We employ an advanced data-mining methodology, archetype analysis, to directly and unambigously identify large scale climate drivers and teleconnections that lead to marine extremes in the Australasian region. This new methodology provides an "outside-in" approach to the analysis of marine extremes, by starting with the identification of the large-scale patterns associated with extreme events. This "outside-in" approach is complementary to the standard "inside-out" approach which identifies extremes at one (or more) point locations before considering their relationship to large-scale climate modes.
We show that this methodology identifies instances of anomalous sea-surface temperatures, frequently associated with marine heatwaves, as well as the broadscale oceanic and atmospheric conditions associated with those extreme events. We relate these patterns to familar climate modes (such as ENSO), but note that the archetype analysis extracts these patterns directly from the data itself, with no prior "knowledge" of climate modes. Additionally, we use archetype analysis to assess the ability of a low-resolution climate model to accurately represent the teleconnection patterns associated with extreme oceanic temperatures.