Early emergence and determinants of human-induced Walker circulation weakening

Domain: earth_science
Published: 2024-10-24
Editorial outcome: minor_revision

Abstract
The Walker circulation is projected to slowdown in response to greenhouse gas warming. However, detecting the impact of human activities on changes in the Walker circulation is challenging due to the significant influence of internal variability. Here, based on ensembles of multiple climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we show evidence that the emergence of the human-induced weakening of Walker circulation tends to occur earlier in the middle-upper troposphere than at the surface. This earlier emergence is attributed to a more pronounced initial weakening response of the middle-upper tropospheric Walker circulation to atmospheric CO2 radiative forcing. We further reveal that the emergence time of a weaker Walker circulation varies across models. This intermodel spread is governed by an ocean thermostat that operates by modulating the zonal sea surface temperature gradient over the tropical Indo-Pacific region. Our findings address the key question of whether and how to detect human-induced large-scale atmospheric circulation changes and provide valuable insights for assessing the associated risks.

Introduction
The Walker circulation is the most prominent large-scale zonal atmospheric circulation over the tropical Pacific, with warm-moist air rising in the west and cold-dry air descending in the east1,2. Changes in the Walker circulation can exert far-reaching impacts throughout the globe, such as shaping the regional hydroclimatic conditions3–5, regulating the monsoon variations6–8, and influencing agricultural production and ecosystems9,10. As anthropogenic forcing intensifies in the future, detecting and understanding human influences on changes in the Walker circulation emerge as one of the paramount concerns in climate sciences. Underpinning this necessitates determining when and where the human-induced Walker circulation changes will emerge from the large background of internal variability.

The primary focus of studies on the emergence time of climate change signals within the Pacific region is on detecting changes in thermodynamic variables such as temperature and precipitation11–15, but little attention has been paid to investigating changes in dynamical variables of large-scale circulations. Previous studies found that the mean sea surface temperature (SST) signal emerges earliest in the tropics and can be detected earlier in the western tropical Pacific than the east11,12,15, while the annual mean rainfall signal over the eastern Pacific is projected to emerge by the mid-21st century15. Considering the profound influence of atmospheric circulation in shaping the spatial distributions of temperature, precipitation and wind patterns, ascertaining the emergence of human-induced changes in the Walker circulation is of utmost importance for predicting extreme weather events like droughts, floods, and tropical cyclones3,16,17. However, it remains unclear when the human-induced Walker circulation change will become distinguishable from internal variability, and which factors determine the emergence time of the Walker circulation change.

Accurately estimating the emergence of human-induced Walker circulation changes depends largely on precisely evaluating its intensity changes. Previous studies mainly use indices from low-tropospheric variables, such as sea level pressure (SLP) gradient and surface zonal winds18–23, to describe the magnitude change in the Walker circulation and uncertainties in its future projections19,24–26. However, these low-level indices exhibit a notable concurrence with SST variations1,27, making it challenging to separate the Walker circulation change signal from SST-driven internal variability. While these low-level indices are widely used, they may not fully capture the complexities of the Walker circulation response to global warming, particularly in the upper troposphere. This is because compared with the lower troposphere, the upper tropical troposphere displays the most substantial intensification of water vapor and temperature warming under the anthropogenic CO2 forcing28,29. This difference in the responses between the upper troposphere and the surface may lead to differing impacts on the Walker circulation at various tropospheric levels30, resulting in distinct emergence times across these layers. Moreover, while various mechanisms have been proposed to comprehend future changes in the Walker circulation22,29–35, it is imperative to elucidate which processes actively regulate the emergence of Walker circulation changes.

In this study, we address the question of the emergence of human-induced Walker circulation changes using simulations from Coupled Model Intercomparison Project Phase 6 (CMIP6) models. We use three distinct indices (i.e., dSLP, dW500, and VPmax, see Methods) from the low-level to the middle and upper troposphere to describe the intensity of the Walker circulation. Based on these indices, we determine the time of emergence (ToE) of Walker circulation changes at different tropospheric levels, identify the multimodel-based consensus, and investigate the origin of intermodel discrepancies. We demonstrate that the ToE of the Walker circulation weakening potentially occurs earlier in the middle-upper troposphere than at the surface. An earlier ToE is also more evident in models that exhibit a stronger weakening of the zonal SST gradient after a long-term adjustment to CO2 increase.

Results
Future Walker circulation responses on different levels
The Walker circulation is projected to weaken at different tropospheric levels in a warmer future climate (Fig. 1). At the surface, an increase in low SLP over the Indo-Pacific warm pool reduces the east-west SLP gradient (Fig. 1a, b). In the middle and upper troposphere, positive trends over the western Pacific (in regions of climatological ascent) and negative trends over the eastern Pacific (in regions of climatological descent) indicate a weakening of both ascending and descending motions of the Walker circulation (Fig. 1c–f). This weakening is further supported by trends in vertical velocity, with positive values in the western Pacific and negative values in the eastern Pacific (Fig. 1g, h).

Almost all models project an overall weakening of the Walker circulation under both medium and high greenhouse gas emission scenarios based on different indices (Supplementary Fig. 1). However, changes in the Walker circulation exhibit remarkably multidecadal variations due to internal variability (Supplementary Fig. 1a, c, and e). After removing the influence of internal variability (see Methods), the externally forced signal shows a weakening trend of Walker circulation at different tropospheric levels in response to global warming (Supplementary Fig. 1b, d, f). This forced weakening happens with enhanced warming in the eastern tropical Pacific (Supplementary Fig. 2c, d) and a greater rise in the tropical mean upper tropospheric temperature (Supplementary Fig. 2e, f).

ToE of the Walker circulation change
The temporal evolution of signal-to-noise ratio (see Methods) reveals that the forced Walker circulation change is detected earlier in the middle and upper troposphere than in the lower troposphere (Fig. 2a, c and e). Under the SSP5-8.5 scenario, the multimodel ensemble mean of the forced signal is likely to exceed the range of internal variability in 2040s in the dW500 index (middle troposphere) and 2050s in the VPmax index (upper troposphere) (Fig. 2c and e), while it will not emerge until the 2080s in the dSLP index (lower troposphere) (Fig. 2a). The forced weakening of Walker circulation under the SSP2-4.5 scenario shows similar results, but with a delayed emergence period across all tropospheric levels (Fig. 2a, c and e). Moreover, there is a spread in the signal-to-noise ratio across models, gradually increasing over time (Fig. 2a, c, and e). This increased intermodel spread is explained by the increased intermodel uncertainty in the forced signal of the Walker circulation change (Supplementary Fig. 1b, d, and f).

The ToE analysis (see Methods) further confirms a higher detectability of the Walker circulation weakening in the middle and upper troposphere (Fig. 2b, d, and f). A majority of climate models (93% and 83%) exhibit detectable weakening of the Walker circulation by the end of this century based on the middle and upper tropospheric indices under the SSP5-8.5 scenario (Fig. 2d and f), whereas only approximately half of the models (53%) demonstrate detectability based on the low-level index (Fig. 2b). Furthermore, the ensemble-mean ToE appears earlier in the middle and upper troposphere (year 2050 and year 2053) compared to that at the surface (year 2070) (Supplementary Fig. 3b, d, and f). Earlier emergence of the Walker circulation weakening in the middle-upper troposphere is also found under the SSP2-4.5 scenario, but the ToE is later than that under the SSP5-8.5 scenario in models by several decades (Fig. 2b, d, f).

Factors contributing to early ToE in the middle-upper troposphere
The varying emergence time in the Walker circulation weakening at different tropospheric levels is largely attributed to the distinct signal-to-noise ratio of the Walker circulation change in response to CO2 forcing. The signal of a weaker Walker circulation emerges earliest in the middle troposphere, while it is delayed by about 30 years at the surface (Fig. 3a, c, and e). In the abrupt 4×CO2 experiment, the signal-to-noise ratio indicated by the dSLP index is of smaller magnitude compared to that of the dW500 and VPmax indices (Fig. 3a, c, and e). This lower signal-to-noise ratio for the dSLP index results in a longer time required for the signal to exceed the noise range. Consequently, the signal in the dSLP index does not surpass the noise until about 30 years later, whereas in the dW500 and VPmax indices, the signal of a weaker Walker circulation emerges much earlier (Fig. 3a, c, and e).

The spatial distribution differences in both signal magnitude and internal variability explain the variation in emergence times among the indices. At the surface, the SLP signal only emerges in the western tropical Pacific in the first 10 years of the abrupt 4×CO2 experiment (Fig. 4a). This is because the SLP strengthens over the western tropical Pacific in response to increased CO2 forcing in the first few years, with no significant change seen in the eastern tropical Indian Ocean and eastern tropical Pacific (Supplementary Fig. 4a). However, the internal variability in the latter regions is higher than that in the western tropical Pacific (Supplementary Fig. 4b). Consequently, the signal-to-noise ratio peaks in the western tropical Pacific. Therefore, the difference between the east and the west over the tropical Pacific yields a low signal-to-noise ratio in the dSLP index. In contrast, the dW500 index emerges earliest due to a stronger signal in the Maritime Continent region and the central tropical Pacific, coupled with lower internal variability in these areas (Fig. 4c, d and Supplementary Fig. 4c, d).

The stronger signal in the middle-upper troposphere is related to a larger fast weakening response in the middle-upper component of the Walker circulation in response to CO2 forcing. The temporal evolution of the Walker circulation response in all indices from the abrupt 4×CO2 experiment shows two different stages: a fast response, which refers to the response in the first few years to the abruptly imposed CO2, and a slow response, which is characterized by a longer-term adjustment (Fig. 3b, d, and f). The slow responses in all three indices display a pronounced weakening of the Walker circulation, which stabilizes after about 100 years (Fig. 3b, d, and f). However, the fast response in the surface differs from that in the middle-upper troposphere. At the surface, the weakening of the Walker circulation becomes significant after 20–30 years, while in the middle-upper troposphere, the Walker circulation weakens from the initial stage (Fig. 3b, d, and f).

The larger fast weakening of the middle and upper Walker circulation is caused by stronger radiative forcing, enhanced static stability, and slower radiative cooling in the middle and upper troposphere compared to the surface. The increased atmospheric CO2 concentration reduces infrared radiation loss more in the upper troposphere than at the surface, leading to faster warming and greater static stability at higher altitudes31,36,37. This enhanced stability weakens the middle and upper Walker circulation, as the upper troposphere stabilizes more rapidly than the lower layers36,37. As the entire troposphere warms, the moist adiabatic lapse rate disproportionately increases static stability in the upper troposphere, further suppressing buoyancy-driven motions that support the Walker circulation36,38–40. Additionally, CO2-driven warming slows the rate of radiative cooling31,37–39, weakening vertical motions in the middle and upper troposphere, leading to a significant weakening of the Walker circulation at these levels37,39. In contrast, the circulation changes near the surface are primarily influenced by boundary layer processes and surface fluxes, which are closely tied to SST changes. Hence, when the zonal SST gradient begins to decrease after about 30 years, the SLP also starts to change (Supplementary Fig. 5). The above results suggest that the mid-to-upper-level component of the Walker circulation weakens directly in response to increased atmospheric CO2 radiative forcing36, while the weakening of its surface manifestation is delayed by SST adjustment processes related to ocean dynamics. Therefore, the forced signal in Walker circulation change indicated by indices from the middle and upper troposphere is more likely to be detected earlier than the lower tropospheric indices.

Sources of intermodel uncertainty in ToE
A large spread exists in the ToE across different models (Fig. 2 and Supplementary Fig. 3). For models exhibiting ToE before 2099, the year of ToE displays a wide-ranging distribution exceeding 50 years (Supplementary Fig. 3). Specifically, the ToE shows a range of 2049–2094 (2042–2090) in the dSLP index, 2021–2091 (2015–2095) in the dW500 index, and 2026–2086 (2015–2094) in the VPmax index under the SSP5-8.5 (SSP2-4.5) scenario (Supplementary Fig. 3). Notably, certain models even indicate the absence of the Walker circulation weakening emergence (Fig. 2b, d and f).

The intermodal uncertainty in ToE likely stems from a wide range of forced signals and internal variability across different models. To analyze the source of intermodel uncertainty in the ToE, we calculate the ToE by simultaneously considering the forced signal and internal variability in all the models based on three indices (Fig. 5a, c, and e). Here we estimate the magnitude of the forced signal as the long-term trend of the forced Walker circulation change. The results show that the ToE is influenced by both internal variability and the forced signal, with an earlier ToE appearing when there is smaller internal variability and a larger forced signal (Fig. 5a, c, e and Supplementary Fig. 6a, c and e). Since the Walker circulation responds to CO2 forcing with both a fast and slow response, we examine the intermodel relationships between ToE and the fast response (Supplementary Fig. 7), ToE and the slow response (Fig. 5b, d, f and Supplementary Fig. 6b, d and f), and ToE and internal variability (Supplementary Fig. 8). The highest intermodel correlation coefficient between the ToE and the slow response suggests the major role of slow response in explaining the intermodel difference of ToE (Fig. 5b, d, f, and Supplementary Fig. 6b, d and f). The stronger the slow response is, the earlier the ToE appears, and vice versa. For models showing Walker circulation weakening but no emergence (Fig. 2b, d, f), this can be attributed to a smaller slow response rather than larger internal variability (Fig. 5 and Supplementary Fig. 8).

The slow response of the Walker circulation change is mainly determined by zonal SST gradient change (Supplementary Fig. 9), which is modulated by an ocean thermostat response. We select two subsets of models, namely Group-E (models with an earlier ToE) and Group-L (models with a later ToE), based on the occurrence time of the ToE to verify the influence of the ocean thermostat mechanism (Table S1) (see Methods). Models in Group-E show earlier ToE in all three indices while ToE in Group-L models arises later. In Group-L models, the initial SST change over the first 10 years resembles the ocean thermostat response, displaying negative SST anomalies in the central equatorial Pacific (Fig. 6a). It shows that an enhanced upwelling of cold water acts as a balancing mechanism to counter the radiative forcing caused by increased CO233–35. The cooling or suppressed warming pattern eventually shifts to an enhanced eastern equatorial Pacific warming (Fig. 6b). In Group-E models, however, immediate warming over the eastern equatorial Pacific occurs, which progressively intensifies over time (Fig. 6c, d). The results above suggest that the ocean thermostat delays the weakening of the zonal SST gradient. The transition from cooling to warming SST pattern in Group-L models delays the weakening of the Walker circulation, thus postponing the emergence of a weaker Walker circulation. However, the enhanced extratropical warming and weakened subtropical oceanic cells diminish the supply of cold water to equatorial upwelling after a longer-term of adjustment in both groups of models, resulting in a reduced zonal SST gradient30. Therefore, the difference in the magnitude of the slow response in the zonal SST gradient across models leads to intermodel uncertainty in the slow response of the Walker circulation to CO2 forcing, and consequently, in the ToE.

Methods
Models simulations
CMIP6 models simulations. Monthly outputs from 30 CMIP6 models are used in this study (Table S1). The historical runs for 1980–2014 and the future projections under the SSP2-4.5 and SSP5-8.5 scenarios for 2015–2099 are analyzed. The SSP2-4.5 scenario represents a moderate-emission pathway, with a projected radiative forcing of 4.5 W/m² by 2100. In contrast, the SSP5-8.5 scenario reflects a high-emission, fossil fuel-reliant pathway, leading to a radiative forcing of 8.5 W/m² by 210059.

We also use 24 models with 150 years simulations from the piControl experiment and abrupt 4×CO2 rise experiment to investigate the response of Walker circulation to CO2 forcing. The piControl experiment simulates pre-industrial conditions, representing the period before large-scale industrialization. In the abrupt 4×CO2 experiment, the CO2 concentration is immediately and abruptly quadrupled from the global annual mean 1850 value, allowing for the assessment of radiative forcing caused by elevated atmospheric CO2 levels60.

A 35 year period from 1980–2014 is defined as the reference period and all changes under global warming are calculated relative to this reference period in historical and future SSP scenarios. The global mean surface air temperature (GSAT) increase is computed using the near-surface air temperature measured at 2 meters, based on historical experiments, relative to the period of 1851–1910. Additionally, we use the 150 year period from the piControl experiments as the reference period for the abrupt 4×CO2 experiments. One ensemble realization per model is used to give equal weights to each model and all the model outputs are bilinearly interpolated into a 1.5°×1.5° grid before analyses.

Statistical analysis
Indices for Walker circulation intensity. Here we mainly focus on the annual-mean change of the Walker circulation. We use three indices at different levels to estimate the intensity of the Walker circulation: the sea-level pressure gradient (dSLP), the vertical velocity gradient at 500 hPa (dW500), and the maximum velocity potential at 200 hPa (VPmax). The dSLP is one of the most commonly used index tightly linked to SST gradient, which is defined as the sea-level pressure anomaly difference between the eastern (5°S–5°N, 160°–80°W) and western (5°S–5°N, 80°–160°E) tropical Pacific22. The dW500 describes the vertical motion in the ascending and descending branches of the Walker circulation, which is defined as the vertical velocity anomaly difference at 500 hPa between the Maritime Continent region (5°S–5°N, 160°–120°W) and central tropical Pacific (5°S–5°N, 100°–140°E)25. The VPmax index is defined as the maximum absolute value over 15°S–15°N, 100°–140°E in the deviation from the zonal mean for velocity potential at 200 hPa, which reflects the characteristic of the circulation in the upper troposphere25.

Estimating the signal of the Walker circulation change
The signal of modeled annual-mean change in the Walker circulation is extracted by calculating the response of Walker circulation to global warming11,15. To obtain the global warming signal, we first calculate the time series of GSAT relative to the pre-industrial period 1851–1910 (T(t)) (Supplementary Fig. 2a). We then apply a fourth order polynomial to T(t) to smooth the global warming time series, which can be written as Te(t) (Supplementary Fig. 2b). Hence, the signal of Walker circulation change, S(t), can be obtained by regressing the annual-mean Walker circulation change onto Te(t):

S(t) = aTe(t) + b (1)

where a is the regression coefficient representing the sensitivity of Walker circulation to global warming, while b represents the intercept.

ToE of Walker circulation change
The ToE of Walker circulation change is defined as the first year when the signal-to-noise ratio (S/N) becomes larger (smaller) than 1 (−1) and continues into the future if the Walker circulation strengthens (weakens) in response to global warming. The N is computed as the standard deviation of the anomaly for annual-mean Walker circulation index for the period 1851–1910, when the anthropogenic forcing was much smaller than present13.

Definition of fast and slow response
To isolate the response of Walker circulation to CO2 forcing, we compare changes in different variables from abrupt 4×CO2 experiments with that in the pre-industrial control (piControl) experiments30. We define the fast response as the mean of changes during the first 10 years, from year 1 to year 10, after imposed forcing. The slow response is defined as the mean of changes in the last 50 years. Hence, the strengthening and weakening of the Walker circulation in abrupt 4×CO2 experiment refers to a stronger or weaker Walker circulation relative to the piControl experiment.

Selection of Group-E and Group-L models
Here we categorize models into Group-E and Group-L based on the timing of ToE occurrence across all three indices. Group-E consists of the top 30% of models where ToE appears earliest across all indices, while Group-L comprises the bottom 30% of models where ToE appears latest.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Detecting when and how the climate change signal of the Walker circulation exceeds the background noise of natural variability is of great significance to the climate science research. The authors find an earlier detectable of Walker circulation changes in the middle and upper troposphere than in the sea level. This result is interesting and novel. However, I have several questions about this study, especially for the explanation about why the ToE is earlier in the middle and upper troposphere. I suggest the authors make it clearer in the paper, as well as some other issues shown below.\nMajor comments:\n1) Line 96-106, the authors indicate that the surface SLP changes is driven by the SST warming pattern, whereas the signals in the middle and upper troposphere are constrained by the hydrological cycle mechanism proposed by Held and Soden (2006). This is somewhat subjective, since changes in the sea surface and the free atmosphere can be treated as a whole, and the SST warming pattern can also drive circulation changes in the middle and upper troposphere through deep convections. For example, during the past forty years, there is a La Nina-like warming pattern, which is accompanied by a strengthened Walker circulation. So how to separate the effect of the two mechanisms clearly?\n2) Line 127-133, the authors find a different emergence time of the Walker circulation change based on different indices. What is the significance to the climate community? Which index is more reliable to represent the detectability of the Walker circulation change under global warming?\n3) Fig. 2b, d, f, are there any inter-model correlations in the different emergence times among different indices? This is important since it reflect some consistencies in representing the changes in the Walker circulation in a specific model.\n4) The authors use the abrupt 4×CO2 experiment to further explain why the surface signal (i.e., the dSLP) emerges earlier. To me, the SSP585 experiment and the 4×CO2 experiment are similar since they both have the robust external forcing. I suggest that the authors plot the time evolutions of the S/N under SSP585 run to compare with those under the abrupt 4×CO2 run as shown in Fig. 3b, d, f.\n5) Line 205-208, this explanation is intriguing. I suggest that this sentence can be extended and more evidence can be given to better support your opinion.\n6) The authors finally attribute the main sources of uncertainty in all the three indices to the zonal SST gradient changes. This seems reasonable. However, the authors also indicated that the ToE represented by dW500 and VPmax are mainly constrained by the energy balance through hydrological cycle. How to reconcile this?\n7) The last question arises when going through the conclusion part. It seems that a few models will have an ocean-atmosphere decoupled period in the fast response. Therefore, a key question emerges that when the effect of the zonal SST gradient changes can be reached on the middle and upper tropospheric circulation changes? The authors can have a discussion about this.\nMinor comments:\n1. Line 96-97, I cannot find any El Nino-like warming in Fig. 1c-d.\n2. Line 97-98, Fig. 1g-h should be Fig. 1a-b. In addition, are you sure that the SLP over the Indo-Pacific warm pool is decreased in response to the reduced zonal SST gradient?\n3. Extended Data Fig. 1e, f, a typo, should be VPmax.\n4. Extended Data Fig. 1a, b, how about the meaning of the red shading?", "reviewer_2": "Review of\n\"Early emergence and determinants of human-induced Walker circulation weakening\" by Mingna Wu, Chao Li, Matthew Collins, et al. for Nature Communications.\nSummary: I found the topic of this paper to be very interesting and I think many people will be interested. Although there are several typos and the logic in some places is hard to follow, overall the paper is pretty well written. The authors ask many good questions and have done some nice analysis. The future state of the Walker Circulation and its impacts on society is a key question when trying to anticipate the future. This paper shows that the response of the Walker Circulation to warming experiments has different time scales at different atmospheric heights and for different atmospheric variables. This is shown in the context of CMIP6 models.\nCritique: This seemed like a paper that is largely diagnostic in nature. Several patterns and characteristics were noted, but I was left with many questions and not much of a physical understanding of what is being shown or why it is occurring. I would like to know how much of future changes in the Walker circulation will be due to anthropogenic forcing but I find myself not quite convinced that this analysis has fully answered that question. It is a challenging question.\nGeneral Notes:\n- It doesn’t appear that ‘GSAT’ is ever clearly defined. Anyone with motivation can look this up in the CMIP6 info as the global surface air temperature, but it should also be clearly defined in your paper.\n- This work relies heavily on some of the future projection scenarios from CMIP6 (SSP2-4.5 and SSP5-8.5). The scenarios are not described at all in the methods section and therefore attentive readers are left with many questions. For thoroughness I think that the piControl and abrupt4xCO2 experiments should be described in the methods section. Most people have either no knowledge of the details of these experiments or only a very incomplete understanding of them. I think a few paragraphs of clarification in the methods section of the paper would be very helpful.\n- What is the p value in Figure 5 panels? Statisticians probably know but it should be clear to the general reader and this definition is never given.\n- Why is the term ‘human induced’ used instead of ‘anthropogenic’? Is there a particular reason to not use the common term?\n- There are several fairly obvious spelling or grammatical typos that need to be corrected (e.g. in the axis labels of Extended Data Figure 8). I suggest that the full paper be read carefully again to correct these mistakes.\nMain Concern:\n1. The analysis in this paper focuses on CMIP6 models and what happens to them under various future emissions scenarios. The authors note that there is a discrepancy between observations and models concerning what the Walker Circulation (WC) is expected to do in the future and has done over the past 40 years, but in my opinion this concern is not adequately discussed. The authors seem to be implying confidently that the models are accurately projecting the future changes of the WC. I think the key issue in this debate is that coupled climate models struggle to produce the SST patterns that have been observed over the past 10-40 years in the tropical Pacific. So while this could simply be a manifestation of internal variability, we don’t have much reason to think the models are representing the internal variability of the Earth system correctly. Is this what they are trying to imply by their comments on internal variability? That the observations represent internal variability? If so, that doesn’t seem to have been stated yet.\n2. Some elements of the logic are not complete, or not convincing. Many grand claims are made, and then not fully explained or backed up with the figures. I think this is partly because many of the details in the analysis have been left out or pushed into the methods section at the end. It also seems like there is a substantial amount of relevant literature that is not referenced here, which would help to interpret the results. For example, Bony et al., 2013(on the fast CO2 forcing response), and Betts, 1998 (Climate-convection feedbacks: Some further issues. Climate Change, 39, 35-38).\nLine by line comments:\nLine 25: Is this shown in the paper? If not, it should either be clearly cited or not stated. The same is true all the way through line 29. On reading over the paper I am not yet convinced of the claims in these lines.\nLine 51: What are ‘emergence studies’? Is that a thing or did they just make up this phrase? I can guess what you mean by this term, but I shouldn’t have to guess, it should be clearly stated.\nLines 65-66: “Accurately estimating the emergence of human-induced Walker circulation changes hinges on…”. The authors state that this depends on ‘precisely evaluating its intensity changes’, but simply knowing how the intensity changes over time does not clearly indicated if the changes are human-induced or otherwise driven (internal variability, etc.). I assume that determining the emergence of anthropogenic signals will hinge on the clear identification of internal variability, and then measuring how the total signal differs from this. Because of the inherent uncertainty of internal variability, this sounds very challenging.\nLines 65-80: I think this paragraph would be more clear if it was restructured a bit. The statements about the discrepancy between observations and projections of changes in the Walker circulation (70-73) seems to be randomly slipped into the discussion about low-level verses upper tropospheric variables, and is thus confusing. Are you trying to make the argument that the disparity between observed and simulated changes is related to metrics that are based on the low-level verses upper level variables? I don’t think that is your argument, and so I think lines 70-73 should be in a different spot.\nLines 70-72: Suggestion: Observations of lower-tropospheric WC metrics suggest a strengthening WC since the 1980’s while models tend to project a weaker WC.\nLine 75-76: I don’t think you have sufficiently explained what disparity in vertical profile you are discussing here.\nLine 100-106…. Is it really necessary to distinguish different mechanisms at different levels? Does this make sense scientifically? What do we gain from such a paradigm? Line 99-106 seems to be discussing the mechanism for circulation slow-down that was discussed by Held and Soden, 2006, but I think the description of this mechanism has some issues. First, the mid-tropospheric circulation is quite different from the circulation between the BL and the troposphere…. Second, the hydrologic sensitivity is not measured by omega_500 but by precipitation and the ratio of water vapor. Measuring the change of precipitation in this context, in the mid-troposphere, doesn’t really seem to make sense. For more clarity on the various ways that overturning circulations have been measured and discussed in the literature you could look at several relevant papers (Jeevanjee, 2022 (Three Rules for the Decrease of Tropical Convection With Global Warming); Jenney et al., 2020 (Understanding the response of tropical ascent to warming…); Silvers et al., 2023 (The Response of the Large-Scale Tropical Circulation to Warming)).\nLine 137: What does this really mean? Why is there increased intermodel uncertainty in response to the external forcings? Perhaps this is a naïve thought, but I would have guessed that that the spread of the signal to noise ratio would decrease over time because the signal is presumably increasing while the noise\nLine 194: Is the fast weakening response really ‘more robust’ or is it simply different? More robust than what? What do you mean by robust?\nLine 195: PWC seems to have not been defined.\nLine 199: ‘after a longer-term adjustment’; I am confused here. I thought the slow response was the long-term adjustment, not something that comes after the long-term adjustment.\nLine 213: Are you referring to a direct response to increased CO2 forcing or simply to the fact that CO2 has increased in these experiments? Cite, Bony et al., 2013.\nLine 244-245: Is this true by construction of your definitions? If so then it doesn’t really tell us anything new.\nLine 250: You should explain the meaning of the names of Group-E or Group-L when they are first introduced?\nLine 267-269: This is probably one of the key results of the paper. Has this been shown before? By Heede et al., for example?\nLine 269: This sentence should probably be rewritten. Just tacking, ‘hence the ToE’ onto the end of the sentence doesn’t really work grammatically.\nLine 298-299: Your results show this in CMIP6 models, but not in general. This should be noted.\nLine 358: typically 1850-1910 is not considered to be preindustrial. I thought the cutoff was either 1850 or 1870. If you want to use a period that extends up to 1910 perhaps the description or language needs to change."}, "author_response": "Response to reviewers’ comments of NCOMMS-24-30437-T “Early emergence and determinants of human-induced Walker circulation weakening”\nWe appreciate to the reviewers for all the constructive comments that helped us to improve the manuscript. We have addressed the comments from the two reviewers and revised the manuscript based on their suggestions. Please see our point-by-point response below. In the following, the reviewer’s comments are written in black, followed by our response in blue.\nResponse to Reviewer #1:\nRemarks to the Author:\nDetecting when and how the climate change signal of the Walker circulation exceeds the background noise of natural variability is of great significance to the climate science research. The authors find an earlier detectable of Walker circulation changes in the middle and upper troposphere than in the sea level. This result is interesting and novel. However, I have several questions about this study, especially for the explanation about why the ToE is earlier in the middle and upper troposphere. I suggest the authors make it clearer in the paper, as well as some other issues shown below.\nWe appreciate to the reviewer for all the encouraging and constructive comments that helped us to improve the manuscript. In the revision, we have thoroughly revised the manuscript.\nWe would like to address that the earlier ToE in the middle and upper troposphere is due to both statistical and physical factors. The statistical reason is that the ToE is determined by the signal-to-noise ratio, which depends on both the magnitude of the signal and the noise. The signal-to-noise ratio indicated by the surface index is smaller compared to that of the mid- and upper-level indices, resulting in a longer time required for the signal to exceed the threshold. The physical explanation is that the Walker circulation near the surface is primarily driven by boundary layer processes and surface fluxes linked to SST changes, while the middle and upper troposphere respond more quickly to direct CO₂ radiative forcing. Stronger warming, increased static stability, and reduced radiative cooling at these levels cause the weakening signal of the Walker circulation to emerge earlier than at the surface. We have clarified these points in the “Factors contributing to early ToE in the middle-upper troposphere” section.\nWe believe the discussions regarding the reasons for an earlier ToE in the middle and upper troposphere are now clear and help further convince readers of our conclusions.\nMajor comments:\n1) Line 96-106, the authors indicate that the surface SLP changes is driven by the SST warming pattern, whereas the signals in the middle and upper troposphere are constrained by the hydrological cycle mechanism proposed by Held and Soden (2006).\n1 / 20\nThis is somewhat subjective, since changes in the sea surface and the free atmosphere can be treated as a whole, and the SST warming pattern can also drive circulation changes in the middle and upper troposphere through deep convections. For example, during the past forty years, there is a La Nina-like warming pattern, which is accompanied by a strengthened Walker circulation. So how to separate the effect of the two mechanisms clearly?\nThanks for your comments. As you mentioned, the weakening of the Walker circulation arises from a variety of mechanisms, and it is quite challenging to clearly separate different mechanisms based solely on SSP projection experiments. Based on your comments, as well as those from Reviewer #2 regarding “Lines 100-106”, we believe that it is unnecessary to distinguish different mechanisms at different tropospheric levels. Therefore, we have revised this section to present the projection of Walker circulation at different tropospheric levels in L92–100. The mechanisms related to a stronger mid- and upper-tropospheric Walker circulation weakening signal have been moved to the “Factors contributing to early ToE in the middle-upper troposphere” section.\nL92–100: “The Walker circulation is projected to weaken at different tropospheric levels in a warmer future climate (Fig. 1). At the surface, an increase in low SLP over the Indo-Pacific warm pool reduces the east-west SLP gradient (Fig. 1a–b). In the middle and upper troposphere, positive trends over the western Pacific (in regions of climatological ascent) and negative trends over the eastern Pacific (in regions of climatological descent) indicate a weakening of both ascending and descending motions of the Walker circulation (Fig. 1c–f). This weakening is further supported by trends in vertical velocity, with positive values in the western Pacific and negative values in the eastern Pacific (Fig. 1g–h)”.\n2) Line 127-133, the authors find a different emergence time of the Walker circulation change based on different indices. What is the significance to the climate community? Which index is more reliable to represent the detectability of the Walker circulation change under global warming?\nIn this study, we emphasize that the earlier ToE in the middle and upper troposphere is due to both statistical and physical factors. Apart from the statistical factors discussed in our previous manuscript, we now highlight the significance of the vertical warming pattern. In addition to the El Niño-like warming over the eastern tropical Pacific, the temperature response to increasing CO concentrations also includes a vertical rise in\n2\nthe tropical mean upper tropospheric temperature. This distinct three-dimensional spatial pattern in temperature changes is a key contributor to the weakening of the Walker circulation.\nThe significance for the climate community is that the increased tropical mean upper tropospheric temperature, as represented in climate models, is more certain than change in the zonal SST gradient. This means that indices from the middle and upper\n2 / 20\ntroposphere, which respond more directly to radiative forcing, offer an earlier indication of Walker circulation changes under global warming compared to those based on lower tropospheric variables, which are more influenced by surface processes and ocean dynamics.\nThus, the mid- and upper-troposphere variables are particularly important for early detection of Walker circulation changes, and focusing on these layers provides a clearer signal of anthropogenic impacts on large-scale atmospheric circulations. Furthermore, while all the indices we used are physically consistent and provide valuable insights, we would suggest prioritizing those from the middle and upper troposphere for detecting Walker circulation changes under global warming, as they present the earliest signal. Based on your comments, we have added a discussion on this point in L302–321 of the revision.\nL302–321: “We emphasize that the earlier ToE in the middle and upper troposphere is due to both statistical and physical factors. The ToE is determined by the signal-to-noise ratio, which depends on both the magnitude of the signal and the noise.\nThe signal-to-noise ratio indicated by the surface index is smaller compared to that of the mid- and upper-level indices, resulting in a longer time required for the signal to exceed the threshold. Moreover, in addition to the El Niño-like warming over the eastern tropical Pacific, the temperature response to increasing CO\n2\nconcentrations also includes a vertical rise in the tropical mean upper tropospheric temperature. This distinct three-dimensional spatial pattern in temperature changes contributes to the weakening of the Walker circulation. Because climate models exhibit higher certainty in projecting the increase in tropical mean upper tropospheric temperature compared to changes in the zonal SST gradient, the forced signal of Walker circulation change—reflected in middle and upper troposphere variables—is more robust and thus more likely to be detected earlier than signals derived from lower tropospheric variables. This underscores the need for greater focus on middle and upper tropospheric variables for early detection of human-induced changes in tropical large-scale atmospheric circulations. While all the indices are physically consistent and provide valuable insights, we suggest prioritizing those from the middle and upper troposphere for detecting Walker circulation changes under global warming, as they present the earliest signal”.\n3) Fig. 2b, d, f, are there any inter-model correlations in the different emergence times among different indices? This is important since it reflect some consistencies in representing the changes in the Walker circulation in a specific model.\nTo address your concern, we have calculated the intermodel correlations in ToE across different indices (Fig. R1-1). The results show that a significant intermodel correlation exists only between the dSLP (i.e., low-level) and dW500 (i.e., mid-level) indices (Fig. R1-1a–c). Given that the ToE is influenced by both the signal (i.e., externally-forced change) and noise (i.e., internal variability), we further examined the intermodel relationships for the signal and noise among the three indices (Fig. R1-1d–i).\n3 / 20\nSignificant intermodel correlations were found among the three indices for both the signal and noise (Fig. R1-1d–i). However, the intermodel correlation between the dSLP and dW500 indices is overall stronger (Fig. R1-1d and g), suggesting that the low- and mid-level indices are more closely related across individual models. Therefore, the significant intermodel correlation in ToE between the low- and mid-level indices is driven by their strong intermodel correlation in both the signal and noise. The ToE involves the ratio of a signal variable to a noise variable, even for variables that are dynamically or physically related. The above results indicate that there is consistency in how individual models represent changes in the Walker circulation in both the signal and noise, although this consistency is only observed in the low- and mid-level indices in ToE.\nFig. R1-1 Intermodel relationships among different indices under the SSP5-8.5 scenario. a, dSLP and dW500, b, dSLP and VPmax, and c, dW500 and VPmax for ToE. d–f and g–i are the same as a–c, but for signal and noise, respectively. The numbers in parentheses denote the intermodel correlation coefficients.\n4 / 20\n4) The authors use the abrupt 4×CO2 experiment to further explain why the surface signal (i.e., the dSLP) emerges earlier. To me, the SSP585 experiment and the 4×CO2 experiment are similar since they both have the robust external forcing. I suggest that the authors plot the time evolutions of the S/N under SSP585 run to compare with those under the abrupt 4×CO2 run as shown in Fig. 3b, d, f.\nThanks for your suggestion. The abrupt 4×CO₂ simulations are idealized experiments that provide valuable insights into the fundamental and immediate responses of the climate system to a sudden increase in CO₂ levels. In contrast, SSP5-8.5 scenario simulations offer realistic projections of future climate conditions under a high-emission scenario, incorporating various socioeconomic and environmental factors. In this study, because the SSP5-8.5 simulations are transient and involve gradual increases in CO₂, we use abrupt 4×CO₂ simulations to understand the fast and slow adjustments of the Walker circulation to sudden CO₂ forcing. The time evolution of the signal-to-noise ratio under the SSP5-8.5 scenario has been displayed in Figure 2a, c and e (please see the red lines and shadings).\n5) Line 205-208, this explanation is intriguing. I suggest that this sentence can be extended and more evidence can be given to better support your opinion.\nThanks for raising the question here. In the revision, we show the physical explanation on why the weakening signal of the Walker circulation appears earlier in the middle and upper troposphere. This is because the Walker circulation is primarily influenced by boundary layer processes and surface fluxes near the surface (which are closely tied to SST changes), while the middle and upper troposphere respond quickly to direct radiative forcing of increased atmospheric CO concentration. The combined effects of\n2\nstronger warming, increased static stability, and reduced radiative cooling in the middle and upper troposphere cause weakening signal of the Walker circulation at these levels to appear earlier compared to near the surface.\nFirstly, the increase in atmospheric CO forcing causes a greater reduction in infrared\n2\nradiation loss to space in the upper troposphere than at the surface. This leads to faster warming and increased static stability in the upper layers of the atmosphere, which weakens vertical motions as the upper troposphere stabilizes more quickly than the lower layers (Held and Soden, 2006; Bony et al., 2013; Jeevanjee, 2022). Secondly, as the entire troposphere warms, the moist adiabatic lapse rate results in a disproportionate increase in static stability in the upper troposphere compared to the lower levels. This heightened stability further suppresses buoyancy-driven vertical motions, which are key to maintaining the strength of the Walker circulation (Betts et al., 1998; Bony et al., 2013; Jenney et al., 2020; Silvers et al., 2023). Moreover, CO -driven warming also\n2\nslows down the rate of radiative cooling (Held and Soden, 2006; Jenney et al., 2020; Jeevanjee, 2022; Silvers et al., 2023), which is crucial for sustaining convective circulation. The reduced radiative cooling diminishes the strength of vertical motions, particularly in the mid-troposphere, contributing to a significant weakening of the Walker circulation at these levels (Jeevanjee, 2022; Silvers et al., 2023). We have clarified these points and expanded this discussion in L211–232 of the revised manuscript.\n5 / 20\nL211–232: “The larger fast weakening of the middle and upper Walker circulation is caused by stronger radiative forcing, enhanced static stability, and slower radiative cooling in the mid- and upper troposphere compared to the surface. The increased atmospheric CO concentration reduces infrared radiation loss more in\n2\nthe upper troposphere than at the surface, leading to faster warming and greater static stability at higher altitudes31,36,37. This enhanced stability weakens the middle and upper Walker circulation, as the upper troposphere stabilizes more rapidly than the lower layers36,37. As the entire troposphere warms, the moist adiabatic lapse rate disproportionately increases static stability in the upper troposphere, further suppressing buoyancy-driven motions that support the Walker circulation36,38-40. Additionally, CO -driven warming slows the rate of radiative cooling31,37-39,\n2\nweakening vertical motions in the mid- and upper troposphere, leading to a significant weakening of the Walker circulation at these levels37,39. In contrast, the circulation changes near the surface are primarily influenced by boundary layer processes and surface fluxes, which are closely tied to SST changes. Hence, when the zonal SST gradient begins to decrease after about 30 years, the SLP also starts to change (Extended Data Fig. 5). The above results suggest that the mid-to-upper-level component of the Walker circulation weakens directly in response to increased atmospheric CO radiative forcing36, while the weakening of its surface\n2\nmanifestation is delayed by SST adjustment processes related to ocean dynamics. Therefore, the forced signal in Walker circulation change indicated by indices from the middle and upper troposphere is more likely to be detected earlier than the lower tropospheric indices”.\n6) The authors finally attribute the main sources of uncertainty in all the three indices to the zonal SST gradient changes. This seems reasonable. However, the authors also indicated that the ToE represented by dW500 and VPmax are mainly constrained by the energy balance through hydrological cycle. How to reconcile this?\nThanks for your question. Both the reduced zonal SST gradient and the energy balance through the hydrological cycle contribute to the weakening of the middle and upper components of the Walker circulation, but they operate on different timescales. The hydrological constraint mechanism, driven by convective processes in the free troposphere, responds promptly to increased CO₂ forcing and affects the weakening of the Walker circulation during the fast response stage. This is why the weakening of the Walker circulation, as described by indices such as dW500 and VPmax, is primarily constrained by the energy balance through the hydrological cycle at this stage.\nAfter about 30 years, the zonal SST gradient begins to decrease (Extended Data Fig. 5), and its impact on the middle and upper Walker circulation starts to enhance during the slow response stage. Therefore, the intermodel spread in the zonal SST gradient, which emerges later, leads to the intermodel spread in the Walker circulation weakening during the slow response stage in all three indices (Extended Data Fig. 9) and, consequently, contributes to the uncertainty in the ToE across models (Fig. 5 and Extended Data Fig. 6).\n6 / 20\nTherefore, while the energy balance plays a critical role in constraining the middle and upper Walker circulation weakening for dW500 and VPmax during the fast response stage, the zonal SST gradient becomes the dominant factor contributing to model uncertainty in Walker circulation weakening as the system progresses to the slow response stage.\n7) The last question arises when going through the conclusion part. It seems that a few models will have an ocean-atmosphere decoupled period in the fast response. Therefore, a key question emerges that when the effect of the zonal SST gradient changes can be reached on the middle and upper tropospheric circulation changes? The authors can have a discussion about this.\nTo address your concern, we analyzed the timescales of correlation coefficients between the zonal SST gradient and different Walker circulation indices in the abrupt 4×CO\n2\nexperiment (Fig. R1-2). The results show that the zonal SST gradient can impact the middle and upper troposphere at short timescales. However, after about 50 years, the correlation between the zonal SST gradient and the middle and upper indices stabilizes at a high level, while its correlation with the surface index remains the highest across all timescales. This suggests that changes in the zonal SST gradient could have a stable impact on the middle and upper troposphere after about 50 years. Based on your suggestion, we have added some discussion about this point in L352–358 in the revision.\nL352–358: “We further analyze the timescales of the correlation coefficients between the zonal SST gradient and different Walker circulation indices to determine when the zonal SST gradient can exert stable impacts on the middle and upper troposphere (Extended Data Fig. 11). The results show that after about 50 years, the correlation between the zonal SST gradient and the middle and upper indices stabilizes at a high level, while its correlation with the surface index remains consistently the highest across all timescales”.\nFig. R1-2 (Extended Data Fig. 11 in the revision) Timescale for the correlation coefficients between the zonal SST gradient and different Walker circulation indices. The yellow, red, and blue lines denote the correlation coefficients between the\n7 / 20\nzonal SST gradient (dSST) and the dSLP index, dW500 index, and VPmax index at different timescales in abrupt4×CO2 experiment, respectively. Shown are the ensemble means of ACCESS-CM2, CNRM-ESM2-1, CNRM-CM6-1-HR, and MPI-ESM1-2-LR.\nMinor comments:\n1. Line 96-97, I cannot find any El Nino-like warming in Fig. 1c-d.\nWe apologize for the incorrect citation. The SST changes in Fig. 1 have now been removed to improve the flow of the logic.\n2. Line 97-98, Fig. 1g-h should be Fig. 1a-b. In addition, are you sure that the SLP over the Indo-Pacific warm pool is decreased in response to the reduced zonal SST gradient?\nWe apologize for the typos. We have corrected the citation to “Fig. 1a–b”. As for your second concern, the sentence has been revised into “At the surface, an increase in low SLP over the Indo-Pacific warm pool reduces the east-west SLP gradient (Fig. 1a–b)”.\n3. Extended Data Fig. 1e, f, a typo, should be VPmax.\nDone.\n4. Extended Data Fig. 1a, b, how about the meaning of the red shading?\nThe red shading in Extended Data Fig. 1 indicates the model spread under the SSP8-8.5 scenario. We have modified this point to make it clearer.\n8 / 20\nResponse to Reviewer #2:\nRemarks to the Author:\nReview of \"Early emergence and determinants of human-induced Walker circulation weakening\" by Mingna Wu, Chao Li, Matthew Collins, et al. for Nature Communications.\nSummary: I found the topic of this paper to be very interesting and I think many people will be interested. Although there are several typos and the logic in some places is hard to follow, overall the paper is pretty well written. The authors ask many good questions and have done some nice analysis. The future state of the Walker Circulation and its impacts on society is a key question when trying to anticipate the future. This paper shows that the response of the Walker Circulation to warming experiments has different time scales at different atmospheric heights and for different atmospheric variables. This is shown in the context of CMIP6 models.\nWe would like to express our appreciation to the reviewer for these encouraging comments.\nCritique: This seemed like a paper that is largely diagnostic in nature. Several patterns and characteristics were noted, but I was left with many questions and not much of a physical understanding of what is being shown or why it is occurring. I would like to know how much of future changes in the Walker circulation will be due to anthropogenic forcing but I find myself not quite convinced that this analysis has fully answered that question. It is a challenging question.\nBased on the reviewer’s comments, we have added discussions to enhance the physical understanding of our results. As the reviewer mentioned, determining how much of the future changes in the Walker circulation can be attributed to anthropogenic forcing is quite challenging, and we hope that our results are now more convincing.\nWe would like to address that the earlier ToE in the middle and upper troposphere is due to both statistical and physical factors. The statistical reason is that the ToE is determined by the signal-to-noise ratio, which depends on both the magnitude of the signal and the noise. The signal-to-noise ratio indicated by the surface index is smaller compared to that of the mid- and upper-level indices, resulting in a longer time required for the signal to exceed the threshold. The physical explanation is that the Walker circulation near the surface is primarily driven by boundary layer processes and surface fluxes linked to SST changes, while the middle and upper troposphere respond more quickly to direct CO radiative forcing. Stronger warming, increased static stability, and\n2\nreduced radiative cooling at these levels cause the weakening signal of the Walker circulation to emerge earlier than at the surface. We have clarified these points in the “Factors contributing to early ToE in the middle-upper troposphere” section.