Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009.

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Presentation transcript:

Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009

Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Aerosol-Cloud-Climate Interactions Presented by Yi Ming Presented by Yi Ming

3 Prognostic Cloud Properties: Liquid water Amount Droplet number AdvectionShallow cumulusLarge-scale processes Ming et al. JAS (2006, 2007) A prognostic treatment of aerosol-liquid cloud interactions Source and sink terms are fully consistent Multiple aerosol species (i.e., sulfate, organic carbon and sea salt) are activated Droplets evolve freely with model meteorology

4 Cloud droplet number concentration (cm -3 ) in July at 925 hPa Derived from MODIS-retrieved cloud effective radius and optical depth AM3 Bennartz (2007) Comparison of AM3-simulated droplet number distribution with satellite data

5 Anthropogenic aerosol radiative flux perturbation (RFP, W m -2 ) at TOA from pre-industrial to present-day AM3 (to be used for AR5) AM2 (used for AR4) Direct effects – Sulfate and organic carbon 0 (assuming internal mixing of sulfate and black carbon) -1.3 (external mixing) Direct effects - Black carbon 0.5 (external mixing) Indirect effects -1.3 Not included An evolving understanding of aerosol climate impacts

6 Emissions Dry Aerosols Cloud Albedo Wet Removal Activation Albedo Susceptibility 1 st IE Cloud Droplets Dissecting indirect effects on the process level GCM Dynamics & Physics Cloud Albedo Effect Foster et al. (2007) Forcing estimates in AR4 An approach to narrowing down the uncertainties in aerosol indirect effects

7 Difference in cloud albedo (x1000) caused by a uniform 10% increase in droplet number in July Oreopoulos and Platnick (2008) MODIS AM3 Comparison of AM3-simulated cloud albedo susceptibility with satellite data

8 Surface temperature (K)Precipitation (mm day -1 ) AERO GAS BOTH SUM AERO GAS BOTH SUM Ming and Ramaswamy (2009) Zonal-mean responses to aerosol direct and indirect effects simulated with a modified AM2.1 coupled to a slab ocean model Aerosols are important for understanding regional climate change

9 Summary In AM3, a prognostic scheme of droplet number establishes a physical link between aerosols and clouds; Strong cooling caused by anthropogenic aerosol indirect effects is present at TOA; Theories, models and measurements are used to better constrain indirect effects; Aerosol-induced circulation changes need to be studied more thoroughly.

Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009