On the classification of different flavours of Indian Ocean Dipole events.

There is a large discrepancy between studies on how the Indian Ocean Dipole (IOD) is defined. Indeed, the definition of historical events varies substantially, resulting in conflicting classifications, hampering hydroclimatic impact assessment of this phenomenon. Therefore, this paper aims to compare the various methods that have previously been adopted to define IOD events and demonstrate an alternative method that specifically captures different "flavours" of IOD. It is shown that the choice of sea surface temperature (SST) data set and climatological baseline has significant impact on the resulting classification of IOD events. Furthermore, not all events display the traditional dipole signature pattern of warming/cooling occurring at opposite poles. Rather, some events could be considered "pseudo dipoles," whereby the SST anomalies in the two poles are not of opposite sign. Importantly, the different types of IOD (i.e., "pseudo and true") are associated with varying impacts on rainfall for surrounding regions. To overcome these issues, this study treats Indian Ocean SST anomalies as a continuum of a finite maximum number of statistically distinguishable patterns using a neural network‐based cluster analysis. Ten individual SST patterns were identified with distinct rainfall teleconnections. In particular, four strong IOD patterns (two positive and two negative) were identified, alongside three pseudo dipoles representing anomalously warm conditions across the entire Indian Ocean Basin, with a SST gradient towards the east (i.e., a pseudo negative dipole) or west (i.e., a pseudo positive dipole). The occurrence of each of the 10 self‐organizing mapping (SOM) patterns is shown to be variable over the past 130 years, with some types more common during certain phases of the El Niño/Southern Oscillation or during the first (or second) half of the 20th century. The implications of these findings are particularly significant for attribution studies, development of proxy climate reconstructions, climate model evaluation and future climate change assessment. The Indian Ocean Dipole (IOD) is known to impact hydroclimate across many Indian Ocean rim counties. However, there is a growing body of research that confirms the IOD is a complex phenomenon with multiple variants, which cannot be captured by a simple index such as the dipole mode index (DMI). This paper uses a novel technique (SOM) to identify 10 individual flavours of the IOD with distinct rainfall teleconnections. Figure shows 10 different Indian Ocean SST "types" derived using SOM. Note that numbers in brackets show the number of occurrences of each type. [ABSTRACT FROM AUTHOR]