Experiments State of the Art CDNC predicted with detailed radiative (inverse) transfer models initialised with measured multispectral radiances AGREE with measured CDNC Schüller et al. 2003 CLOUDNET J. L. Brenguier Météo-France

  18. Satellite Monitoring of the AIE Correlation between Cloud Optical Thickness and Droplet Effective Radius - 1 CLOUDNET J. L. Brenguier Météo-France

  19. Radiative Transfer Microphysics CONCLUSIONS : QUITE GOOD • Discrepancies attributed to • heterogeneities of the microphysical fields • optical properties of aerosols and droplets • GCM Parameterization of radiative transfer is AN ISSUE • because of the poor representation of clouds in GCM, • not because of the susceptibility to CDNC CLOUDNET J. L. Brenguier Météo-France

  20. 2nd Measurements of the Aerosol Indirect Effect Aerosol Indirect Effect Précipitation Evaporation Onset of Précipitation Microphysics • Well known since 50 years • from • - in situ measurements • & 1D to 3D modelling • has been carefully explored for weather modification, without success though!!! CLOUDNET J. L. Brenguier Météo-France

  21. Onset of Précipitation Microphysics Closure Experiments State of the Art Measured drizzle concentration depends on the maximum radius droplets can reach in a cloud layer and the threshold (10µm) corresponds to the value derived from detailed modelling of droplet coalescence Pawlowska et al. 2003 CLOUDNET J. L. Brenguier Météo-France

  22. Précipitation Evaporation Microphysics CONCLUSIONS : Very bad Pawlowska et al. 2003 Menon et al. 2003 Aerosol-CNES September 2003 J. L. Brenguier Météo-France

  23. Parameterization of precipitation in GCM Detailed microphysics 1 to 3-D (50 to 200 variables) 3-D CRM Runs (diverse conditions) Tripoli-Cotton, Beheng, Khairoutdinov-Kogan Bulk microphysics for CRM (3 variables: N, qc, qr) Auto-conversion (N, qc) and Accretion (N, qc, qr) 3-D bulk CRM Runs (meso-scale) Tuning bulk coefficients to account for GCM grid smoothing effects Bulk microphysics for GCM (2 variables : N, qc) Auto-conversion (N, qc) (Accretion diagnosed) Bulk microphysics for GCM (2 variables : N, H) Average precipitation rate from multi-cells in stationary state EGS 7 April 2003 Nice J. L. Brenguier Météo-France

  24. CRM versus GCM PARAMETERIZATION OF PRECIPITATION H. Pawlowska CLOUDNET J. L. Brenguier Météo-France

  25. Précipitation Evaporation Microphysics Model variability attributed to the use of CRM bulk parameterizations of auto-conversion and accretion in GCM. New bulk parameterizations are tested (ACE2, DYCOMS), where precipitation rate only depends on LWP and CDNC Pawlowska et al. 2003 CLOUDNET J. L. Brenguier Météo-France

  26. Cloud Life Cycle Microphysics Experimental strategy for BL clouds Aerosols have a strong impact on the onset of precipitation and precipitation rate, but it is not obvious that they have an impact on the cloud life cycle. In BL clouds, the contribution of precipitation to the water budget is comparable to the contributions of radiative & turbulent fluxes. The uncertainty in measurements of these fluxes are still higher than the fluxes themselve. Requires long term monitoring of the cloud life cycle at a super site equipped with surface fluxes, radar and lidar remote sensing and concomitant aerosol characterization CLOUDNET J. L. Brenguier Météo-France

  27. State of the art in GCM simulation of AIE • CONCLUSION • Most of the uncertainty comes from the coarse representation • of thin BL clouds in GCMs • MVDR at cloud top  H1/3, Optical depth  H5/3, Precipitation rate  H4 • Priorities • - Finer vertical resolution and sub-grid vertical schemes • « GCM Bulk » parameterization of rain formation • Reduce the bias in the prediction of Nact • Better understand the heterogenous bias in relation with • the second AIE • - Parameterizations of the aerosol processing in clouds EGS 7 April 2003 Nice J. L. Brenguier Météo-France

  28. 1st and 2nd Boundary Layer Clouds A=0.50 Entrainment-Mixing Aerosol Indirect Effect Radiative Transfer rl=0.2 g kg-1 Microphysics Onset of Précipitation CCN Activation rv=20 g kg-1 Précipitation Evaporation Turbulent Fluxes rv T A=0.05 CLOUDNET J. L. Brenguier Météo-France

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