Deep ocean warming-induced El Niño changes

Domain: earth_science
Published: 2024-07-23
Editorial outcome: major_revision

Abstract
The deep ocean, a vast thermal reservoir, absorbs excess heat under greenhouse warming, which ultimately regulates the Earth’s surface climate. Even if CO2 emissions are successfully reduced, the stored heat will gradually be released, resulting in a particular pattern of ocean warming. Here, we show that deep ocean warming will lead to El Niño-like ocean warming and resultant increased precipitation in the tropical eastern Pacific with southward shift of the intertropical convergence zone. Consequently, the El Niño-Southern Oscillation shifts eastward, intensifying Eastern Pacific El Niño events. In particular, the deep ocean warming could increase convective extreme El Niño events by 40 to 80% relative to the current climate. Our findings suggest that anthropogenic greenhouse warming will have a prolonged impact on El Niño variability through delayed deep ocean warming, even if CO2 stabilization is achieved.

Introduction
Over the past few centuries, the Earth has been warming at an unprecedented rate due to human activities, raising serious concerns about the risks this poses1. In response to these potential dangers, the 2015 Paris Agreement enshrined the global goal of limiting the global temperature rise to below 2°C, and ideally to 1.5°C. Achieving the objective of limiting climate change requires balancing carbon dioxide emissions with equivalent carbon absorption2 and potentially reducing CO2 concentrations below current levels to avoid climate tipping3. However, even if we were to reduce CO2 in the atmosphere to pre-industrial levels, the climate system would not return to its original state. In other words, the climate system would change to a different state with the same level of anthropogenic forcing, which is referred to as climate irreversibility. Therefore, understanding climate irreversibility is crucial for assessing the ability of the climate to recover from anthropogenic global warming and for designing climate policy4. Accordingly, including the Carbon Dioxide Removal Model Intercomparison Project (CDRMIP)5, several idealized modeling experiments with different approaches have been conducted to explore the potential of mitigating CO2 forcing. Theirreversibility of several key climate components has been identified, such as surface temperature6–8, sea level9–11 precipitation12–14, the Atlantic Meridional Overturning Circulation (AMOC)15, the Antarctic ice sheet16 and the Intertropical Convergence Zone (ITCZ)17. Concerning the mechanism of irreversible climate change, the role of the deep ocean has recently been highlighted18. The deep ocean absorbs and stores large amounts of thermal energy and facilitates the slow transport of heat from the ocean surface to its interior, acting as a heat reservoir19. The heat stored in the deep ocean will be released at a slower rate than it has been accumulated, leading to irreversible warming of the deep ocean over several centuries and regional irreversibility of sea surface temperature (SST) and precipitation18. This irreversible warming of the SST primarily occurs in the high latitudes and the equatorial eastern Pacific, where the oceans are weakly stratified to allow vigorous heat release through both vertical upwelling and mixing from the deep ocean to the surface. The efficiency of energy transfer from the deep ocean to the surface is closely related to ocean stratification, so deep ocean warming modulates irreversible SST changes in a unique pattern, e.g., El Niño-like warming.

The El Niño-Southern Oscillation (ENSO) is the most dominant interannual climate variability, affecting global weather and climate20, and understanding changes in ENSO in the future climate is important because of its large environmental, economic, and social impacts21. In recent decades, various studies have investigated ENSO changes under greenhouse warming in terms of its intensity, asymmetry, duration, spatial pattern, diversity, and teleconnections22–25. For example, the greenhouse warming has led to strong surface feedback, resulting in more Central Pacific (CP) El Niño26,27, as well as an enhanced nonlinear atmospheric response in the Eastern Pacific (EP), leading to more extreme EP El Niño26,28. As such, the changes in ENSO variability have been studied extensively, while ENSO changes under CO2 removal scenarios are not fully understood. For example, the SST variability over the eastern Pacific29,30 and frequency of convective extreme El Niño31 has increased due to the southward shift of the ITCZ, despite the return of CO2 concentration to current levels. During the climate recovery process, heat released from the deep ocean leads to an effective warming of the equatorial eastern Pacific32, implying a link between deep ocean warming and ENSO changes. However, this possibility has not yet been investigated.

Accordingly, the changes in ENSO during the restoring period after the return of CO2 levels to their present-day climate conditions were investigated. During this period, the Earth’s climate was incompletely recovered and warmer compared to the current climate. This study will investigate the role of irreversible deep ocean warming in ENSO changes. This can provide a perspective on ENSO changes attributed to deep ocean warming, whereas previous studies have interpreted ENSO changes mainly in terms of ocean-atmosphere interactions and upper ocean changes.

Results
The changes in tropical Pacific mean state
To simulate the climate after mitigating global warming by reducing CO2 emissions, the Community Earth System Model (CESM) was run with constant atmospheric CO2 (restoring) after it was increased for 140 years, then symmetrically decreased (see “Methods” and Supplementary Fig. 1). The mean state change was quantified by calculating the difference between the restoring period, defined as the entire 220 years of the restoring simulation, and the present-day (PD) period, defined as the last 400 years of the PD simulation. Figure 1a, b show the changes in the tropical mean state from the PD period. Even when the CO2 concentration returns to current levels, the tropical mean state shows considerable differences. SST anomalies (SSTA) show positive signals across the tropics, indicating incomplete recovery and a warmer state compared to the present climate. In particular, El Niño-like warming (i.e., stronger warming in the eastern Pacific) is evident in the spatial pattern of the SST difference, which is similar to the slow response to global warming33,34.

The increase in precipitation in the tropics and the decrease in the subtropics indicate a southward shift of the ITCZ in the Pacific (Fig. 1b). The latitudinal position of the ITCZ is linked to the energy transport across the equator, which is regulated by the meridional energy exchange between the hemispheres35. As the climate recovers after CO2 reaches current levels, the Northern Hemisphere (NH) cools much faster than the Southern Hemisphere (SH) (Supplementary Fig. 2). The larger heat capacity of the SH17 and the pronounced heat release from the Southern Ocean18 contribute to a relatively slow cooling rate in the SH. Therefore, the reduction in interhemispheric thermal contrast drives the shift of the ITCZ toward the relatively warmer SH. The southward shift of the Pacific ITCZ is accompanied by an increase in precipitation and a weakening of the trade winds over the equator, which further amplifies El Niño-like warming through the Bjerknes feedback. The mean state change shown in Fig. 1a, b will be eventually determined as a result of this positive feedback.

Previous study18 suggested that the SST response in the restoring period originates from deep ocean warming and climatological ocean stratification. To investigate the influence of deep ocean warming on changes in the tropical mean state, three initial warming experiments (IW_EXPs) were conducted. Specifically, the IW_EXPs were conducted with a constant atmospheric CO2 level but with horizontally uniform vertical profiles of ocean temperature and salinity anomalies added to the ocean model initial conditions. These IW_EXPs allow us to explore the impacts of deep ocean warming on the mean state of the tropical ocean and subsequent alterations in ENSO characteristics (see “Methods” for a detailed description of the IW_EXPs).

The mean state change was quantified by calculating the difference between the average for the last 100 years after 50 years from the IW_EXPs and the PD period. Figure 1c, d shows the SST and precipitation responses when the initial ocean warming is added below 700 m (IW_be700). Although spatially uniform warming is only added below 700 m, the initial deep ocean warming lead to a particular SST pattern. Interestingly, the pattern is almost identical to that in the restoring period, with a high pattern correlation of 0.95 over the tropical Pacific. Similarly, the pattern correlation for the precipitation pattern is 0.97. Furthermore, the other IW_EXPs, adding initial ocean warming in the whole ocean depth (IW_whole) and below 100 m (IW_be100), also show similar changes in SST and precipitation, although their magnitudes are different (Supplementary Fig. 3), supporting strong robustness. These results suggest that deep ocean warming triggers specific patterns in the tropical mean state, such as El Niño-like warming and southward shift of the ITCZ. As reported in the previous study, the deep ocean acts as a stove, continuously supplying heat to the ocean surface, and the efficiency of this process depends on ocean stratification18. As a result, the energy from the deep ocean is more effectively transferred to the surface in the eastern Pacific, where stratification is weaker and climatological upwelling prevails18. The initial warming over the eastern Pacific (Supplementary Fig. 4) will be intensified by the Bjerknes feedback and the southward shift of the Pacific ITCZ.

