  Power-law distributions have been studied as a significant characteristic of
non-linear dissipative systems. Since discovering the power-law distribution of
solar flares that was later extended to nano-flares and stellar flares, it has
been widely accepted that different scales of flares share the same physical
process. Here, we present the newly developed Semi-Automated Jet Identification
Algorithm (SAJIA) and its application for detecting more than 1200 off-limb
solar jets during Solar Cycle 24. Power-law distributions have been revealed
between the intensity/energy and frequency of these events, with indices found
to be analogous to those for flares and coronal mass ejections (CMEs). These
jets are also found to be spatially and temporally modulated by the solar cycle
forming a butterfly diagram in their latitudinal-temporal evolution,
experiencing quasi-annual oscillations in their analysed properties, and very
likely gathering in certain active longitudinal belts. Our results show that
coronal jets display the same nonlinear behaviour as that observed in flares
and CMEs, in solar and stellar atmospheres, strongly suggesting that they
result from the same nonlinear statistics of scale-free processes as their
counterparts in different scales of eruptive events. Although these jets, like
flares and other large-scale dynamic phenomena, are found to be significantly
modulated by the solar cycle, their corresponding power-law indices still
remain similar.
