Interdecadal modulation of ENSO teleconnections to the Indian Ocean Basin Mode and their relationship under global warming in CMIP5 models

Abstract

On the basis of Coupled Model Intercomparison Project phase 5 (CMIP5) models, this study have examined the ability of models to capture the El Niño/Southern Oscillation (ENSO)-Indian Ocean Basin Mode (IOBM) relationship, and investigated the characteristics of interdecadal change of ENSO-IOBM relationship as well as the response of the ENSO-IOBM relationship to the global warming. Among 23 CMIP5 models, the capability of models in representing the IOBM depends largely on the simulation of ENSO. Moreover, half of the models can reproduce the unstable ENSO-IOBM relationship. Considering the simulations of ENSO, ENSO-IOBM relationship and interdecadal change, 6 of 23 CMIP5 models are chosen for further investigation. The interdecadal change of ENSO-IOBM relationship is relative to the three ENSO-related processes. During the high correlation (HC) period, the tropospheric temperature (TT) mechanism, oceanic Rossby waves and antisymmetric wind pattern are strong, prolonging the persistence of IOBM. In comparison, during the low correlation (LC) period, the three processes are weak. The results show that the shallow thermocline in the southwestern Indian Ocean (SWIO), increased interannual variability and prolonged periodicity of ENSO are all responsible for the interdecadal change.Furthermore, the possible changes of ENSO-IOBM relationship in the future are investigated. The ENSO-related tropical Indian Ocean (TIO) warming is strengthened under global warming. Despite the deepened thermocline over SWIO and unchanged ENSO activity, the ENSO-related TIO warming is strengthened by the enhanced TT mechanism, which is caused by the increased saturated specific humidity. The results reveal that there is more downward net heat flux (NHF) over the TIO, which is conducive to the TIO warming, and the latent heat flux (LHF) change makes a great contribution to the NHF change. The weakened upward or strengthened downward LHF is possibly due to the decreased anomalous sea-air temperature difference by strengthened TT mechanism.

Interdecadal Variations in ENSO Influences on Northwest Pacific–East Asian Early Summertime Climate Simulated in CMIP5 Models

“…and surface humidity strengthen tropospheric temperature anomalies and NWP anomalous anticyclone than in the present, and the enhanced NWP anomalous anticyclone in turn leads to increased TIO ! , suggesting the positive feedback strengthens, consistent with Tao et al (2014). Indeed, we find that both TIO !…”

ENSO Atmospheric Teleconnections and Their Response to Greenhouse Gas Forcing

“…The Indian Ocean is home to some of the warmest water in the world's ocean, exceeding 28°C (Tao et al, ). Therefore, deep convection is active over this warm water and is a key source for atmospheric teleconnections into both hemispheres (Xie et al, ).…”

“…ENSO impacts are modulated by the IOD in the Northern and Southern extratropics during boreal winter (Saji & Yamagata, ; Tao et al, ). For example, wave trains like the PNA and the PSA are prominent during El Niño in the boreal winter when accompanied by a positive IOD in the previous fall (Figures a and b).…”

“…In contrast, the number of frequency of La Niñas occurring with a negative IOD is larger than for La Niñas with a positive IOD (Table ). There are clear asymmetries in the spatial pattern of rainfall in the tropical Pacific between an El Niño concurrent with a positive IOD (Figure a), and a La Niña concurrent with a negative IOD (Figure b) (Cai et al, , ; Tao et al, ), resulting in an asymmetry in impact, including greater precipitation anomalies in the central tropical Pacific in El Niño events concurrent with a positive IOD (Figure c).…”

Why does the IOD-ENSO teleconnection disappear in some decades?

“…However, many studies have suggested a decadal variability of ENSO (Gershunov and Barnett, 1998;Wang and Picaut, 2004;Leloup et al, 2007) and/or IOD (Ashok et al, 2004;Abram et al, 2008;Ummenhofer et al, 2011) characteristics, as well as their interactions (Yuan and Li, 2008;Xie et al, 2010;Huang et al, 2010;Chowdary et al, 2012;Tao et al, 2014). The lag correlation between STIO SSTA in fall and Niño 3.4 SSTA in the following fall has been shown to be subjected to decadal variations in both observations and in historical simulations of the coupled climate models of the phase fi ve Coupled Model Intercomparison Project (CMIP5) (Xu et al, 2013, manuscript).…”