The changes in the characteristics of the ENSO
The El Niño-like warming and the southward shift of the ITCZ have the potential to intensify the variability of the ENSO in the eastern Pacific28. Therefore, we hypothesized that deep ocean warming may contribute to changes in ENSO characteristics by the tropical mean state changes. To examine this possibility, we first checked the amplitudes of the Niño indices (Fig. 2a, b, see “Methods”). The standard deviation (STD) of the Niño3 SSTA increases significantly, while the Niño4 SSTA remains unchanged except for IW_whole. Interestingly, the STDs of the Niño3 SSTA in IW_be700, the IW_be100, and IW_whole experiments consistently increase relative to the PD period, similar to the change in the restoring period. The largest increases are in the order of: IW_whole, IW_be100, and IW_be700, which are proportional to the tropical mean state warming (Supplementary Fig. 3). These results suggest that deep ocean warming enhances the SST variability over the eastern Pacific.

Figure 2c shows the El Niño composites for December-January-February (DJF) during the PD period. Here, El Niño events were defined based on 1 STD of the Niño3 SSTA (see “Methods”). The SSTA pattern shows positive anomalies in the equatorial Pacific and the Niño3 SSTA during the PD period, with a maximum near 141°W. During the restoring period, the Niño3 SSTA increased with the maximum near 134°W, indicating an increased ENSO amplitude and an eastward shift (Supplementary Fig. 5). The SSTA difference from the PD period shows a zonal dipole pattern (Fig. 2d), showing that the equatorial eastern and western Pacific regions have opposite signs, consistent with the increase in STD of the Niño3 (Fig. 2a). In addition, Coupled Model Intercomparison Project Phase 6 (CMIP6) models further support our argument (see Supplementary Note and Supplementary Fig. 6). Interestingly, IW_be700 simulates quite a similar difference in SSTA from the PD period (Fig. 2e). Although only uniform deep ocean warming is added to the initial condition, the model simulates mostly identical El Niño SSTA pattern to that in the restoring period, suggesting that the warming of the deep ocean is the most critical factor in changing El Niño characteristics in the restoring period.

The eastward shift of the ENSO synthesis suggests a systematic change in ENSO diversity. To investigate this, we analyzed changes in the spatial diversity of El Niño using a method that detects the longitude of the SSTA peak during DJF (see “Methods”). The zonal distribution of SSTA peaks shows a bimodal structure with maxima at 155W and 115W (Fig. 3a), although the model tends to simulate more CP El Niño compared to the observational distribution26 (see Fig. 1a, b). Based on this result, we can divide El Niño events into two distinct types: CP El Niño, with maximum SSTA between 165°E−145°W, and EP El Niño, between 125°W−105°W (Supplementary Fig. 7). In addition, to make a quantitative comparison, the CP ratio was defined as the CP events relative to the sum of CP and EP events. The change in SSTA peak occurrence shows that EP El Niño events are more frequent in the restoring period (Fig. 3b), consistent with the decrease in CP ratios in the restoring period relative to the PD period (Fig. 3d). The decrease in the frequency of CP El Niño events is consistently simulated in the IW_be700 (Fig. 3c), IW_be100, and IW_whole experiments (Supplementary Fig. 8). These results suggest that heat release from the deep ocean prefers to more frequent EP El Niño. In addition, the distribution for peaks of La Niña events also shows quite similar changes to that of El Niño events in the restoring period and all IW_EXPs (Supplementary Fig. 9).

EP El Niño is mostly stronger than CP El Niños36,37 and tends to be associated with extreme events, which are directly linked to anomalous climate conditions worldwide31,38. To assess the risk by changes in the extreme case of El Niño, we have adopted the concept of a convective extreme El Niño (see “Methods”), which will be more closely related to anomalous atmospheric circulation28,31. The changes in the frequency of the convective El Niño from the PD period are shown in Fig. 3e. During the PD period, convective El Niño occurs about 13 times per 100 years, accounting for 10% of all El Niño events. On the other hand, the frequency of convective El Niño increased by 40 to 80% in warmer climates. In addition, the CMIP6 models provide additional support for our argument (see Supplementary Note and Supplementary Fig. 6).

The changes in ENSO feedback
So far, we have shown that the deep ocean warming induces the tropical mean state change, resulting in more EP El Niño and convective El Niño. It is important to understand what physical processes lead to these changes in the ENSO characteristics. During the restoring period, there is a significant increase in the equatorial ocean temperature below the 300-m depth (Supplementary Fig. 10a). This result is consistent with all IW_EXPs (Supplementary Fig. 10b–d), suggesting a release of heat from the deep ocean to the surface. In the eastern Pacific, a region of weak ocean stratification and intense upwelling, heat is much more efficiently transferred to the surface. The surface warming is further amplified by the Bjerknes feedback so that the surface warming is greater than the subsurface warming though the warming originated from the deep ocean warming. Therefore, the difference in the vertical temperature gradient is positive in the upper layer, suggesting enhanced ocean stratification (Supplementary Fig. 10e–h).

Enhanced stratification leads to strong air-sea coupling, indicating that the surface-layer responses to a given wind anomaly are amplified. To show enhanced surface-layer responses, we performed a linear regression analysis of the zonal current response to the zonal wind stress anomaly (120°E-90°W) during DJF (Fig. 4a). During the PD period, the current response to wind stress shows a stronger eastward flow in the surface layer, which gradually weakens with depth. Below the thermocline, there is a westward current response, indicating a vertically baroclinic structure. In the restoring period, the eastward current response in the surface layer is intensified (Fig. 4b), indicating stronger zonal advective feedback. Note that the stronger zonal current response is particularly distinctive in the eastern Pacific. In addition, the equatorial upwelling and thermocline responses are also intensified in the eastern Pacific (Supplementary Fig. 11). This enhanced surface-layer feedback plays a critical role in the enhanced eastern Pacific SST variability. The IW_be700 also simulates enhanced feedback in the surface layer (Fig. 4c). This result suggests that deep ocean warming leads to stronger oceanic responses in the eastern Pacific upper layer. The other two IW_EXPs show similar changes in the zonal current response (Supplementary Fig. 12a, b), supporting strong robustness.

The ocean stratification is responsible for the intensified surface-layer feedback, but it cannot account for the eastward shift of the responses. Previous studies suggested that the El Niño-like mean conditions not only thermodynamically enhance the response of precipitation to equatorial SST but also provide favorable conditions for the shift of anomalous atmospheric heating due to increased mean trade wind convergence39. For example, when the eastern Pacific is in a more moist state, the response of wind and precipitation to SSTA shifts eastward40. The eastward shift of the wind response to ENSO anomalies strengthens the thermocline and zonal advection feedback, ultimately increasing the eastern Pacific SST variability41,42. As mentioned earlier, the El Niño-like warming induces an eastward shift of the ascending branch of the Walker circulation and an equatorward shift of the ITCZ (Fig. 1), which strengthens the shift in the surface-layer current response.

To analyze the eastward shift of the ENSO feedback, we calculated the regressed precipitation and wind onto the Niño3 SSTA during DJF (Fig. 4d). As expected, the precipitation pattern shows positive anomalies associated with westerlies in the equatorial Pacific. The changes in the precipitation and wind response from the PD period indicate an eastward extension of the response, with positive anomalies observed in the eastern Pacific and negative anomalies in the western Pacific (Fig. 4e). The eastward shift of the wind response to the SSTA contributes to the enhanced Ekman feedback. In addition, the strong equatorial wind stress response enhances the thermocline feedback by intensifying the equatorial Kelvin wave responses. In addition, increases in the meridional slope of the wind stress (Fig. 4e), resulting in a stronger off-equatorial Rossby wave response. The IW_EXPs consistently simulate the precipitation response eastward shifted compared to the PD period (Fig. 4f and Supplementary Fig. 12c, d). The pattern of precipitation change is almost identical to that of the restoring period, with a pattern correlation of 0.95. These results suggest that the warming of the deep ocean produces the ENSO system eastward in the restoring period. Note that the westerly anomaly is stronger at 150-120°W, consistent with where the surface current response increases (Fig. 4b, c). In short, the occurrence of more EP El Niño can be attributed to the eastward shift of the ENSO feedback system caused by El Niño-like warming.

Methods
Definition of ENSO
The Niño3 and Niño4 SSTA, defined as the area-averaged SSTA in the Niño3 region (5°S-5°N, 150-90°W) and Niño4 region (5°S-5°N, 160°E-150°W) are used to describe the amplitude of ENSO, respectively. The SSTA was calculated by removing the linear trend and the monthly climatological mean for each experiment and ensemble. We utilize a threshold of ±1 STD of the DJF mean Niño3 SSTA during the PD period to define ENSO events. To define convective extreme El Niño, we employed the method used in previous studies31,48–50, wherein convective extreme El Niño was identified as absolute precipitation exceeding a threshold of 5 mm/day during the DJF season.

Detecting center method
To identify the center of the ENSO, we adopt the method used in the previous study26, focusing specifically on the detection of its longitudinal peak: first, we calculate a moving average of the DJF SSTA over a 30° longitude window, moving at 10° intervals from 150°E to 90°W (10 points in total). We then identify the points where the moving average DJF SSTA is greater than 1 STD or less than −1 STD. The STD is calculated on the basis of DJF SSTA values above 150°E-90°W during the PD period. Among the selected points, the point with the largest absolute value is taken as the peak of El Niño (or La Niña). The longitude where the peak is located is taken as the center of ENSO.

Model
This study used the CESM, Version 1.2, which comprises several components, including the Community Atmospheric Models Version 5 (CAM5), the Community Land Model Version 4 (CLM4), the Community Ice Code Version 4 (CICE4), and the Parallel Ocean Version 2 (POP2). The CAM5 and CLIM4 components were characterized by a horizontal resolution of about 1° and 30 vertical levels, while the CICE4 and POP2 components used a nominal horizontal resolution of 1° (with the 30 meridional resolutions being about 1/3° near the equator) and 60 vertical ocean levels.

Design of the ramp-up and ramp-down experiment
The present and future climate simulations were carried out. The first simulation was a present-day scenario with a constant atmospheric CO2 concentration (at the current level of 367 ppm) for 900 years (Supplementary Fig. 1). The second simulation was a CO2 ramp-up and ramp-down scenario that started with different initial conditions from the present-day simulation (28 in total). This experimental design was similar to the 1pctCO2-cdr scenario used in the CDRMIP4, except for the initial CO2 level, which was set to the pre-industrial level (284.7 ppm). In these experiments, we gradually increased the atmospheric CO2 concentration at a rate of 1% per year until it reached four times the initial value (1469 ppm) over a period of 140 years. We then reduced the CO2 concentration symmetrically at the same rate for 140 years until it returned to the initial value (367 ppm). We then conducted a recovery experiment with a constant CO2 concentration (367 ppm) for 220 years to simulate a period of net-zero emissions. The second experiment consists of 28 ensemble members with different initial conditions for a total of 500 years in each ensemble.

