85th AMS Annual Meeting

Tuesday, 11 January 2005
Microphysical properties of Arctic mixed-phase clouds using ground-based remote sensors
Jennifer M. Comstock, PNNL, Richland, WA; and C. J. Flynn, C. N. Long, R. T. Marchand, J. H. Mather, S. A. McFarlane, A. Mendoza, D. D. Turner, and K. Widener
Poster PDF (252.1 kB)
Arctic clouds are characterized as being stratiform and optically thin, and up to ~50% are mixed-phase clouds that occur routinely during all seasons. Arctic mixed-phase clouds have been observed to persist for days, even though the clouds are precipitating ice. Mixed-phase cloud processes are poorly understood and thus the mechanisms that allow for the maintenance of these clouds are uncertain. By characterizing the microphysical properties of mixed-phase clouds at high resolution we can gain a better understanding of the physical processes that help maintain these clouds.

During the Department of Energy Atmospheric Radiation Measurement (ARM) programís Mixed-Phase Arctic Cloud Experiment (M-PACE) in October 2004, the PNNL (Pacific Northwest National Laboratory) Atmospheric Remote Sensing Laboratory (PARSL) will deploy a variety of active and passive remote sensors at Oliktok Point, AK. This deployment will include high spatial resolution lidar, Doppler cloud radar, a dual-channel microwave radiometer, and an Atmospheric Emitted Radiance Interferometer (AERI) from the University of Wisconsin - Madison. We will use these observations to develop a combined remote sensor algorithm for retrieving mixed-phase cloud microphysical properties and phase. In preparation for this experiment, we will examine archived data from the ARM North Slope site near Barrow, AK and from the SHEBA (Surface Heat Budget of the Arctic Ocean) campaign. We will present examples of combined radar-lidar retrievals and spectral infrared retrievals of microphysical properties for typical Arctic mixed-phase clouds. We also anticipate presenting preliminary M-PACE results. Our research goal for this experiment is to understand how small-scale inhomogeneities contribute to the maintenance of Arctic mixed-phase clouds and to develop new parameterizations for global circulation and cloud resolving models.

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