Reconsidering the relationship of the El Ni~no--Southern Oscillation and the Indian monsoon using ensembles in Earth system models

We study the relationship between the El Ni~no–Southern Oscillation (ENSO) and the Indian summer monsoon in ensemble simulations from state-of-the-art climate models, the Max Planck Institute Earth System Model (MPI-ESM) and the Community Earth System Model (CESM). We consider two simple variables: the Tahiti–Darwin sea-level pressure difference and the Northern Indian precipitation. We utilize ensembles converged to the system’s snapshot attractor for analyzing possible changes (i) in the teleconnection between the fluctuations of the two variables, and (ii) in their climatic means. (i) With very high confidence, we detect an increase in the strength of the teleconnection, as a response to the forcing, in the MPI-ESM under historical forcing between 1890 and 2005, concentrated to the end of this period. We explain that our finding does not contradict instrumental observations, since their existing analyses regarding the nonstationarity of the teleconnection are either methodologically unreliable, or consider an ill-defined teleconnection concept. In the MPI-ESM we cannot reject stationarity between 2006 and 2099 under the Representative Concentration Pathway 8.5 (RCP8.5), and in a 110-year-long 1-percent pure CO2 scenario; neither can we in the CESM between 1960 and 2100 with historical forcing and RCP8.5. (ii) In the latter ensembles, the climatic mean is strongly displaced in the phase space projection spanned by the two variables. This displacement is nevertheless linear. However, the slope exhibits a strong seasonality, falsifying a hypothesis of a universal, emergent relationship between these two climatic means, excluding applicability in an emergent constraint.

💡 Research Summary

This paper revisits the long‑standing question of how the El Niño–Southern Oscillation (ENSO) modulates the Indian summer monsoon by exploiting large‑ensemble simulations from two state‑of‑the‑art Earth system models: the Max Planck Institute Earth System Model (MPI‑ESM) and the Community Earth System Model (CESM). The authors focus on two physically transparent variables – the Tahiti–Darwin sea‑level pressure difference (TD SLP) as a proxy for ENSO phase and intensity, and the precipitation over northern India (NI P) as a proxy for monsoon strength. By constructing ensembles that have converged to the system’s snapshot attractor, they ensure that the statistical properties they analyse are intrinsic to the forced climate and not artefacts of initial‑condition dependence or short‑term non‑stationarity.

Two complementary research questions are addressed. (1) Does the teleconnection strength between TD SLP and NI P change under historical forcing and future emission scenarios? (2) How do the climatic means of the two variables shift in the two‑dimensional phase space, and does a simple linear relationship (an “emergent relationship”) hold across time and scenarios?

For the first question, the MPI‑ESM historical run (1890‑2005) shows a statistically robust increase in teleconnection strength, with the most pronounced rise occurring in the late 1990s to early 2000s. The authors argue that this increase does not contradict the instrumental record because many observational studies suffer from methodological shortcomings – for example, arbitrary moving‑window lengths, neglect of non‑linear correlation structures, and an ill‑defined teleconnection metric. In contrast, the MPI‑ESM future experiments (RCP8.5, 2006‑2099, and a 1 % yr⁻¹ CO₂ increase scenario lasting 110 years) do not provide sufficient evidence to reject stationarity of the teleconnection; the same holds for the CESM historical‑plus‑RCP8.5 run (1960‑2100). Thus, while a historical increase is detectable in one model, the response under sustained high‑forcing remains ambiguous.

The second question reveals that the joint mean state of TD SLP and NI P moves approximately along a straight line in phase space as the climate warms, indicating a linear displacement. However, the slope of this line is strongly seasonal. During the monsoon months (June‑September) the slope steepens dramatically, meaning that a given ENSO amplitude translates into a larger monsoon precipitation response in summer than in other seasons. This seasonality falsifies the hypothesis of a universal, emergent linear relationship between the two climatic means. Consequently, any emergent constraint that relies on a fixed proportionality between ENSO and monsoon means would be misleading unless it explicitly accounts for seasonal modulation.

Methodologically, the study employs bootstrap resampling to construct confidence intervals, cross‑correlation analysis to quantify teleconnection strength, and seasonally resolved linear regressions to capture slope variability. The use of snapshot attractor ensembles eliminates the need for detrending or ad‑hoc stationarity assumptions, thereby providing a more rigorous statistical foundation than many previous observational studies.

In summary, the paper delivers three key insights. First, a model‑dependent increase in ENSO‑monsoon teleconnection strength is detectable in the historical period, but this signal is not universally present across models or future scenarios. Second, the lack of clear non‑stationarity in future high‑forcing runs underscores the necessity of longer ensembles and multi‑model comparisons to robustly assess climate‑change‑driven teleconnection shifts. Third, while the mean climate state shifts linearly in the two‑variable phase space, the pronounced seasonal dependence of the slope invalidates a simple emergent relationship and cautions against using ENSO‑monsoon coupling as a universal constraint in climate projections. These findings have direct implications for climate model evaluation, the design of emergent constraints, and the development of risk‑based policies that hinge on ENSO‑driven monsoon variability.