Design of the initial warming experiment
To investigate how deep ocean warming contributes to the change in ENSO characteristics, three types of initial warming experiments (denoted as IW_whole, IW_be100, and IW_be700) were conducted. These experiments were branched from the initial condition (year 2000) of each ensemble member and then integrated with the constant atmospheric CO2 concentration of 367 ppm. In addition, horizontally uniform vertical profiles of the ocean temperature and salinity anomalies were added to the initial condition of the ocean model (year 2000). In other words, the initial temperature and salinity perturbations of IW_EXPs are horizontally identical in all ocean grids. The added initial anomalies are the global mean ocean temperature and salinity in the year 2280, when the atmospheric CO2 level first returns to its original level (367 ppm). Note that, in addition to the temperature profile, a salinity anomaly profile was added to prevent any potential imbalance for running the model. To isolate the role of deeper ocean warming, the initial perturbation was added to the entire depth, below 100 m and below 700 m in IW_whole, IW_be100, and IW_be700, respectively. All experiments were integrated for 150 years with nine ensemble members. Note that these three IW_EXPs were also used in a previous study18 (see Fig. 3).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The authors used CESM model to perform idealized CO2 ramp up and ramp down simulations in which atmospheric CO2 increases at a rate of 1% per year to 4xCO2, and then decreases at the same rate to 1xCO2 (present-day level). The authors focused on the response of El Niño and the analyzed the role of deep ocean warming. By comparing El Niño events with present-day, the authors found that during the restoring period when atmospheric CO2 returns to present-day level, Eastern Pacific El Nino events are intensified, precipitation in the tropical eastern Pacific increases, and convective extreme El Nino events also increase. By designing deep ocean warming simulations, the authors showed the importance of deep ocean warming in regulating El Nino response. This paper is well written. The simulations are well designed and the analysis is well done. I recommend its publication with minor modification.\nHow much heat is stored in the deep ocean and the resulting effect on El Nino response would depend on the rate of atmospheric CO2 decrease. The author only performed ramp down simulations with a CO2 decreasing rate of 1% per year. The implication of different CO2 ramp down rate on the presented results should be discussed.\nSpecific comments:\nLine 49: What results does ‘here’ refer to?\nLines 97-98: Please elaborate a bit more here of how the shift of the Pacific ITCZ partly contributes to the El Niño-like warming.\nLines 183-184: It might also be useful to show the vertical density gradient.\nLines 234-235: ‘These changes are driven by ocean stratification and El Niño-like warming, ‘. It appears twice.\nLine 288: How long does the current-day simulation last?\nLine 309: How is the salinity anomaly profile determined?\nLine 379-380: Deep ocean warming induced irreversible climate changes Nature Climate Change, Nature Climate Change\nFor some reason, I could not find this article.\nFig. 1 caption (b) and (c) should exchange with each other. Or, the numbering of each panel should be changed.", "reviewer_2": "Kim et al. investigated the variations in ENSO during the recovery period after intensive global warming. Generally, this study showed some interesting results helping us to deepening understanding of ENSO, based on a series of numerical experiments. But I still have some concerns, which are listed below.\n1) The mitigation scenario in the title is somewhat unrelated to this study.\n2) “As the climate recovers after CO2 reaches current climate levels, the Northern Hemisphere (NH) cools much faster than the Southern Hemisphere (SH)” The authors should give evidence to support this. What causes the different cooling rates? And what is the relative contribution of the NH-SH contrast and the El Nino-like warming pattern to the migration of the ITCZ?\n3) “The initial warming over the eastern Pacific “in line 121. The authors may show the initial warming pattern in supplementary material, which is very helpful to understanding the formation processes of the El Nino-like warming pattern.\n4) The authors stressed the intensification of the zonal-advection feedback. However, in previous studies, this feedback favors the CP El Ninos?\n5) “The second experiment lasted 500 years and involved 28 ensemble members.” Do you mean 500*28 years of integrations were conducted?\n6) “A horizontally uniform temperature anomaly profile was added to the initial ocean state”. Why uniform temperature anomalies are specified? This should be very different from those in recovery experiments.\n7) Various feedbacks were diagnosed, but the authors did not mention which seasons they analyzed.", "reviewer_3": "March 2024,\nA review of the manuscript NCOMMS-24-06651 \"Deep Ocean warming-induced El Niño changes under climate mitigation scenarios\" submitted by J.-S. Kug.\nThis study explored ENSO changes due to deep-ocean warming based on a CO2 ramp-up and ramp-down experiment and present-day experiments initialized with horizontally uniform deep-ocean heat anomalies using CESM1.2. The authors examined not only the ENSO amplitude changes but also the diversity and feedback changes.\nI have read several previous papers related to the CESM1.2 CO2 ramp-up/down experiments. This paper aims to clarify the impact of the deep-ocean heat on the hysteresis of ENSO, which is important to the ENSO community. Although the results are interesting, I have some potentially critical concerns in their analyzing method. Because the present manuscript does not sufficiently describe their method, I could not fully understand how the data was analyzed. I would like to ask the authors to revise the methodology and clarify my major concerns below.\nMajor comments:\n1. The IW experiments are not at the equilibrium states, so the anomalous fields have to be carefully defined to compare with the PD experiment.\nThe last 100 years after 50 years are analyzed in the IW experiments and the PD period (Lines 106-107). However, it is clear in Fig. 3b of Oh et al. (2024), that the SST change is not steady at all. Thus, all the anomalous fields have to be carefully defined.\nAs the mean state remains changing for 150 years, it is important to describe it and consider removing its potential impact on the anomalous fields analyzed in this study. First of all, the definition of anomalies needs to be clarified. Then, how to remove the potential background changes from the anomalies needs to be described. For example, the Nino3 SSTA st.d. is easy to be affected by spurious slow anomalies due to background change. The SSTA pattern in Fig. 2 is also affected by the definition. Other main and supplementary figures are also sensitive to the definition of the anomalies.\nIdeally, an initial condition large ensemble is required to define the anomalies from the changing background, but the experiments have only 9 ensembles for each of the IW experiments. Therefore, the method to define the anomaly is important.\n2. The IW experiments are not fully described (Lines 104-105 and the Methods section), so it is not possible to reproduce the simulations based on the manuscript.\nThe method could be explained more in detail. At least, it must be clarified if the experiments are identical to the previous work (ref. 17).\nAnd, what are the values of the uniform temperature anomaly profile and the corresponding salinity anomaly profile? How did you determine the salinity anomaly profile to avoid any potential density imbalance? Is there an initial condition's vertical gap at the 700-m (100-m) depth in IW_be700 (IW_be100)? The total heat content from the bottom to the surface may depend on the bottom topography, so probably the total heat content is not horizontally uniform --Does this affect the results? Because these points were unclearly written, I could not follow the detailed parts of the results.\n3. Adding a schematic chart to explain the present conclusion may help readers understand what is different between the mechanism underlying ENSO changes induced by deep ocean warming and that associated with anthropogenic greenhouse warming (Lines 243-252).\n4. The criteria for defining ENSO are not clear to me.\nIn Line 135, the authors said that \"El Nino events were defined based on 1 st.d. of the Nino3 SST.\" Are these criteria the same among the experiments? Or, did you use different thresholds in each experiment? This difference may affect the patterns of the SSTA in Fig. 2c,d,e., for example.\n5. The convective El Niño is not clearly defined in the text.\nIn Line 166, the authors described \"the convective El Nino was defined as when Nino3 rainfall during the DJF season exceeds a threshold of 5 mm/day\". Do the authors mean \"Nino3 precipitation anomaly\" instead of \"the absolute precipitation\"? If the absolute precipitation in the Nino3 region is used for defining the convective El Nino, the increase of the convective El Nino event occurrences is attributed to the mean state change to a certain extent.\n6. It is unclear if there is inter-model uncertainty in the ENSO changes during the restoring period.\nIn the Introduction, the authors imply that there are multi-model datasets of CDRMIP, which can be used to investigate the inter-model uncertainty of the present key results. I would suggest the authors conduct a multi-model analysis to indicate whether the major findings are independent of the models or dependent on the models.\nMinor comments:\nTitle: I would say that this study analyzed El Nino changes under a single climate mitigation scenario in a climate model, so saying \"under climate mitigation scenarios\" does not seem representative of the study.\nLines 24-25: This sentence is too subjective and ambiguous to describe the implications of this study.\nLine 51: The meaning of \"residual upwelling\" is unclear.\nLine 64: I am quite unsure of the reason for citing ref. 28 (Ohba and Ueda 2009, JCLI https://doi.org/10.1175/2008JCLI2334.1).\nLine 79: What is \"the model\"? The details can be found in the Methods section, but the model name could be provided in the main text for clarity.\nLine 129: Actually, the Nino4 SSTA st.d. is decreased in IW_whole. How did you interpret this?\nLine 130: The Nino3 SSTA st.d. is increased more in IW_be100 and IW_whole than in IW_be700 and Restoring. Why this happened could be explained in the text.\nLine 136-137: How to calculate the central longitude is unclear. The Method section needs to be cited here.\nLine 137: Any figure does not describe this text. A supplementary figure needs to be provided.\nLines 150-151: The observational distribution is not shown in any figure.\nFigure 4: Is the figure calculated based on DJF? Please clarify the season used for this figure.\nLine 190: Where is the thermocline in Fig. 4a-c?\nLine 213: Define the Nino3 index. Do you mean Nino3 SSTA? In this manuscript, the index names are confusingly mixed (e.g., Nino3, Nino3 SST, Nino3 SSTA, Nino3 index).\nLine 220: The results from the IW_be700 experiment are not mentioned yet. Figure 4f should appear in Lines 221-222.\nFigure 2a", "reviewer_b": "What is the season for the Niño3 and Niño4 SSTA standard deviations? Write in the caption.\nAns) Added the season to the caption.