J3.2
The Impact of Aged Aerosols on Mixed-Phased Clouds in the Arctic during April 2008

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Tuesday, 25 January 2011: 8:45 AM
The Impact of Aged Aerosols on Mixed-Phased Clouds in the Arctic during April 2008
3A (Washington State Convention Center)
Jerome D. Fast, PNNL, Richland, WA; and J. Rishel, P. Rasch, and L. Emmons

The regional impact of aged aerosol layers on the evolution of mixed-phase clouds over northern Alaska during April 2008 is quantified using the WRF-Chem model. The domain encompasses most of Alaska and the surrounding ocean using a grid spacing of approximately 5 km. Extensive measurements of meteorological, trace gas, and aerosol quantities obtained by several research aircraft conducted in the region by the ISDAC (supported by DOE), ARCTAS (supported by NASA), and ARCPAC (supported by NOAA) field campaigns are utilized to assess model performance. Data was collected by these aircraft below, within, and above cloud layers. Operational data, such as those from in-situ and remote sensing instrumentation at DOE's Atmospheric Radiation Measurement (ARM) facility in Barrow and remote sensing satellite instrumentation, are also employed. Field and operational data have been assembled into a larger dataset for the Aerosol Modeling Testbed, a software tool to assess the performance of WRF-Chem simulations. Boundary conditions for trace gases and aerosols are obtained from a global chemistry model, MOZART-4. Since aerosol predictions over Alaska are dependent on predictions of long-range transport, the MOZART-4 simulations will be evaluated as well. Simulations 1) without aerosol-radiation-cloud interactions, 2) with aerosol-radiation interactions only, and 3) with aerosol-radiation-cloud interactions will be compared to determine the regional impact of aged aerosol layers. The effect of cloud-aerosol interactions in different microphysics schemes will also be examined, since differences in the representation of specific cloud processes (e.g. autoconversion) in these schemes will affect predicted cloud condensation nuclei, cloud droplet number, and consequently the indirect effect predicted by the model. Our group is also currently porting the physics treatments in the CAM global climate model into WRF so that we can fairly assess various treatments for the same process in a consistent manner using a single modeling framework. Ultimately, we seek to compare the advantages and disadvantages of simpler treatments in CAM with the more complex treatments in WRF-Chem when simulating cloud-aerosol interactions. Our initial findings from comparing CAM and WRF-Chem treatments will be presented as well.