\nWe have also thoroughly revised the manuscript to improve its readability and logical flow. We believe that the revised paper is clearer and more understandable for readers.\n9 / 20\nGeneral Notes:\n- It doesn’t appear that ‘GSAT’ is ever clearly defined. Anyone with motivation can look this up in the CMIP6 info as the global surface air temperature, but it should also be clearly defined in your paper.\n“GSAT” refers to global mean surface air temperature, which is calculated using the near-surface air temperature at 2 meters. We have clarified this definition in L441–442 in the revised manuscript.\n- This work relies heavily on some of the future projection scenarios from CMIP6 (SSP2-4.5 and SSP5-8.5). The scenarios are not described at all in the methods section and therefore attentive readers are left with many questions. For thoroughness I think that the piControl and abrupt4xCO2 experiments should be described in the methods section. Most people have either no knowledge of the details of these experiments or only a very incomplete understanding of them. I think a few paragraphs of clarification in the methods section of the paper would be very helpful.\nThanks for your comments. Based on your suggestion, we have reconstructed the CMIP6 model simulations section and added several sentences to describe the SSP2-4.5 and SSP5-8.5 scenarios, the piControl experiments, and the abrupt4×CO\n2\nexperiments. Please see L398–401 and L404–408 in the revised manuscript.\nL398–401: “The SSP2-4.5 scenario represents a moderate-emission pathway, with a projected radiative forcing of 4.5 W/m² by 2100. In contrast, the SSP5-8.5 scenario reflects a high-emission, fossil fuel-reliant pathway, leading to a radiative forcing of 8.5 W/m² by 210060”.\nL404–408: “The piControl experiment simulates pre-industrial conditions, representing the period before large-scale industrialization. In the abrupt4×CO\n2\nexperiment, the CO concentration is immediately and abruptly quadrupled from\n2\nthe global annual mean 1850 value, allowing for the assessment of radiative forcing caused by elevated atmospheric CO levels61”.\n2\n- What is the p value in Figure 5 panels? Statisticians probably know but it should be clear to the general reader and this definition is never given.\nThe p-value in Figure 5 represents the probability of an event occurring. A p-value below 0.01 suggests at least 99% confidence in the result. In the context of linear correlation, p < 0.01 indicates a strong (or significant) linear relationship between two variables. Based on your suggestion, we have explained the statistical meaning of the p-value in L264–265 in the revised manuscript.\nL264–265: “The intermodel correlation coefficient and p-value are shown in the upper-left corner of the panels, with p < 0.01 denoting a significant correlation”.\n- Why is the term ‘human induced’ used instead of ‘anthropogenic’? Is there a particular\n10 / 20\nreason to not use the common term?\nBoth terms are often used in climate change science. Here we use “human-induced” instead of “anthropogenic” because the former is more general and easier to understand, while the latter is more specialized.\n- There are several fairly obvious spelling or grammatical typos that need to be corrected (e.g. in the axis labels of Extended Data Figure 8). I suggest that the full paper be read carefully again to correct these mistakes.\nThanks for your comments. We have corrected the typo in the y-axis label of Extended Data Figure 8 (Extended Data Fig. 9 in the revision). We have also read carefully again through the full paper and corrected some typos.\nMain Concern:\n1. The analysis in this paper focuses on CMIP6 models and what happens to them under various future emissions scenarios. The authors note that there is a discrepancy between observations and models concerning what the Walker Circulation (WC) is expected to do in the future and has done over the past 40 years, but in my opinion this concern is not adequately discussed. The authors seem to be implying confidently that the models are accurately projecting the future changes of the WC. I think the key issue in this debate is that coupled climate models struggle to produce the SST patterns that have been observed over the past 10-40 years in the tropical Pacific. So while this could simply be a manifestation of internal variability, we don’t have much reason to think the models are representing the internal variability of the Earth system correctly. Is this what they are trying to imply by their comments on internal variability? That the observations represent internal variability? If so, that doesn’t seem to have been stated yet.\nIn our study, we acknowledge that there is a notable discrepancy between the observed strengthening of the Walker circulation over the past 40 years and the weakening trend projected by most coupled climate models. This discrepancy arises from several factors, including internal variability, model errors, and potential underestimation of the forced response to external forcings (Watanabe et al., 2024).\nInternal variability, particularly modes like the PDO and IPO, has significantly contributed to the observed strengthening of the Walker circulation in recent decades (Chung et al., 2019; England et al., 2014; Wu et al., 2021). As you pointed out, models often struggle to accurately represent this internal variability (Wu et al., 2021), which can lead to discrepancies between observed and modeled Walker circulation changes. We agree that the observed strengthening may be partly due to internal variability that models do not fully capture.\nMoreover, recent studies demonstrate that internal variability alone cannot fully explain the observed Walker circulation strengthening, and external forcing also plays a role\n11 / 20\nin recent decades (Heede & Fedorov, 2021, 2023). For example, the fast response of tropical Pacific SST to CO forcing—characterized by an enhanced zonal SST gradient and a strengthened\nBased on your comments, we have revised and expanded the discussion of this topic in L369–385.\nL369–385: “Another notable issue is that current climate models fail to replicate the recent Walker circulation strengthening in observations19,23,41,50. This long-standing conundrum has brought the robustness of the future projection of a weaker Walker circulation into question. This discrepancy arises from several factors, including internal variability, potential underestimation of the forced response to external forcings, and model errors55. Internal variability, particularly modes like the PDO and IPO, has significantly contributed to the observed strengthening of the Walker circulation in recent decades19,50,56. Models often struggle to accurately represent this internal variability23, leading to discrepancies between observed and modeled Walker circulation changes. Moreover, models may potentially underestimate the forced response, such as the fast strengthening response of the Walker circulation to global warming34,52. Additionally, model errors in simulating the tropical Pacific35 or Atlantic ocean20 mean states and the subtropical cloud feedback57 may contribute to this discrepancy by underestimating inter-basin interactions and the effects of Southern Ocean cooling54. Considering all the factors mentioned above, we acknowledge that the actual emergence time of Walker circulation weakening may occur later than projected by models, but first be detected in the middle to upper troposphere”.\nReferences:\nChung, E.-S. et al. Reconciling opposing Walker circulation trends in observations and model projections. Nat. Clim. Change 9, 405-412, doi:10.1038/s41558-019-0446-4 (2019).\nEngland, M. H. et al. Recent intensification of wind-driven circulation in the Pacific and the ongoing warming hiatus. Nat. Clim. Change 4, 222-227, doi:10.1038/nclimate2106 (2014).\nHeede, U. K. & Fedorov, A. V. Eastern equatorial Pacific warming delayed by aerosols and thermostat response to CO2 increase. Nat. Clim. Change 11, 696-703, doi:10.1038/s41558-021-01101-x (2021).\nHeede, U. K. & Fedorov, A. V. Colder Eastern Equatorial Pacific and Stronger Walker Circulation in the Early 21st Century: Separating the Forced Response to Global Warming From Natural Variability. Geophys. Res. Lett. 50, doi:10.1029/2022gl101020 (2023).\n12 / 20\nKang, S. M., Shin, Y., Kim, H., Xie, S. P. & Hu, S. Disentangling the mechanisms of equatorial Pacific climate change. Sci Adv 9, eadf5059, doi:10.1126/sciadv.adf5059 (2023).\nKim, H., Kang, S. M., Kay, J. E. & Xie, S. P. Subtropical clouds key to Southern Ocean teleconnections to the tropical Pacific. Proc Natl Acad Sci U S A 119, e2200514119, doi:10.1073/pnas.2200514119 (2022).\nMcGregor, S. et al. Recent Walker circulation strengthening and Pacific cooling amplified by Atlantic warming. Nat. Clim. Change 4, 888-892, doi:10.1038/nclimate2330 (2014).\nSeager, R. et al. Strengthening tropical Pacific zonal sea surface temperature gradient consistent with rising greenhouse gases. Nat. Clim. Change 9, 517-522, doi:10.1038/s41558-019-0505-x (2019).\nWatanabe, M. et al. Possible shift in controls of the tropical Pacific surface warming pattern. Nature 630, 315-324, doi:10.1038/s41586-024-07452-7 (2024).\nWu, M. et al. A very likely weakening of Pacific Walker Circulation in constrained near-future projections. Nat. Commun. 12, 6502, doi:10.1038/s41467-021-26693-y (2021).\n2. Some elements of the logic are not complete, or not convincing. Many grand claims are made, and then not fully explained or backed up with the figures. I think this is partly because many of the details in the analysis have been left out or pushed into the methods section at the end. It also seems like there is a substantial amount of relevant literature that is not referenced here, which would help to interpret the results. For example, Bony et al., 2013 (on the fast CO2 forcing response), and Betts, 1998 (Climate-convection feedbacks: Some further issues. Climate Change, 39, 35-38).\nThanks for your comments. We have carefully revised the manuscript to improve its readability and clarity. The recommended literature has been cited in the appropriate sections.\nLine by line comments:\nLine 25: Is this shown in the paper? If not, it should either be clearly cited or not stated. The same is true all the way through line 29. On reading over the paper I am not yet convinced of the claims in these lines.\nWe have revised the first two sentences of the Abstract to “The Walker circulation is projected to slow down in response to greenhouse gas warming. However, detecting the impact of human activities on changes in the Walker circulation is challenging due to the significant influence of internal variability” and removed any unclear sentences to avoid confusion and misunderstanding.\nLine 51: What are ‘emergence studies’? Is that a thing or did they just make up this phrase? I can guess what you mean by this term, but I shouldn’t have to guess, it should be clearly stated.\n13 / 20\nWe apologize for the confusion here. The phrase “emergence studies” refer to studies that focus on identifying when human-caused climate signals become distinguishable from natural variability. We have corrected this phrase into “studies on the emergence time of climate change signals”.