\nTypos etc.:\nLine 21: Use \"Intertropical Convergence Zone\" or \"intertropical convergence zone\" instead of \"Intertropical convergence zone\".\nAns) Revised to “Intertropical Convergence Zone”.\nLine 84: Do you mean \"The present-day period\" instead of \"the restoring period\"?\nAns) Revised.\nLine 129, etc.: Use \"Niño3 SSTA\" instead of \"Niño3 SST\"? Check the manuscript overall.\nAns) Revised to “Niño3 SSTA”. In addition, we have unified the expressions “SSTA” and “Niño3 SSTA” throughout the manuscript.\nLine 130, 141, 496, etc.: Use \"Niño3 SSTA\" instead of \"Niño3\"? Check the manuscript overall.\nAns) Revised.\nLine 188 etc.: Use \"wind stress\" instead of \"windstress\" overall.\nAns) Overall, revised every instance of 'windstress' to 'wind stress' in the manuscript.\nLine 210: Replace \"Fig\" with \"Fig.\".\nAns) Revised\nLines 235-236: This sentence repeats the previous sentence in Lines 234-235.\nAns) Revised sentence to “These changes are driven by ocean stratification and El Niño-like warming, which enhance zonal advective, Ekman, and thermocline feedbacks in the eastern Pacific, despite increased thermal damping (Supplementary Fig. 13). Our findings consistently show that deep ocean warming is the primary driver of these ENSO changes, as observed in the IW_EXPs.”\nLine 272: \"STD\" is not defined.\nAns) Revised the manuscript (L135-136) to define the STD as follows: The standard deviation (STD) of the Niño3 SSTA increases significantly, while the Niño4 SSTA remains unchanged except for IW_whole.\nLines 331", "reviewer_361": "Check the titles of these references. \"CO2\" instead of \"CO 2\". And, \"2°C\" instead of \"2 C\".\nAns) Revised the reference.\nReferences (e.g., ref. 14): The authors' names are not consistent in the references. for example, JS, or J-S? Check all references for consistency.\nAns) Revised the format of references to be consistent.\nReference 17: Replace \"cPhaden\" with \"McPhaden\".\nAns) Revised the reference.\nLine 380: Add a period at the end of the title.\nAns) Revised the reference.\nReference 17: I could not find ref. 17. Has it changed from the cited one to the following published paper? Oh, JH., Kug, JS., An, SI. et al. Emergent climate change patterns originating from deep ocean warming in climate mitigation scenarios. Nat. Clim. Chang. (2024). https://doi.org/10.1038/s41558-024-01928-0.\nAns) Revised the reference.\nReference 31: I could not reach this reference (Pathirana et al. 2022). Is the reference changed from the cited one to the following paper? Gayan Pathirana et al. Increase in convective extreme El Niño events in a CO2 removal scenario. Sci. Adv. 9, eadh2412 (2023). DOI:10.1126/sciadv.adh2412\nAns) Revised the reference.", "reviewer_author_response": "Response to Reviewer #1\nThe authors used CESM model to perform idealized CO2 ramp up and ramp down simulations in which atmospheric CO2 increases at a rate of 1% per year to 4xCO2, and then decreases at the same rate to 1xCO2 (present-day level). The authors focused on the response of El Niño and the analyzed the role of deep ocean warming. By comparing El Niño events with present-day, the authors found that during the restoring period when atmospheric CO2 returns to present-day level, Eastern Pacific El Niño events are intensified, precipitation in the tropical eastern Pacific increases, and convective extreme El Niño events also increase. By designing deep ocean warming simulations, the authors showed the importance of deep ocean warming in regulating El Niño response. This paper is well written. The simulations are well designed and the analysis is well done. I recommend its publication with minor modification.\nWe thank the reviewer for encouraging comments. The comments were fully considered in the revised manuscript. The point-by-point responses are as follows:\nComments:\n1. How much heat is stored in the deep ocean and the resulting effect on El Niño response would depend on the rate of atmospheric CO2 decrease. The author only performed ramp down simulations with a CO2 decreasing rate of 1% per year. The implication of different CO2 ramp down rate on the presented results should be discussed.\nAns) Thanks for asking an important question. Based on the reviewer's comments, we've added the discussion as follows:\nThe hysteresis of the precipitation and SST remains over the tropical Pacific even with a rapid CO reduction, indicating that changes in ENSO are inevitable (Kim et al. 2022). The strength of the irreversibility depends on the rate of CO reduction, which contributes to the amount of energy stored in the ocean. The slower the rate of reduction, the more heat will be stored in the ocean and the greater the warming of SST when CO returns to current levels (Jeltsch-Thömmes et al. 2020). The results from the IW experiments show that the stronger the El Niño-like warming, the greater the increase in SST variability over the eastern Pacific (Fig. 2a). These results indicate that a slower rate of decline will result in a more prolonged and pronounced warming of the tropical Pacific SST, which may potentially lead to a more intense El Niño event.\nSpecific comments:\nLine 49: What results does ‘here’ refer to?\nAns) Revised to “This irreversible warming of the SST primarily occurs in the high latitudes and the equatorial eastern Pacific, where the oceans are weakly stratified to allow vigorous heat release through both vertical upwelling and mixing from the deep ocean to the surface.”\nLines 97-98: Please elaborate a bit more here of how the shift of the Pacific ITCZ partly contributes to the El Niño-like warming.\nAns) Revised “The southward shift of the Pacific ITCZ is accompanied by an increase in precipitation and a weakening of the trade winds over the equator, which further amplifies El Niño-like warming through the Bjerknes feedback.”\nLines 183-184: It might also be useful to show the vertical density gradient.\nAns) As the reviewer suggested, we have added the changes in density and vertical density gradient in supplementary Fig. 10 (Fig A).\nFig. A | The changes in ocean stratification. The difference in the equatorial averaged (5°S–5°N) vertical climatological temperature and potential density from the PD period to (a) restoring, (b) IW_be700, (c) IW_be100 and (d) IW_whole. The difference in the equatorial averaged (5°S–5°N) vertical gradient of climatological temperature and potential density from the PD period to (e) restoring, (f) IW_be700, (g) IW_be100 and (h) IW_whole. The shading, contour, and dashed lines indicate the temperature, potential density, and depth of the thermocline, respectively, in each experiment. Temperature values that are significant at the 95% confidence level using the bootstrap test are shown.\nLines 234-235: ‘These changes are driven by ocean stratification and El Niño-like warming, ‘. It appears twice.\nAns) Revised sentence to “These changes are driven by ocean stratification and El Niño-like warming, which enhance zonal advective, Ekman, and thermocline feedbacks in the eastern Pacific, despite increased thermal damping (Supplementary Fig. 13). Our findings consistently show that deep ocean warming is the primary driver of these ENSO changes, as observed in the IW_EXPs.”\nLine 288: How long does the current-day simulation last?\nAns) The present-day (PD) simulation was performed for a total of 900 years, and the PD period used in the analysis is defined as the last 400 years of the PD simulation. We revised the sentence to “The first simulation was a present-day scenario with a constant atmospheric CO2 concentration (at the current level of 367 ppm) for 900 years.”\nLine 309: How is the salinity anomaly profile determined?\nAns) The salinity anomaly was calculated using the same method as used for the temperature anomaly. We revised the sentence to “Additionally, horizontally uniform vertical profiles of the ocean temperature and salinity anomalies were added to the initial condition of the ocean model (year 2000). In other words, the initial temperature and salinity perturbations of IW_EXPs are horizontally identical in all ocean grids.”\nLines 379-380: Deep ocean warming induced irreversible climate changes Nature Climate Change, Nature Climate Change. For some reason, I could not find this article.\nAns) The information on the reference has been updated.\nOh, J.-H. et al. Emergent climate change patterns originating from deep ocean warming in climate mitigation scenarios. Nat. Clim. Chang. 14, 260–266 (2024).\nFig. 1 caption (b) and (c) should exchange with each other. Or, the numbering of each panel should be changed.\nAns) The Fig. 1 caption has been revised accordingly.\nResponse to Reviewer #2\nKim et al. investigated the variations in ENSO during the recovery period after intensive global warming. Generally, this study showed some interesting results helping us to deepening understanding of ENSO, based on a series of numerical experiments. But I still have some concerns, which are listed below.\nWe would like to thank the reviewer for careful and constructive suggestions, which helped to improve the quality of this manuscript. Our responses are as follows:\n1. The mitigation scenario in the title is somewhat unrelated to this study.\nAns) Thanks for pointing out this issue. As the reviewer suggested, we have revised the title of the paper to \"Deep ocean warming-induced El Niño changes\".\n2. “As the climate recovers after CO2 reaches current climate levels, the Northern Hemisphere (NH) cools much faster than the Southern Hemisphere (SH)”. (1) The authors should give evidence to support this. (2) What causes the different cooling rates? (3) And what is the relative contribution of the NH-SH contrast and the El Niño-like warming pattern to the migration of the ITCZ?\nAns for (1) and (2): Figure B shows the difference in the air temperature between the PD period and the restoring period. The temperature anomaly is higher in the Southern Hemisphere (SH) than in the Northern Hemisphere (NH), indicating that the SH cools more slowly. Kug et al. (2022) pointed out that the cooling of the SH during climate recovery is significantly delayed by its heat capacity associated with the land fraction. In addition, Oh et al. (2024) suggested that heat release from the deep ocean is stronger in the Southern Ocean, a weakly stratified background condition, which contributes to the slower cooling of the SH during climate recovery. We have added the supplementary Figure and revised the manuscript as follows :\n“As the climate recovers after CO reaches current levels, the Northern Hemisphere (NH) cools much faster than the Southern Hemisphere (SH) (Supplementary Fig. 2). The larger heat capacity of the SH (Kug et al. 2022) and the pronounced heat release from the Southern Ocean (Oh et al. 2024) contribute to a relatively slow cooling rate in the SH.”\nFig. B | The changes in the air temperature. The difference in (a) the spatial pattern and (b) the zonal averaged the air temperature from the PD period to restoring. The air temperature is vertically averaged from the surface to 300hPa.