HR: 12:05h
AN: A32C-08    [Abstracts]
TI: An analysis of cloud scale vertical motions, upper tropospheric humidity, and cirrus microphysical properties in relation to the large-scale atmospheric state
AU: * Comstock, J M
EM: jennifer.comstock@pnl.gov
AF: Pacific Northwest National Laboratory, PO Box 999, Richland, WA 99352, United States
AU: Marchand, R
EM: rojmarch@u.washington.edu
AF: JISAO/University of Washington, 4909 25th Ave NE, Seattle, WA 98105, United States
AU: Beagley, N
EM: nathaniel.beagley@pnl.gov
AF: Pacific Northwest National Laboratory, PO Box 999, Richland, WA 99352, United States
AU: Wang, Z
EM: zwang@uwyo.edu
AF: Department of Atmospheric Science University of Wyoming, Box 3038 1000 E. University Ave., Laramie, WY 82071, United States
AU: Wang, W
EM: weiguo.wang@pnl.gov
AF: Pacific Northwest National Laboratory, PO Box 999, Richland, WA 99352, United States
AB: The importance of upper tropospheric (UT) ice clouds on the Earth's radiation budget and their influence on UT humidity is well known. The inhomogeneous nature of UT clouds can have a significant impact on the mean longwave and shortwave radiative fluxes. Cloud scale motions play a significant role in determining UT relative humidity (and hence cloud initiation) and the inhomogeneous nature of cirrus microphysical properties. Since cloud scale variability is much smaller than global model grid box scales, parameterization of these sub-grid processes are critical to improving predictions of future climate. We will investigate the relationship between cirrus microphysical properties, upper tropospheric water vapor, and vertical motions to understand the link between cloud scale features and the large-scale atmospheric state. Our approach is to combine cloud scale vertical motion derived from radar Doppler velocity measurements, cirrus microphysical properties retrieved using a combined lidar-radar algorithm, thermodynamic radiosonde profiles, and water vapor measurements measured by Raman lidar to evaluate the relationship between cloud scale motions, cloud properties and UT humidity. We will also explore the link between the large-scale atmospheric state (i.e. synoptic features) and UT clouds and water vapor by utilizing a competitive neural network classification scheme. We will analyze cirrus cases compiled over a 2 year period at the Department of Energy's Atmospheric Radiation Measurement Climate Research Facility located at the Southern Great Plains site near Lamont, OK.
DE: 0320 Cloud physics and chemistry
DE: 3310 Clouds and cloud feedbacks
DE: 3360 Remote sensing
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting