Abstract
Substorms are a rapid release of energy that is redistributed throughout the magnetosphere-ionosphere system, resulting in many observable signals, such as enhancements in the aurora, energetic particle injections, and ground magnetic field perturbations. Numerous substorm identification techniques and onset lists based on each of these signals have been provided in the literature, but often with no cross-calibration. Since the signals produced are not necessarily unique to substorms and may not be sufficiently similar to be identified for each and every substorm, individual event lists may miss or misidentify substorms, hindering our understanding and the development and validation of substorm models. To gauge the scale of this problem, we use metrics derived from contingency tables to quantify the association between lists of substorms derived from SuperMAG SML/SMU indices, midlatitude magnetometer data, particle injections, and auroral enhancements. Overall, although some degree of pairwise association is found between the lists, even lists generated by applying conceptually similar gradient-based identification to ground magnetometer data achieve an association with less than 50% event coincidence. We discuss possible explanations of the levels of association seen from our results, as well as their implications for substorm analyses.