  Cascading failures abound in complex systems and the BTW sandpile model
provides a theoretical underpinning for their analysis. Yet, it does not
account for the possibility of nodes having oscillatory dynamics such as in
power grids and brain networks. Here we consider a network of Kuramoto
oscillators upon which the BTW model is unfolding, enabling us to study how the
feedback between the oscillatory and cascading dynamics can lead to new
emergent behaviors. We assume that the more out-of-sync a node is with its
neighbors the more vulnerable it is and lower its load-carrying capacity
accordingly. And when a node topples and sheds load, its oscillatory phase is
reset at random. This leads to novel cyclic behavior at an emergent, long
timescale. The system spends the bulk of its time in a synchronized state where
load builds up with minimal cascades. Yet, eventually the system reaches a
tipping point where a large cascade triggers a "cascade of larger cascades,"
which can be classified as a Dragon King event. The system then undergoes a
short transient back to the synchronous, build-up phase. The coupling between
capacity and synchronization gives rise to endogenous cascade seeds in addition
to the standard exogenous ones, and we show their respective roles. We
establish the phenomena from numerical studies and develop the accompanying
mean-field theory to locate the tipping point, calculate the load in the
system, determine the frequency of the long-time oscillations and find the
distribution of cascade sizes during the build-up phase.
