180 Liquid water clouds: conditions for sub-adiabatic water content from long-term ground-based remote sensing observations

Wednesday, 9 July 2014
Bernhard Pospichal, University of Leipzig, Leipzig, Germany; and P. Seifert

Handout (1.4 MB)

The vertical distribution of liquid water content (LWC) within a cloud is often assumed to increase adiabatically from cloud base to top. From observations it is known that the LWC profile shows a sub-adiabatic behavior in many cases, which is caused by the presence of entrainment or precipitation processes. Karstens et al (1994) presented a modified adiabatic assumption changing the adiabatic LWC (LWCad) as a function of distance from cloud base (Δh) to fit better with observations: LWC = LWCad(1.239 - 0.145 ln Δh).

In this study, we utilize long-term ground-based cloud observations performed in the framework of the Cloudnet program (Illingworth et al., 2007) to assess the adiabaticity of liquid water clouds, using a combination of cloud radar, microwave radiometer, and ceilometer. First, a cloud classification is performed and cloud boundaries are defined. The LWCad can then be derived by using temperature profiles from atmospheric models and is compared to the measured LWP by the microwave radiometer as well as the modified adiabatic LWC after Karstens et al.

We define a scale factor (LWPad/LWPMW) which describes the overestimation of LWC by the adiabatic assumption. We will show the dependency of the scale factor on several factors, such as cloud depth, cloud temperature and stability within the cloud. We can show that the adiabatic assumption is met best for relatively warm clouds (10-15°C) and low cloud depth (< 200m).

This study will provide results from Leipzig and other Cloudnet stations in Europe (e.g. Mace Head, Chilbolton, Jülich, Potenza).


Karstens, U., C. Simmer, and E. Ruprecht. "Remote sensing of cloud liquid water." Meteorology and Atmospheric Physics 54.1-4 (1994): 157-171.

Illingworth, A. J., et al. "Cloudnet: Continuous evaluation of cloud profiles in seven operational models using ground-based observations." Bulletin of the American Meteorological Society 88.6 (2007): 883-898.

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