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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]

Sea-surface temperature interannual anomalies (SSTAs) in the thermocline ridge of the southwestern tropical Indian Ocean (TRIO) have several well-documented climate impacts. In this paper, we explore the physical processes responsible for SSTA evolution in the TRIO region using a combination of observational estimates and model-derived surface layer heat budget analyses. Vertical oceanic processes contribute most to SSTA variance from December to June, while lateral advection dominates from July to November. Atmospheric fluxes generally damp SSTA generation in the TRIO region. As a result of the phase opposition between the seasonal cycle of vertical processes and lateral advection, there is no obvious peak in SSTA amplitude in boreal winter, as previously noted for heat content anomalies. Positive Indian Ocean Dipole (IOD) events and the remote influence of El Niño induce comparable warming over the TRIO region, though IOD signals peak earlier (November-December) than those associated with El Niño (around March-May). Mechanisms controlling the SSTA growth in the TRIO region induced by these two climate modes differ strongly. While SSTA growth for the IOD mostly results from southward advection of warmer water, increased surface shortwave flux dominates the El Niño SSTA growth. In both cases, vertical oceanic processes do not contribute strongly to the initial SSTA growth, but rather maintain the SSTA by opposing the effect of atmospheric negative feedbacks during the decaying phase. [ABSTRACT FROM AUTHOR]

An important question in assessing twentieth-century climate change is to what extent have ENSO-related variations contributed to the observed trends. Isolating such contributions is challenging for several reasons, including ambiguities arising from how ENSO itself is defined. In particular, defining ENSO in terms of a single index and ENSO-related variations in terms of regressions on that index, as done in many previous studies, can lead to wrong conclusions. This paper argues that ENSO is best viewed not as a number but as an evolving dynamical process for this purpose. Specifically, ENSO is identified with the four dynamical eigenvectors of tropical SST evolution that are most important in the observed evolution of ENSO events. This definition is used to isolate the ENSO-related component of global SST variations on a month-by-month basis in the 136-yr (1871–2006) Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST). The analysis shows that previously identified multidecadal variations in the Pacific, Indian, and Atlantic Oceans all have substantial ENSO components. The long-term warming trends over these oceans are also found to have appreciable ENSO components, in some instances up to 40% of the total trend. The ENSO-unrelated component of 5-yr average SST variations, obtained by removing the ENSO-related component, is interpreted as a combination of anthropogenic, naturally forced, and internally generated coherent multidecadal variations. The following two surprising aspects of these ENSO-unrelated variations are emphasized: 1) a strong cooling trend in the eastern equatorial Pacific Ocean and 2) a nearly zonally symmetric multidecadal tropical–extratropical seesaw that has amplified in recent decades. The latter has played a major role in modulating SSTs over the Indian Ocean. [ABSTRACT FROM AUTHOR]

Understanding the interactions between the Pacific and other ocean basins during extreme phases of the El Niño-Southern Oscillation (ENSO) is necessary for explaining its global climate impacts. Here climate model experiments are used to highlight a mechanism by which the characteristic warming of the Indian Ocean during peak El Niño months can cool North Africa and South Asia, an area encompassing over three billion people. It is found that warming of the Indian Ocean during extreme El Niño events leads to broader upper tropospheric geopotential height anomalies than would otherwise occur. This weakens the extratropical Rossby wave response initiated in the tropics and leads to higher pressure and reduced cloud forcing over North Africa and South Asia. Reanalysis data provides empirical support for this mechanism, although it is likely only to be prominent during strong El Niño events when Indian Ocean warming tends to be larger. This dampening effect needs to be taken into account in understanding the climatic impact of extreme El Niño events, which are projected to increase under global warming. [ABSTRACT FROM AUTHOR]

Recent studies have pointed out an increased warming over the Indian Ocean warm pool (the central-eastern Indian Ocean characterized by sea surface temperatures greater than 28.0°C) during the past half-century, although the reasons behind this monotonous warming are still debated. The results here reveal a larger picture-namely, that the western tropical Indian Ocean has been warming for more than a century, at a rate faster than any other region of the tropical oceans, and turns out to be the largest contributor to the overall trend in the global mean sea surface temperature (SST). During 1901-2012, while the Indian Ocean warm pool went through an increase of 0.7°C, the western Indian Ocean experienced anomalous warming of 1.2°C in summer SSTs. The warming of the generally cool western Indian Ocean against the rest of the tropical warm pool region alters the zonal SST gradients, and has the potential to change the Asian monsoon circulation and rainfall, as well as alter the marine food webs in this biologically productive region. The current study using observations and global coupled ocean-atmosphere model simulations gives compelling evidence that, besides direct contribution from greenhouse warming, the long-term warming trend over the western Indian Ocean during summer is highly dependent on the asymmetry in the El Niño-Southern Oscillation (ENSO) teleconnection, and the positive SST skewness associated with ENSO during recent decades. [ABSTRACT FROM AUTHOR]

The epochal changes in the seasonal evolution of El Niño induced tropical Indian Ocean (TIO) warming in the context of mid-1970s regime shift is investigated in this study. El Niño induced warming is delayed by one season in the northern TIO during epoch-2 (post mid-1970) and southern TIO during epoch-1 (pre mid-1970). Significant spatiotemporal changes in TIO (especially in the north) warming are apparent during the developing phase of El Niño. The ocean dynamics is the major driver in the basin wide warming during epoch-2 whereas heat fluxes are the dominant processes during epoch-1. Strong coupling between thermocline and sea surface temperature (SST) in epoch-2 indicates that El Niño induced oceanic changes are very significant in the seasonal evolution of basin-wide warming. The thermocline-SST coupling is strengthened by the upward propagating subsurface warming in epoch-2. The westward propagating barrier layer over southern TIO supports persistence of warm SST (over southwest TIO in epoch-2), which in turn induce spring asymmetric mode in winds and precipitation. The asymmetric wind pattern and persistent subsidence over maritime continent are primarily responsible for stronger spring warming in epoch-2. The strong east equatorial Indian Ocean cooling in epoch-2 is mainly driven by coastal upwelling over Java-Sumatra coast, whereas in epoch-1 the weak cooling is controlled by the latent heat flux. The spatiotemporal changes in TIO SST warming and their evolution have strong impact on atmospheric circulation and rainfall distribution over the Indian Oceanic rim through local air-sea interaction. [ABSTRACT FROM AUTHOR]