\nAns for (3): It is a bit difficult to quantify the relative contribution of the SH-NH contrast and the El Niño-like warming to the southward shift of the ITCZ, since they are closely related. However, we tried to examine the relative importance based on the inter-ensemble spread. The shift of the ITCZ index was defined as the difference in precipitation between the northern (15°-5°N, 120°E-120°W) and southern (15°-5°S, 120°E-120°W) off-equatorial regions. El Niño-like warming was defined as the mean SST in the Niño3 region (5°S-5°N, 150-90°W). The inter-hemispheric temperature contrast is defined as the difference between the tropics (0°-90°N and 90S°-0°) of the NH and SH annual mean temperature, which is vertically averaged from the surface to 300hPa. Figure C shows the inter-model relationship between El Niño-like warming, interhemispheric contrast, and the ITCZ shift. El Niño-like warming and interhemispheric contrast correlated with the southward shift of the ITCZ by 0.68 and 0.41, respectively. The results indicate that a stronger inter-hemispheric contrast and a stronger El Niño-like warming are both associated with a larger southward shift of the ITCZ. In order to compare the relative contribution of the SH-NH contrast and El Niño-like warming, partial correlation analysis is employed. The partial correlation coefficient r between two variables A and A , after removing the influence of the variable A , is given by:\nFig. C | The relationship between El Niño-like warming, interhemispheric contrast, and the shift of the ITCZ. The scatter diagram (a) between the El Niño-like warming and the shift of the ITCZ and (b) between the interhemispheric contrast and the shift of ITCZ.\n3. “The initial warming over the eastern Pacific “in line 121. The authors may show the initial warming pattern in supplementary material, which is very helpful to understanding the formation processes of the El Niño-like warming pattern.\nAns) To represent the initial SST warming pattern, we calculated for each experiment the SST difference between the PD period and the first 5 years of the experiment (Fig. D). Based on the reviewer's comment, we have added the initial warming pattern to Supplementary Fig. 4\nFig. D | The initial warming pattern of the IW experiment. The difference in SST from the PD period to the initial five-year of (a) IW_be700, (b) IW_be100, and (c) IW_whole.\n4. The authors stressed the intensification of the zonal-advection feedback. However, in previous studies, this feedback favors the CP El Niños?\nAns) As the reviewer mentioned, the zonal advection feedback is of critical importance in the CP El Niño, while the thermocline feedback represents a key process in the EP El Niño (Kug et al. 2009). However, in terms of changes in ENSO diversity, the region where the feedbacks change is more important. In response to El Niño-like warming, the wind response shifts eastward. As a result, the ocean current response intensifies in the eastern Pacific (150-120W) rather than in the central Pacific in the restoring and all IW_EXPs. (Fig E). In addition to zonal currents, vertical currents, and thermocline responses are enhanced in the eastern Pacific (Supplementary Fig. 11). Therefore, the frequency of EP El Niños increases as zonal advection in the eastern Pacific intensifies.\nFig. E | The changes in the current response. The difference of the regression coefficients of zonal current onto averaged wind stress over the equatorial Pacific (120°E–90°W, 5°S–5°N) during DJF from the PD period to (a) restoring, (b) IW_be700, (c) IW_be100 and (d) IW_whole. Only values that are significant at the 95% confidence level using the bootstrap test are shown.\n5. “The second experiment lasted 500 years and involved 28 ensemble members.” Do you mean 500*28 years of integrations were conducted?\nAns) Yes. The sentence is revised as follows:\n“The second experiment consists of 28 ensemble members with different initial conditions, for a total of 500 years in each ensemble.”\n6. “A horizontally uniform temperature anomaly profile was added to the initial ocean state”. Why uniform temperature anomalies are specified? This should be very different from those in recovery experiments.\nAns) Our intention of these experiments is to emphasize that the climatological distribution of the oceanic vertical mixing is a key in determining the deep ocean warming-induced climate changes. As the reviewer pointed out, the added globally-uniform ocean warming pattern is quite different from the actual distribution of the deep ocean warming in the restoring period. Nevertheless, the simulated tropical mean states are almost identical to those in the restoring period. This suggests that the climatological equatorial upwelling is a key to transferring the heat from the deep ocean, regardless of the horizontal distribution of the deep ocean warming.\n7. Various feedbacks were diagnosed, but the authors did not mention which seasons they analyzed\nAns) A description of the seasons was added for each Figure and supplementary caption.\nResponse to Reviewer #3\nThis study explored ENSO changes due to deep-ocean warming based on a CO2 ramp-up and ramp-down experiment and present-day experiments initialized with horizontally uniform deep-ocean heat anomalies using CESM1.2. The authors examined not only the ENSO amplitude changes but also the diversity and feedback changes.\nI have read several previous papers related to the CESM1.2 CO2 ramp-up/down experiments. This paper aims to clarify the impact of the deep-ocean heat on the hysteresis of ENSO, which is important to the ENSO community. Although the results are interesting, I have some potentially critical concerns in their analyzing method. Because the present manuscript does not sufficiently describe their method, I could not fully understand how the data was analyzed. I would like to ask the authors to revise the methodology and clarify my major concerns below.\nWe appreciate the reviewer’s careful and constructive comments. The reviewer’s comments were fully reflected in the revised manuscript, and we carefully checked and revised the manuscript. Our responses to the specific comments are as follows:\nMajor comments:\n1. The IW experiments are not at the equilibrium states, so the anomalous fields have to be carefully defined to compare with the PD experiment. The last 100 years after 50 years are analyzed in the IW experiments and the PD period (Lines 106-107). However, it is clear in Fig. 3b of Oh et al. (2024), that the SST change is not steady at all. Thus, all the anomalous fields have to be carefully defined.\nAs the mean state remains changing for 150 years, it is important to describe it and consider removing its potential impact on the anomalous fields analyzed in this study. First of all, the definition of anomalies needs to be clarified. Then, how to remove the potential background changes from the anomalies needs to be described. For example, the Niño3 SSTA std. is easy to be affected by spurious slow anomalies due to background change. The SSTA pattern in Fig. 2 is also affected by the definition. Other main and supplementary figures are also sensitive to the definition of the anomalies.\nIdeally, an initial condition large ensemble is required to define the anomalies from the changing background, but the experiments have only 9 ensembles for each of the IW experiments. Therefore, the method to define the anomaly is important.\nAns) We agree with the reviewer that defining the anomalies can be very important. Given the limited number of ensembles in the IW experiments, it is not appropriate that anomalies are defined by removing the ensemble mean to remove the inherent changing background.\nTherefore, anomalies of each ensemble were defined by removing the linear trend and the monthly mean climatology for the last 100 years.\nFurthermore, we also checked the sensitivity of our results to the definitions of anomalies. We conducted the composite analysis for the El Niño using anomalies defined as removing only the monthly mean not the linear trend. Figure F shows the SSTA difference from the PD period. The SSTA difference shows a zonal dipole pattern, showing that the equatorial eastern and western Pacific regions have opposite signs. These results are consistent with those obtained by removing the linear trend (Fig. 2b,c in the manuscript), indicating that the impact of spurious slow anomalies due to background change on the ENSO composite result is very limited.\nFollowing the reviewer's comment, how we defined anomalies is added in the method section as follows:\nDefinition of ENSO\nThe Niño3 and Niño4 SSTA, defined as the area-averaged SSTA in the Niño3 region (5°S-5°N, 150-90°W) and Niño4 region (5°S-5°N, 160°E-150°W) are used to describe the amplitude of ENSO, respectively. The SSTA was calculated by removing the linear trend and the monthly climatological mean for each experiment and ensemble. We utilize a threshold of ±1 STD of the DJF mean Niño3 SSTA during the PD period to define ENSO events. To define convective El Niño, we employed the method used in previous studies (Cai et al. 2014, 2015; Wang et al. 2017; Pathirana et al. 2023), wherein convective extreme El Niño was identified as absolute precipitation exceeding a threshold of 5 mm/day during the DJF season.\nFig. F | The changes in ENSO amplitude. The changes in the spatial pattern of El Niño SSTA during DJF from the PD period (a) IW_be700, (b) IW_be100, and (c) IW_whole. El Niño was defined using the 1 STD threshold of the DJF Niño SSTA. Stippled areas are regions that are not significant at the 95% differences of each experiment using the bootstrap test.\n2. The IW experiments are not fully described (Lines 104-105 and the Methods section), so it is not possible to reproduce the simulations based on the manuscript. (1) The method could be explained more in detail. At least, it must be clarified if the experiments are identical to the previous work (ref. 17).\nAns for (1): Thanks for asking the important point. The experiments are identical to those in Oh et al. (2024). We have described the design of the IW experiments in the Method sections in more detail as follows:\nResults\nTo investigate the influence of deep ocean warming on changes in the tropical mean state, three initial warming experiments (IW_EXPs) were conducted. Specifically, the IW_EXPs were conducted with a constant atmospheric CO level, but with horizontally uniform vertical profiles of ocean temperature and salinity anomalies added to the ocean model initial conditions. These IW_EXPs allow us to explore the impacts of deep ocean warming on the mean state of the tropical ocean and subsequent alterations in ENSO characteristics (see Methods for a detailed description of the IW_EXPs).\nDesign of the initial warming experiment\nTo investigate how deep ocean warming contributes to the change in ENSO characteristics, three types of initial warming experiments (denoted as IW_whole, IW_be100, and IW_be700) were conducted. These experiments were branched from the initial condition (year 2000) of each ensemble member and then integrated with the constant atmospheric CO concentration of 367 ppm. Additionally, horizontally uniform vertical profiles of the ocean temperature and salinity anomalies were added to the initial condition of the ocean model (year 2000). In other words, the initial temperature and salinity perturbations of IW_EXPs are horizontally identical in all ocean grids. The added initial anomalies are the global mean ocean temperature and salinity in the year 2280 when the atmospheric CO level first returns to its original level (367 ppm). Note that, in addition to the temperature profile, a salinity anomaly profile was added to prevent any potential imbalance for running the model. To isolate the role of deeper ocean warming, the initial perturbation was added to the entire depth, below 100m and below 700m in IW_whole, IW_be100, and IW_be700, respectively. All experiments were integrated for 150 years with nine ensemble members. Note that these three IW_EXPs were also used in a previous study (Oh et al. 2024, see their Fig. 3).