Abstract. A subset of continental shallow convective cumulus (Cu) cloud fields has been
shown to have distinct spatial properties and to form mostly over forests and
vegetated areas, thus referred to as “green Cu”
(Dror et al., 2020). Green Cu fields are known to form organized mesoscale
patterns, yet the underlying mechanisms, as well as the time variability of
these patterns, are still lacking understanding. Here, we characterize the
organization of green Cu in space and time, by using data-driven organization
metrics and by applying an empirical orthogonal function (EOF) analysis to a
high-resolution GOES-16 dataset. We extract, quantify, and reveal modes of
organization present in a green Cu field, during the course of a day. The EOF
decomposition is able to show the field's key organization features such as
cloud streets, and it also delineates the less visible ones, as the
propagation of gravity waves (GWs) and the emergence of a highly organized
grid on a spatial scale of hundreds of kilometers, over a time period that
scales with the field's lifetime. Using cloud fields that were reconstructed
from different subgroups of modes, we quantify the cloud street's wavelength
and aspect ratio, as well as the GW-dominant period.