The Indian summer monsoon (ISM, or simply, monsoon) rainfall (ISMR) is the backbone of the socio-economic well-being of the people in India. Especially the farmers of the rain-fed farmlands in India heavily rely on the summer monsoon rainfall. Despite the remarkable recurrence of the ISM rainfall every year, considerable year-to-year variability makes its prediction a challenging issue (Goswami 2005). Major sources of its predictability come from the slowly varying boundary conditions (Charney and Shukla 1981). The equatorial Pacific sea surface temperature (SST) anomalies associated with the El Niño–Southern Oscillation (ENSO) are one such source (Shukla and Paolino 1983).
The ENSO and the ISM are two giants of tropical climate that are delicately related. Often, the cold phase of the ENSO or La Niña is associated with a strong ISM and the warm phase of the ENSO or El Niño is associated with a weaker ISM (Webster et al. 1998). However, following an above-normal monsoon rainfall in the year 1997 despite a strong El Niño event, Kumar et al. (1999) suggested that the ENSO-monsoon relationship might have broken down post-1980 due to global warming. However, the deficit ISMR in 2002 and 2004 (that were El Niño years) motivated Annamalai et al. (2007) to investigate the evolution of the ENSO-monsoon teleconnection under global warming using climate model simulations. Comparing historical simulations and global warming runs, Annamalai et al. (2007) concluded that the ENSO-monsoon relation may remain intact under global warming. Due to the immense impact of ENSO and monsoon on the global climate and future climate projections, the issue of ENSO-monsoon teleconnection has received considerable attention. However, there is no clear consensus whether the ENSO-monsoon relationship will weaken or stay intact amidst a warming climate (Turner and Annamalai 2012; Lee and Bódai 2021). While some studies find that the ENSO-monsoon relationship will stay stable under global warming (Annamalai et al. 2007; Turner et al. 2007; Azad and Rajeevan 2016); some find that it is going to weaken (Li and Ting 2015) and some argue that it is going to be a battle between circulation changes and moisture availability (Roy et al. 2019). A recent study by Bódai et al. (2020) even reported an increase in strength of this teleconnection albeit with some cautionary notes on the choice of indices and methodology to evaluate the teleconnection.
A crucial aspect of the ENSO-monsoon teleconnection is the role of the Indian Ocean Dipole (IOD) (Saji et al. 1999; Webster et al. 1999) in it. The importance of the IOD is evident from the fact that about 50% of the positive IODs (pIODs) occur when the Pacific ocean exhibits an El Niño like state (Meyers et al. 2007; Cherchi and Navarra 2013). Several studies that investigated the variability and diversity of the ENSO-monsoon teleconnection find that the IOD plays a critical role in modulating the ENSO-monsoon relation (Ashok et al. 2001, 2004). Ashok et al. (2001) found that co-occurrence of El Niño and pIOD reduces the impact of El Niño on monsoon. While El Niño drives large-scale subsidence over the monsoon domain, pIOD makes more moisture available to the monsoon winds reducing the negative impact of El Niño on the monsoon rainfall. In fact, in view of the changing ENSO-monsoon relation, few studies have reported changes in the co-occurrence of IOD events with ENSO (Ashok et al. 2007; Krishnaswamy et al. 2015; Hrudya et al. 2021). Analyzing the Climate Model Intercomparison Project (CMIP) model simulations under warming scenarios some recent studies argue that extreme positive IODs may increase in the future (Cai et al. 2013, 2014, 2020).
The climate models are the only tools to investigate the future evolution of the ENSO-monsoon relation. Despite limitations in our understanding of the processes that connect the ENSO, monsoon, and IOD, and the systematic biases in the climate models in mimicking these processes, the climate models perform reasonably well in capturing major features of these climate phenomena and their associations (Ramu et al. 2018; McKenna et al. 2020). As per the latest Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), for higher emissions, many models suggest an El Niño-like warming of the mean state in the Pacific Ocean (Zheng et al. 2016; Cai et al. 2018; Fredriksen et al. 2020). This is intriguing because El Niño-like warming can potentially prohibit the increase in seasonal mean ISM rainfall (Ju and Slingo 1995; Lau and Nath 2000; Wang et al. 2000; Jang and Straus 2012). However, the same IPCC AR6 reports that the ISM rainfall is projected to increase during the 21st century in response to continued global warming (Almazroui et al. 2020; Chen et al. 2020; Ha et al. 2020; Wang et al. 2020; Katzenberger et al. 2021). On the other hand, the report also indicates pIOD-like warming of the mean state in the Indian Ocean (Cai et al. 2013; Zheng et al. 2013), which can be expected to enhance ISM seasonal mean rainfall. These projections of the ISM, ENSO, and IOD in the IPCC AR6 suggest that the IOD may play a crucial role in the future evolution of the ENSO-monsoon teleconnection.
Unfortunately, realistic simulation of the ENSO-Monsoon teleconnection even in a historical run is still a struggle for many state-of-the-art climate models (Ramu et al. 2018). Modulation of the strength of this teleconnection over time, for example, decadal time scales (Krishnamurthy and Goswami 2000; Yun and Timmermann 2018), makes it very harder for the models to simulate this relationship. Intermodel diversity in the simulation of monsoon and ENSO leads to large uncertainty in the projection of ENSO-monsoon relation (Lee and Bódai 2021). While it is desirable to obtain a multi-model agreement on the future projection of ENSO-monsoon relation, given the large intermodel diversity, investigations based on the simulations by a single model can also be insightful and instructive. A plausible option is to analyze ensemble simulations (Bódai et al. 2020). Idealization of the forcing field is also helpful in understanding the evolution of the ENSO-monsoon teleconnection under global warming (e.g., Annamalai et al. 2007; Turner et al. 2007).
With this background, we analyzed the relationship between monsoon and ENSO during the ramp-up phase toward CO2 quadrupling in a transient CO2 reversibility experiment with CESM1.2. The model experiment details are provided in Methods section.