Clouds are primary modulators of Earth's energy balance. It is thus
important to understand the links connecting variabilities in cloudiness
to variabilities in other state variables of the climate system, and
also describe how these links would change in a changing climate. A
conceptual model of global cloudiness can help elucidate these points.
In this work we derive simple representations of cloudiness, that can be
useful in creating a theory of global cloudiness. These representations
illustrate how both spatial and temporal variability of cloudiness can
be expressed in terms of basic state variables. Specifically, cloud
albedo is captured by a nonlinear combination of pressure velocity and a
measure of the low-level stability, and cloud longwave effect is
captured by surface temperature, pressure velocity, and standard
deviation of pressure velocity. We conclude with a short discussion on
the usefulness of this work in the context of global warming response
studies.