Continental liquid water cloud variability and its parameterization using Atmospheric Radiation Measurement data

Authors

  • Byung-Gon Kim,

    1. Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, New Jersey, USA
    2. Now at Department of Atmospheric Environmental Sciences, Kangnung National University, Gangnung, Gangwondo, Korea.
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  • Stephen A. Klein,

    1. Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, New Jersey, USA
    2. Now at Atmospheric Science Division, Lawrence Livermore National Laboratory, Livermore, California, USA.
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  • Joel R. Norris

    1. Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, USA
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Abstract

[1] Liquid water path (LWP) variability at scales ranging from roughly 200 m to 20 km in continental boundary layer clouds is investigated using ground-based remote sensing at the Oklahoma site of the Atmospheric Radiation Measurement (ARM) program. Twelve episodes from the years of 1999 to 2001 are selected corresponding to conditions of overcast, liquid water single-layered cloud. In contrast to previous studies of marine boundary layer clouds, variability in cloud-top height in these clouds is comparable to that of cloud base, and most continental clouds appear to be subadiabatic. In agreement with previous studies of marine boundary layer clouds, variations in LWP are well related to the variations in cloud thickness. LWP variability exhibits significantly negative correlation with the static stability of the inversion near cloud top; larger cloud variability is associated with less stable inversions. A previously developed parameterization of LWP variability is extended to account for the differing conditions of continental clouds. The relationship between fluctuations in LWP and cloud thickness suggests that cloud parameterizations treating variations in LWP at these scales should include the effects of subgrid-scale fluctuations in cloud thickness. One such treatment is proposed within the context of a statistical cloud scheme.

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