  We investigate the response of outer radiation belt electron fluxes to
different solar wind and geomagnetic indices using an interpretable machine
learning method. We reconstruct the electron flux variation during 19
enhancement and 7 depletion events and demonstrate a feature attribution
analysis on the superposed epoch results for the first time. We find that the
intensity and duration of the substorm sequence following an initial dropout
determine the overall enhancement or depletion of electron fluxes, while the
solar wind pressure drives the initial dropout in both types of events. Further
statistical results from a dataset with 71 events confirm this and show a
significant correlation between the resulting flux levels and the average AL
index, indicating that the observed "depletion" event can be more accurately
described as a "non-enhancement" event. Our novel SHAP-Enhanced Superposed
Epoch Analysis (SHESEA) method can be used as an insight discovery tool in
various physical systems.