\nAnd, (2) what are the values of the uniform temperature anomaly profile and the corresponding salinity anomaly profile? (3) How did you determine the salinity anomaly profile to avoid any potential density imbalance?\nAns for (2) and (3): As described in the Methods section, the added initial vertical profile is the global mean ocean temperature and salinity anomalies in the year 2280 when the atmospheric CO concentration first returns to its original level (367 ppm, Fig. G and H). To avoid any potential imbalance in running the model, we simply added the global mean salinity profile in addition to the temperature profile.\nTo compare the sensitivity of our results to the salinity, We conducted additional IW_whole experiments, which separately added the temperature and salinity anomalies to the initial ocean state. Figure I shows the change in SST from the PD period to the IW_whole experiment with temperature and salinity added respectively. The experiment where only the temperature was added shows a pronounced warming at the surface (Fig. Ia), with an El Niño-like warming pattern, consistent with the experiment where both temperature and salinity were added (Fig. 1 in the manuscript). In contrast, the experiment where only salinity was added shows no clear surface warming pattern (Fig. Ib). These results suggest that how to deal with the salinity anomalies does not change our main conclusion significantly.\nFig. G | Idealized CO scenario imposed in the Earth System Model experiment. The black line indicates the CO pathway with model year. Present day (PD, 1100-2000 years), ramp-up (2000-2140 years), ramp-down (2140-2280 years), and restoring period (2280-2500 years) were delineated on the figure.\nFig. H | Design and results of the initial warming experiment (Adopted from Fig 3a in Oh et al, 2024). Global mean potential temperature (red) and salinity (black) profile in year 2280 when the CO concentration first returns to the present level. These two vertical profiles are uniformly added to all ocean grids of the model’s original initial condition (year 2000 condition). The two grey horizontal lines denote the 100 m and 700 m depths, respectively. The red, blue, and yellow vertical bars indicate the depth of the initial forcing used in each experiment.\nFig. I | The changes in SST. The changes in the spatial pattern of SSTA from PD to IW_whole experiments. (a) Only horizontally uniform temperature anomaly profiles and (b) only salinity anomaly profiles were added to the initial ocean state. The SSTA was defined as the difference between the PD period and the time average of the last 100 years of the simulation.\n(4) Is there an initial condition's vertical gap at the 700-m (100-m) depth in IW_be700 (IW_be100)?\nAns for (4): In the IW_be100 and IW_be700, the initial perturbation was set to zero for the upper 100m and 700m, respectively. Therefore, as the reviewer asked, there exists a vertical discontinuity of initial perturbation at the 100m and 700m in the IW_be100 and IW_be700, respectively. We acknowledge that this discontinuity can be somewhat unrealistic. However, it seems that it may not significantly impact our overall findings, because the results are quite similar to those in the IW_whole, which utilized a complete vertical anomaly profile and yielded similar results.\n(5) The total heat content from the bottom to the surface may depend on the bottom topography, so probably the total heat content is not horizontally uniform --Does this affect the results? Because these points were unclearly written, I could not follow the detailed parts of the results.\nAns for (5): As the reviewer points out, the ocean heat content (OHC) from the bottom to the surface is not horizontally uniform due to the topography of the ocean. To investigate the effect of differences in the OHC as the topographic properties of the oceans, the OHC added as the initial forcing was divided into the above and the below 3000m (Fig. Ja, b). The OHC integrated over 3000 m shows an almost identical value over the globe, except along coastlines with low water depths. On the other hand, the ocean heat content integrated from 3000 m to the bottom is not spatially uniform, with positive values in regions of deep ocean depth, such as the northwest Pacific. To make a quantitative comparison, the ratio was defined as the OHC below 3000m relative to the OHC above 3000m (Fig. Jc). The values are between 0.1 and -0.1 in all regions, indicating that the amount of OHC below 3000 meters is relatively very small. Furthermore, its spatial pattern is not associated with SST warming (Fig.1 in the manuscript), with a pattern correlation coefficient of -0.06, which is not statistically significant. Therefore, it seems that the regional difference in OHC added to the initial condition due to ocean topography may not significantly impact our overall findings.\nFig. J | The ocean heat content. The ocean heat content (OHC) integrated from (a) the surface to 3000m and (b) 3000m to the bottom. (c) The ratio of OHC above 3000m to below 3000m. The OHC was calculated using the temperature anomalies which were added to the initial condition. The shaded unit (a) is 10 times larger than (b).\n3. Adding a schematic chart to explain the present conclusion may help readers understand what is different between the mechanism underlying ENSO changes induced by deep ocean warming and that associated with anthropogenic greenhouse warming (Lines 243-252).\nAns) Thank you for the constructive suggestions. Figure K shows the schematic chart for the mechanism of the changes in ENSO induced by greenhouse and deep ocean warming. In the second step, the process that is more dominant is indicated by a greater-than symbol, while the less dominant process is stippled. As the reviewer suggested, we have added a schematic chart to the supplementary Fig. 14 (Fig. K).\nFig. K | The schematic chart for the mechanism of the changes in ENSO. Mechanisms for El Niño changes induced by (a) the greenhouse and (b) deep ocean warming. The dominant process is indicated by a greater-than symbol, while the other is stippled. Greenhouse gas warming increases ocean surface temperatures, leading to increased ocean stratification, and consequently intensifies the ocean response in the central Pacific, promoting more frequent CP-type El Niño events. Deep ocean warming begins from a state of initially reduced stratification, limiting its stratification effect. El Niño-like warming response to deep ocean warming contributes to an eastward shift in the wind response, which reinforces the ocean response in the eastern Pacific, culminating in a higher frequency of EP-type El Niño events.\n4. The criteria for defining ENSO are not clear to me.\nIn Line 135, the authors said that \"El Niño events were defined based on 1 st.d. of the Niño3 SST.\" Are these criteria the same among the experiments? Or, did you use different thresholds in each experiment? This difference may affect the patterns of the SSTA in Fig. 2c,d,e., for example.\nAns) In the previous manuscript, the different thresholds were applied by calculating the standard deviation for each experiment and ensemble (Fig. L). As in response to comment #1, we have added a definition for El Niño events to the methods. In order to ascertain the changes in the SSTA patterns in accordance with the thresholds, the composite analysis for the El Niño was conducted using identical thresholds for all experiments. El Niño was defined using the 1 standard deviation threshold of the DJF Niño SSTA in the PD period (Fig. M). The SSTA difference shows a zonal dipole pattern, suggesting that the variability of SST in the eastern Pacific is increasing. These results are consistent with those obtained by using different thresholds for each ensemble (Fig. 2b,c in the previous manuscript). This implies that employing a distinct threshold does not significantly alter our main conclusions. Based on these results, the manuscript and figures have been fully replaced by applying identical thresholds in all experiments when defining El Niño (Fig N and O).\nFig. L | The thresholds of ENSO. The standard deviation of DJF Niño3 SSTA for each ensemble in each experiment and ensemble.\nFig. M | The changes in ENSO amplitude. The changes in the spatial pattern of El Niño SSTA during DJF from the PD period (a) restoring, (b) IW_be700, (c) IW_be100 and (d) IW_whole. El Niño was defined using the 1 STD threshold of the DJF Niño SSTA in the PD period. Stippled areas are regions that are not significant at the 95% differences of each experiment using the bootstrap test.\nFig. N | The changes in ENSO amplitude. The standard deviation of the DJF (a) Niño3 and (b) Niño4 SSTA. (c) The spatial pattern of El Niño SSTA during DJF for the PD period. El Niño was defined using the 1 STD threshold of the DJF Niño SSTA. As in (c) but for the difference from the PD period to (d) restoring and (e) IW_be700. Error bars represent the 95% confidence interval using the bootstrap test. Stippled areas are regions that are not significant at the 95% confidence level of the Student’s t-test in the PD period and for the differences of restoring and IW_be700 using the bootstrap test.\nFig. O | The changes in ENSO’s flavor. (a) Histogram (normalized occurrences) of El-Niño SSTA centers during DJF for the PD period. As in (a) but for the difference from the PD period to (b) restoring and (c) IW_be700. (d) Ratios of frequencies of CP El Niño events proportion to the total number of CP and EP El Niño events. (e) The frequency of convective El Niño defined as absolute precipitation exceeding a threshold of 5 mm/day during the DJF season. Error bars represent the 95% confidence interval using the bootstrap test.\n5. The convective El Niño is not clearly defined in the text.\nIn Line 166, the authors described \"the convective El Niño was defined as when Niño3 rainfall during the DJF season exceeds a threshold of 5 mm/day\". Do the authors mean \"Niño3 precipitation anomaly\" instead of \"the absolute precipitation\"? If the absolute precipitation in the Niño3 region is used for defining the convective El Niño, the increase of the convective El Niño event occurrences is attributed to the mean state change to a certain extent.\nAns) For convective extreme El Niño, we just adopted the definition used in previous studies (Cai et al. 2014, 2015; Wang et al. 2017; Pathirana et al. 2023), wherein convective extreme El Niño was identified as absolute precipitation exceeding a threshold of 5 mm/day during the DJF season. As in response to comment #1, we have added a definition for El Niño events to the methods.\nAs the reviewer points out, the increase in convective El Niño events is to some extent due to the change in mean state. However, the increase in extreme El Niño events is not simply due to an increase in climatological precipitation, but to an increase in the probability of deep atmospheric convection in the eastern equatorial Pacific due to the changes in the mean state change.\n6. It is unclear if there is inter-model uncertainty in the ENSO changes during the restoring period.\nIn the Introduction, the authors imply that there are multi-model datasets of CDRMIP, which can be used to investigate the inter-model uncertainty of the present key results. I would suggest the authors conduct a multi-model analysis to indicate whether the major findings are independent of the models or dependent on the models.\nAns) Based on the reviewer's comments, we analyzed the CDRMIP data and added the results to the revised manuscript and supplementary.