P4.31
Cloud vertical distribution and overlap statistics from ARM radar/lidar observations
Baike Xi, University of North Dakota, Grand Forks, ND; and X. Dong
Clouds are one of the largest sources of uncertainty in predicting any potential future climate change and have been classified as the highest priority by the U.S. Climate Change Research Initiative. Of great importance for the simulations of climate using General Circulation Models is their ability to accurately represent the vertical distribution of clouds. To provide the statistical information about the vertical distribution of clouds and their overlap, we have collected seven years of ARM/lidar observations at the ARM SGP site during the January 1997-December 2003 period. The ARM 35 GHz cloud radar provides the vertical distribution of clouds and lidar/ceilometer provide the first cloud base information. The radar/lidar data were averaged in 5-min temporal interval and in 90 m vertical resolution. From this extended dataset, we will provide the vertical distribution of clouds first; then study the single-layer cloud fractions, such as low, middle, and high clouds; finally analyze the overlapped clouds, such as contiguous or non-contiguous between different layers. In addition, we will study the seasonal variations of cloud vertical distribution and develop a new technique to identify different cloud types by using maximum/minimum/random cloud overlap techniques with 5-min/1-hour/3-hour temporal resolutions. It is our hope that we can eventually provide statistics of cloud vertical distribution and overlap over the SGP site for climate modelers.
Poster Session 4, Radiation Poster Session IV: Remote Sensing
Wednesday, 12 July 2006, 5:00 PM-7:00 PM, Grand Terrace
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