Cirrus clouds and the large-scale atmospheric state: Relationships revealed by six years of ground based data

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Abstract

The properties of cirrus clouds observed at the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) in Oklahoma are documented from a nearly continuous 6-yr record of 35-GHz cloud radar data. Cirrus frequency over the ACRF is 23% and 28% of the time in the warm (May-September) and cold seasons (November-March), respectively, with maxima and minima during the period studied of 30% and 16% in the warm season and 34% and 24% in the cold seasons. Cirrus, as defined here, reveal a seasonal oscillation in their macroscale properties that can be traced to the seasonal deepening of the troposphere in the Southern Plains region. While the average bulk microphysical properties do not change significantly from season to season, the variability of certain parameters demonstrates seasonal change. It is shown that the properties of cirrus clouds vary perceptively with the large-scale vertical motion. Using NCEP-NCAR reanalysis data to define the large-scale meteorological state when cirrus are observed at the ACRF, the authors find that cirrus tend to exist within a maximum in upper-tropospheric humidity and downstream of the peak upper-tropospheric vertical motion. Cirrus that exist in large-scale ascent upstream of the synoptic-scale middle-tropospheric ridge axis are shown to have higher water contents than cirrus that exist in large-scale subsidence downstream of the ridge axis, although the overall nature of the statistical distributions of water contents do not change greatly, suggesting that it may be difficult to parameterize the properties of cirrus based solely on large-scale vertical motion. The layer-mean particle size, on the other hand, shows no such sensitivity to the large-scale vertical motion. © 2006 American Meteorological Society.

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APA

Mace, G. G., Benson, S., & Vernon, E. (2006). Cirrus clouds and the large-scale atmospheric state: Relationships revealed by six years of ground based data. Journal of Climate, 19(13), 3257–3278. https://doi.org/10.1175/JCLI3786.1

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