Teleconnection Patterns of Different El Niño Types Revealed by Climate Network Curvature

Abstract

The El Niño-Southern Oscillation (ENSO) is the most dominant interannual variation in the global climate system. It is a dynamical atmospheric and oceanic phenomenon characterized by anomalously warm (El Niño) or cold (La Niña) phases of sea surface temperatures (SSTs) in the Equatorial Pacific. Both phases are known to impact Earth's climate significantly on large spatial scales, typically referred to as teleconnections (Trenberth, 1997) and thus have been investigated in many studies over the past two decades (Capotondi et al., 2015(Capotondi et al., , 2020Timmermann et al., 2018).Yet, significant differences in the downstream impacts of El Niño events are reported (Shi et al., 2019), depending on the amplitude and spatial position of SST anomalies. These differences can be partly related to the type of El Niño. The diversity of El Niño events is typically characterized by two modes: The "canonical" or Eastern Pacific (EP) El Niño (Rasmusson & Carpenter, 1982) with peak SST anomalies in the eastern equatorial Pacific, and the "El Niño Modoki" (Ashok et al., 2007) or Central Pacific (CP) El Niño with peak SST anomalies in the Central Equatorial Pacific (Kao & Yu, 2009). Although the effect of both El Niño types on different locations of the Earth-such as the Indian Ocean (IO) (e.g., Klein et al., 1999), maritime continent (e.g., G. Wang and Hendon 2007), tropical Atlantic (e.g., Huang 2004), and Northern America (e.g., Yu et al., 2012)-has been studied thoroughly (see Okumura 2019 andTaschetto et al., 2020 for an overview), previous work has mainly focused on single teleconnections of the El Niño types.In comparison, little is known about differences in the spatial extent of global teleconnection patterns between EP and CP events. In this study, we address this issue by introducing a novel machine learning approach that

Propagation pathways of Indo-Pacific rainfall extremes are modulated by Pacific sea surface temperatures

“…We apply a climate network approach, derived from complex network science. It offers a valuable extension to traditional methods by utilizing the toolset of complex network analysis 80 such as node degree analysis 81 betweenness centrality 82 , and network curvature 83 , to provide insights into climatic patterns and their interconnections. These network-based metrics provide a non-linear time series analysis of the underlying climate system, allowing conclusions to be drawn that may not be readily accessible through conventional approaches.…”

Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance

“…These different types of ENSO events have substantially different downstream impacts on the global climate (e.g., Ashok et al., 2007; Beniche et al., 2024; Larkin & Harrison, 2005; Strnad et al., 2022). For example, extreme drought conditions were recorded in eastern Australia in 2002, while a minor impact on precipitation was detected during the extreme 1997 event (Wang & Hendon, 2007).…”

A multi-modal representation of El-Niño Southern Oscillation Diversity

“…The different types of ENSO events have substantially different downstream impacts on the global climate and dynamics (Strnad et al, 2022). CP El Niño events, for instance, result in a more intense but abbreviated monsoon season over northwest Australia, as compared to their EP El Niño counterparts (Taschetto and England, 2009).…”