The El Ni\~no-Southern Oscillation (ENSO) is characterized by alternating
periods of warm (El Ni\~no) and cold (La Ni\~na) sea surface temperature
anomalies (SSTA) in the equatorial Pacific. Although El Ni\~no and La Ni\~na
are well-defined climate patterns, no two events are alike. To date, ENSO
diversity has been described primarily in terms of the longitudinal location of
peak SSTA, used to define a bimodal classification of events in Eastern Pacific
(EP) and Central Pacific (CP) types. Here, we use low-dimensional
representations of Pacific SSTAs to argue that binary categorical memberships
are unsuitable to describe ENSO events. Using fuzzy unsupervised clustering, we
recover the four known ENSO categories, along with a fifth category: an Extreme
El Ni\~no. We show that Extreme El Ni\~nos differ both in their intensity and
temporal evolution from canonical EP El Ni\~nos. We also find that CP La
Ni\~nas, EP El Ni\~nos, and Extreme El Ni\~nos contribute the most to
interdecadal ENSO variability