Drivers of reduced ENSO variability in mid-Holocene in a coupled model

Abstract

The drivers of El Niño-Southern Oscillation (ENSO) intensity change during the mid-Holocene (MH) are investigated through employing a coupled model that exhibits excellent performance in simulating the present-day ENSO behaviors. The model shows a 28% decrease in ENSO intensity in the MH simulation compared to the pre-industrial (PI) simulation, showing an agreement with the ranges indicated by the paleo-proxies. Based on quantitative analyses, we reveal that the changes in the oceanic dynamic processes (including the thermocline, zonal-advection, and Ekman feedback terms, in the order from being most to least important) were the major drivers of the reduced ENSO intensity in the MH. Further diagnosis analyses show that the weakening in all three oceanic dynamic terms could be traced back to the weakened thermocline response to zonal wind stress anomaly in the MH compared to that in the PI. Such weakened thermocline response was due to the relatively flattened meridional structure of ENSO-related interannual anomaly field (e.g., zonal wind stress anomaly field) in the MH, which arose from the strengthening of the mean meridional overturning circulation, namely, the mean Pacific subtropical cell (STC). The process-oriented analyses throughout this study suggest a critical linkage between ENSO intensity change and mean STC change in the MH, through documenting how the mean STC change altered the oceanic dynamic processes and thus drove the ENSO intensity change.

Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

“…More sophisticated feedback analysis revealed that the reduction of ENSO variability is due to either the increase of the negative feedback by the mean current thermal advec-tion (An and Bong, 2018) or the reduction of the major positive feedback processes (thermocline, zonal advection and Ekman feedbacks) (Chen et al, 2019a;Tian et al, 2017). The negative feedback due to the thermal advection by the mean current was intensified by the stronger cross-equatorial winds associated with the northward migration of the ITCZ (e.g.…”

“…The negative feedback due to the thermal advection by the mean current was intensified by the stronger cross-equatorial winds associated with the northward migration of the ITCZ (e.g. An and Choi, 2014), and the positive dynamical feedback was suppressed due to the strengthening of the mean Pacific subtropical cell (Chen et al, 2019a). Therefore, the linear stability of ENSO during the mid-Holocene was reduced through the dedicated balance among the various feedback processes, but the change in each feedback process is model dependent.…”

Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

“…More sophisticated feedback analysis revealed that the reduction of ENSO variability is due to either the increase of the negative feedback by the mean current thermal advection (An and Bong, 2018) or the reduction of the major positive feedback processes (thermocline, zonal advection and Ekman feedbacks) (Chen et al, 2019a;Tian et al, 2017). The negative feedback due to the thermal advection by the mean current was intensified by the stronger cross-equatorial winds associated with the northward migration of the ITCZ (e.g., An and Choi, 2014), and the positive dynamical feedback was suppressed due to the strengthening of the mean Pacific subtropical cell (Chen et al, 2019a). Therefore, the linear stability of ENSO during the mid-Holocene was reduced through the dedicated balance among the various feedback processes, but the change in each feedback process is model-dependent.…”

Towards understanding the suppressed ENSO activity during mid-Holocene in PMIP2 and PMIP3 simulations

“…Building on the framework in Jin et al 2006, Kim and Jin (2011a, b) further completed the tool of BJ index. Recently, the BJ index has been widely used to study the scientific issues associated with the ENSO variability change (e.g., Kim et al 2014a, b;Liu et al 2014;Chen et al 2016a, b;Lu et al 2016;Zhu et al 2017;Chen et al 2018;Wang et al 2018). Following Kim and Jin (2011a, b), the specific formulations of BJ index employed in this study are shown below:…”

“…Based on the paleoclimate archives (e.g, the corals, molluscs, ice cores, and seafloor and lake sediments), a number of studies have documented that the level of ENSO variability is lower in MH than present-day climate (e.g., Tudhope et al 2001;Cobb et al 2003;Woodroffe and Gagan 2000;Koutavas and Joanides 2012;Mcgregor et al 2013;Karamperidou et al 2015;Emile-Geay et al 2016;Pausata et al 2017;White et al 2018; and many other studies), although few studies (e.g., Cobb et al 2013) argued that due to the high level of internal variability, it is challenging to discern the ENSO behavior change throughout the Holocene. With the aid of climate models with different complexities, many modeling studies (e.g., Clement et al 2000;Liu et al 2000;Kitoh and Murakami 2002;Otto-Bliesner et al 2003;Brown et al 2008;Zheng et al 2008;Chiang et al 2009;Braconnot et al 2012;An and Choi 2014;Luan et al 2012Luan et al , 2015Roberts et al 2014;Emile-Geay et al 2016; see the review by; Chen et al 2018;Lu et al 2018) also presented evidence about the reduction in the ENSO variability in MH compared to present-day climate, albeit showing a large spread in the level of the reduction among the model simulations.…”