\nTo strengthen the robustness of our findings, we further analyzed the 8 model simulations from the Carbon Dioxide Removal Model Intercomparison Project (CDRMIP)(Keller et al. 2018) of CMIP6, which has a similar experimental protocol to the simulation in this study. All of the model data are bilinearly interpolated onto a common 1°× 1° grid before analysis. The length of the recovery period (constant CO forcing period) varies among models (Table A). Note that several models provide too short restoring period to quantify significant El Niño changes.\nFigure Pa shows the difference in the temperature from the picontrol to the restoring period. The SST pattern in the MME is quite similar to the result of this study, implying that the deep ocean warming induces the El Niño-like warming in the restoring period. To check the changes in ENSO characteristics, we calculate the changes in the STD of the Niño3 SSTA from the picontrol to the restoring period (Fig Pb). Five of the eight models show an increase in the STD of the Niño3 SSTA, with four showing an increase of more than 8%. GFDL-ESM4, CESM2, and CNRM-ESM2-1 show relatively large increases, but these are not statistically significant, due to the short recovery period (Table A). The MME values show a statistically significant increase of about 7%. Convective extreme El Niño increased in all models except the MIROC-ES2L model, although CanESM5 has no value as no convective El Niño occurred in either period (Fig Pc). In particular, the top four models with large increases in the Niño3 STD show a large increase in the frequency of convective El Niño events. The MME results indicate that the number of convective extreme El Niño events has been about double during the restoring period. The CDRMIP results are overall consistent with our main results, suggesting the robustness of our results, but caution is needed for the short restoring period.\nFig. P | The changes in the tropical mean state and ENSO amplitude in CMIP6. (a) The difference in SST between the restoring and PD period. The difference in (b) the standard deviation of the DJF Niño3 SSTA and (c) the frequency of convective El Niño between the restoring and PD period. Error bars represent the 90% confidence interval using the bootstrap test. Stippled areas are regions that are not significant at the 90% confidence level for the differences of restoring and PD period using the bootstrap test.\nTable A | CMIP6 8 models list.\nModel number Model name Model year (pi-control) Model year (restoring)\nMinor comments:\nTitle: I would say that this study analyzed El Niño changes under a single climate mitigation scenario in a climate model, so saying \"under climate mitigation scenarios\" does not seem representative of the study.\nAns) We agree with the reviewer, so we have revised the title of the paper to \"Deep ocean warming-induced El Niño changes\".\nLines 24-25: This sentence is too subjective and ambiguous to describe the implications of this study.\nAns) Revised the sentence to “Our findings suggest that anthropogenic greenhouse warming will have a prolonged impact on El Niño variability through delayed deep ocean warming, even if CO stabilization is achieved.”\nLine 51: The meaning of \"residual upwelling\" is unclear.\nAns) Revised to “This irreversible warming of the SST primarily occurs in the high latitudes and the equatorial eastern Pacific, where the oceans are weakly stratified to allow vigorous heat release through both vertical upwelling and mixing from the deep ocean to the surface.”\nLine 64: I am quite unsure of the reason for citing ref. 28 (Ohba and Ueda 2009, JCLI https://doi.org/10.1175/2008JCLI2334.1).\nAns) Removed\nLine 79: What is \"the model\"? The details can be found in the Methods section, but the model name could be provided in the main text for clarity.\nAns) Revised the manuscript to “The Community Earth System Model (CESM) was run with constant atmospheric CO (restoring) after it was increased for 140 years, then symmetrically decreased (see Methods and Supplementary Fig. 1).”\nLine 129: Actually, the Niño4 SSTA st.d. is decreased in IW_whole. How did you interpret this?\nAns) Thanks for asking us an interesting point. However, it is difficult to address this issue accurately. The IW_whole also shows the largest increase in Niño3 SST. Actually, the differences from the other experiments are not statistically significant, we may need longer-term simulation to explore this issue further.\nLine 130: The Niño3 SSTA st.d. is increased more in IW_be100 and IW_whole than in IW_be700 and Restoring. Why this happened could be explained in the text.\nAns) Figure Q shows the change in SST from the PD period to the restoring period and to all IW_EXPs. The larger increase in the STD of the Niño3 SSTA is probably due to the more pronounced El Niño-like warming in IW_be100 and IW_whole. We have revised the sentence as follows: The largest increases are in the order of IW_whole, IW_be100, and IW_be700, which are proportional to the tropical mean state warming (Supplementary Fig. 3).\nFig. Q | The changes in SST. The difference in SST from the PD period to (a) restoring, (b) IW_be700, (c) IW_be100 and (d) IW_whole. Only significant values at the 95% confidence level using the bootstrap test are shown.\nLine 136-137: How to calculate the central longitude is unclear. The Method section needs to be cited here.\nAns) It simply detected the longitude at which the maximum value occurs.\nLine 137: Any figure does not describe this text. A supplementary figure needs to be provided.\nAns) Figure R shows the spatial pattern of El Niño SSTA and its equatorial mean (5°S-5°N) in the recovery period and all IW_EXPs. We have added Figure R to the supplementary Fig. 5.\nFig. R | The spatial pattern of El Niño. The spatial pattern of El Niño SSTA (shading) during DJF and its equatorial average (5°S-5°N, red line) in (a) restoring, (b) IW_700 (c) IW_be100 and (d) IW_whole. Stippled areas are regions that are not significant at the 95% confidence level of Student’s t-test.\nLines 150-151: The observational distribution is not shown in any figure.\nAns) We added the reference and revised the sentence as follows: The zonal distribution of SSTA peaks shows a bimodal structure with maxima at 155W and 115W (Fig. 3a), although the model tends to simulate more CP El Niño compared to the observational distribution (Fig. 1a-b in Shin et al. 2022).\nFigure 4: Is the figure calculated based on DJF? Please clarify the season used for this figure.\nAns) Added the season to the caption.\nLine 190: Where is the thermocline in Fig. 4a-c?\nAns) Added the thermocline depth in Fig. 4a-c.\nLine 213: Define the Niño3 index. Do you mean Niño3 SSTA? In this manuscript, the index names are confusingly mixed (e.g., Niño3, Niño3 SST, Niño3 SSTA, Niño3 index).\nAns) Revised to “Niño3 SSTA”. In addition, we have unified the expressions “SSTA” and “Niño3 SSTA” throughout the manuscript.\nLine 220: The results from the IW_be700 experiment are not mentioned yet. Figure 4f should appear in Lines 221-222.\nAns) Revised.\nFigure 2a"}, "author_response": ""}, {"round": 2, "reviewer_comments": {"reviewer_2": "The authors have solved my concerns satisfactorily. I have no further questions.", "reviewer_3": "May 2024,\nThe review of the revised manuscript \"Deep Ocean warming-induced El Niño changes\".\nI fully appreciate the substantial efforts made by the authors in addressing my concerns. The revised manuscript now includes detailed descriptions of the methods, which has certainly improved the quality of the manuscript. In particular, the authors have changed the El Nino event detections and showed that the results were essentially unchanged. Although the El Nino SSTA differences shown in Fig. 2d and 2e are a bit reduced, these changes do not affect their main results (e.g., Fig. 3 and Fig. 4). The authors have also addressed my concerns about the initial warming profiles and the anomaly definition in their reply, which are supportive to their conclusions. I also found that their new results on a CMIP6 ensemble are consistent with their main conclusions from CESM1.2 simulations (Supplementary Note and Supplementary Fig. 6), showing the robustness of their original findings. Furthermore, their new schematic figure (Supplementary Figure 14) is useful to understand what they found.\nI did not find any additional issues that need clarification, except for the changes in Fig. 4b and 4c from the previous version. I could not find the reason why the statistically significant areas in Fig. 4b and 4c became much wider compared to the previous Fig. 4b and 4c. Please confirm if the statistical test in Fig. 4b and 4c was conducted correctly."}, "author_response": "Response to Reviewer #2\nThe authors have solved my concerns satisfactorily. I have no further questions..\nWe thank the reviewer for encouraging and constructive comments which allowed us to further develop the paper.\nResponse to Reviewer #3\nI fully appreciate the substantial efforts made by the authors in addressing my concerns. The revised manuscript now includes detailed descriptions of the methods, which has certainly improved the quality of the manuscript. In particular, the authors have changed the El Nino event detections and showed that the results were essentially unchanged. Although the El Nino SSTA differences shown in Fig. 2d and 2e are a bit reduced, these changes do not affect their main results (e.g., Fig. 3 and Fig. 4). The authors have also addressed my concerns about the initial warming profiles and the anomaly definition in their reply, which are supportive to their conclusions. I also found that their new results on a CMIP6 ensemble are consistent with their main conclusions from CESM1.2 simulations (Supplementary Note and Supplementary Fig. 6), showing the robustness of their original findings. Furthermore, their new schematic figure (Supplementary Figure 14) is useful to understand what they found.\nWe would like to thank the reviewer for their thoughtful and constructive suggestions, which have helped to enhance the quality of this manuscript. The response is as follows:\nComment:\nI did not find any additional issues that need clarification, except for the changes in Fig. 4b and 4c from the previous version. I could not find the reason why the statistically significant areas in Fig. 4b and 4c became much wider compared to the previous Fig. 4b and 4c. Please confirm if the statistical test in Fig. 4b and 4c was conducted correctly.?\nAns) There was an error in the statistical significance test in the revised manuscript, so we reconducted the statistical tests for Figure 4b and c (Fig. A). The number of bootstrap runs was increased from 1,000 to 10,000, and the area of statistical significance is nearly identical to the results we firstly submitted.\nFig. A | The changes in ENSO feedback. a The regression coefficients of zonal current onto averaged wind stress over the equatorial Pacific (120°E–90°W, 5°S–5°N) during DJF for the PD period. As in a but for the difference from the PD period to b restoring and c IW_be700. The dashed line represents the climatological thermocline depth. Only significant values at the 95% confidence level using the bootstrap test are shown. d The regression coefficients of precipitation (shading) and 850hPa wind (vector) onto Niño3 SSTA during DJF for the PD period. As in d but for the difference from the PD period to e restoring and f IW_be700. Stippled areas are regions that are not significant at the 95% confidence level of the Student’s t-test in the PD period and for the differences of restoring and IW_be700 using the bootstrap test."}]

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