\nLines 65-66: “Accurately estimating the emergence of human-induced Walker circulation changes hinges on…”. The authors state that this depends on ‘precisely evaluating its intensity changes’, but simply knowing how the intensity changes over time does not clearly indicate if the changes are human-induced or otherwise driven (internal variability, etc.). I assume that determining the emergence of anthropogenic signals will hinge on the clear identification of internal variability, and then measuring how the total signal differs from this. Because of the inherent uncertainty of internal variability, this sounds very challenging.\nWe agree that intensity changes alone are not sufficient to estimate the emergence of human-induced changes, as internal variability can significantly influence the Walker circulation. Without accounting for internal variability, it would be difficult to attribute intensity changes solely to human influence. In this sentence, we would like to emphasize that the choice of indices might influence the estimate of the emergence time of Walker circulation changes. Based on your suggestion, we have revised the sentence to “Accurately estimating the emergence of human-induced Walker circulation changes depends largely on precisely evaluating its intensity changes”.\nLines 65-80: I think this paragraph would be more clear if it was restructured a bit. The statements about the discrepancy between observations and projections of changes in the Walker circulation (70-73) seems to be randomly slipped into the discussion about low-level verses upper tropospheric variables, and is thus confusing. Are you trying to make the argument that the disparity between observed and simulated changes is related to metrics that are based on the low-level verses upper level variables? I don’t think that is your argument, and so I think lines 70-73 should be in a different spot.\nThanks for your comments. We have removed this sentence in L70–73 and restructured this paragraph to make it clearer. Please see L62–75 in the revised manuscript.\nL62–75: “Accurately estimating the emergence of human-induced Walker circulation changes depends largely on precisely evaluating its intensity changes. Previous studies mainly use indices from low-tropospheric variables, such as sea level pressure (SLP) gradient and surface zonal winds18-23, to describe the magnitude change in the Walker circulation and uncertainties in its future projections19,24-26. However, these low-level indices exhibit a notable concurrence with SST variations1,27, making it challenging to separate the Walker circulation signal from SST-driven internal variability. While these low-level indices are widely used, they may not fully capture the complexities of the Walker circulation response to global warming, particularly in the upper troposphere. This is because compared with the lower troposphere, the upper tropical troposphere displays the\n14 / 20\nmost substantial intensification of water vapor and temperature warming under the anthropogenic CO forcing28,29. This disparity in water vapor and temperature\n2\nchanges may lead to differing responses of the Walker circulation at various tropospheric levels30, resulting in distinct emergence times at across these layers”.\nLines 70-72: Suggestion: Observations of lower-tropospheric WC metrics suggest a strengthening WC since the 1980’s while models tend to project a weaker WC.\nThanks for your suggestion. We have removed this sentence based on your previous comments to avoid confusion and improve clarity.\nLine 75-76: I don’t think you have sufficiently explained what disparity in vertical profile you are discussing here.\nIn this sentence, we want to emphasize that, compared to the lower troposphere, the upper tropical troposphere exhibits the most substantial intensification of water vapor and temperature under anthropogenic CO forcing. This vertical disparity in water\n2\nvapor and temperature changes may result in differing responses of the Walker circulation at various tropospheric levels. We have clarified this point in L71–75. Please see our response to your comments in “Lines 65-80” above.\nLine 100-106…. Is it really necessary to distinguish different mechanisms at different levels? Does this make sense scientifically? What do we gain from such a paradigm? Line 99-106 seems to be discussing the mechanism for circulation slow-down that was discussed by Held and Soden, 2006, but I think the description of this mechanism has some issues. First, the mid-tropospheric circulation is quite different from the circulation between the BL and the troposphere…. Second, the hydrologic sensitivity is not measured by omega_500 but by precipitation and the ratio of water vapor. Measuring the change of precipitation in this context, in the mid-troposphere, doesn’t really seem to make sense. For more clarity on the various ways that overturning circulations have been measured and discussed in the literature you could look at several relevant papers (Jeevanjee, 2022 (Three Rules for the Decrease of Tropical Convection With Global Warming); Jenney et al., 2020 (Understanding the response of tropical ascent to warming…); Silvers et al., 2023 (The Response of the Large-Scale Tropical Circulation to Warming)).\nThanks for your comments. Based on your suggestion and major comment #1 from Reviewer #1, we agree that it is not necessary to distinguish different mechanisms at different levels. This is because the weakening of the Walker circulation in the SSP scenario results from a combination of different mechanisms, and it is quite difficult to separate them based solely on SSP projection experiments. Following your suggestion, we have revised this section to present the projection of the Walker circulation at different tropospheric levels, showing that the Walker circulation is projected to weaken at various levels of the troposphere. Please refer to L92–100 for more details.\nL92–100: “The Walker circulation is projected to weaken at different tropospheric\n15 / 20\nlevels in a warmer future climate (Fig. 1). At the surface, an increase in low SLP over the Indo-Pacific warm pool reduces the east-west SLP gradient (Fig. 1a–b). In the middle and upper troposphere, positive trends over the western Pacific (in regions of climatological ascent) and negative trends over the eastern Pacific (in regions of climatological descent) indicate a weakening of both ascending and descending motions of the Walker circulation (Fig. 1c–f). This weakening is further supported by trends in vertical velocity, with positive values in the western Pacific and negative values in the eastern Pacific (Fig. 1g–h)”.\nAfter thoroughly reviewing the literatures you recommended, we have gained a physical understanding of why the weakening signal of the Walker circulation appears earlier in the middle and upper troposphere. Near the surface, the Walker circulation is primarily influenced by boundary layer processes and surface fluxes, which are closely tied to SST changes. In contrast, the middle and upper troposphere respond more directly to increased CO forcing. The combined effects of stronger warming, increased\n2\nstatic stability, and reduced radiative cooling in the middle and upper troposphere lead to a greater weakening of the Walker circulation at these levels compared to the surface.\nFirstly, the increase in CO causes a greater reduction in infrared radiation loss to space\n2\nin the upper troposphere than at the surface. This leads to faster warming and increased static stability in the upper layers of the atmosphere, which weakens vertical motions as the upper troposphere stabilizes more quickly than the lower layers (Held and Soden, 2006; Bony et al., 2013; Jeevanjee, 2022). Secondly, as the entire troposphere warms, the moist adiabatic lapse rate results in a disproportionate increase in static stability in the upper troposphere compared to the lower levels. This heightened stability further suppresses buoyancy-driven vertical motions, which are key to maintaining the strength of the Walker circulation (Betts et al., 1998; Bony et al., 2013; Jenney et al., 2020; Silvers et al., 2023). Moreover, CO -driven warming also slows down the rate of\n2\nradiative cooling (Held and Soden, 2006; Jenney et al., 2020; Jeevanjee, 2022; Silvers et al., 2023), which is crucial for sustaining convective circulation. The reduced radiative cooling diminishes the strength of vertical motions, particularly in the mid-troposphere, contributing to a significant weakening of the Walker circulation at these levels (Jeevanjee, 2022; Silvers et al., 2023). We have incorporated this discussion in L211–232 of the revised manuscript to clarify these points.\nL211–232: “The larger fast weakening of the middle and upper Walker circulation is caused by stronger radiative forcing, enhanced static stability, and slower radiative cooling in the mid- and upper troposphere compared to the surface. The increased atmospheric CO concentration reduces infrared radiation loss more in\n2\nthe upper troposphere than at the surface, leading to faster warming and greater static stability at higher altitudes31,36,37. This enhanced stability weakens the middle and upper Walker circulation, as the upper troposphere stabilizes more rapidly than the lower layers36,37. As the entire troposphere warms, the moist adiabatic lapse rate disproportionately increases static stability in the upper troposphere, further suppressing buoyancy-driven motions that support the Walker circulation36,38-40.\n16 / 20\nAdditionally, CO -driven warming slows the rate of radiative cooling31,37-39,\n2\nweakening vertical motions in the mid- and upper troposphere, leading to a significant weakening of the Walker circulation at these levels37,39. In contrast, the circulation changes near the surface are primarily influenced by boundary layer processes and surface fluxes, which are closely tied to SST changes. Hence, when the zonal SST gradient begins to decrease after about 30 years, the SLP also starts to change (Extended Data Fig. 5). The above results suggest that the mid-to-upper-level component of the Walker circulation weakens directly in response to increased atmospheric CO radiative forcing36, while the weakening of its surface\n2\nmanifestation is delayed by SST adjustment processes related to ocean dynamics. Therefore, the forced signal in Walker circulation change indicated by indices from the middle and upper troposphere is more likely to be detected earlier than the lower tropospheric indices”.\nReferences:\nBetts, A. K. Climate-Convection Feedbacks: Some Further Issues. Climatic Change 39, 35-38, doi:10.1023/a:1005323805826 (1998).\nBony, S. et al. Robust direct effect of carbon dioxide on tropical circulation and regional precipitation. Nat. Geosci. 6, 447-451, doi:10.1038/ngeo1799 (2013).\nHeld, I. M. & Soden, B. J. Robust Responses of the Hydrological Cycle to Global Warming. J. Clim. 19, 5686-5699 (2006).\nJeevanjee, N. Three Rules for the Decrease of Tropical Convection with Global Warming. J. Adv. Model. Earth Syst. 14, doi:10.1029/2022ms003285 (2022).\nJenney, A. M., Randall, D. A. & Branson, M. Understanding the response of tropical ascent to warming using an energy balance framework. J. Adv. Model. Earth Syst. 12, e2020MS002056, doi:10.1029/2020MS002056.\nSilvers, L. G., Reed, K. A. & Wing, A. A. The Response of the Large‐Scale Tropical Circulation to Warming. J. Adv. Model. Earth Syst. 15, doi:10.1029/2021ms002966 (2023).\nLine 137: What does this really mean? Why is there increased intermodel uncertainty in response to the external forcings? Perhaps this is a naïve thought, but I would have guessed that that the spread of the signal to noise ratio would decrease over time because the signal is presumably increasing while the noise.\nWe apologize for the inaccurate wording. We intended to convey that the increased intermodel spread in the signal-to-noise ratio over time (please refer to the shading in Fig. 2a, c, e) can be explained by the increased intermodel spread in the forced signal of the Walker circulation change (please refer to the shading in Extended Data Fig. 1b, d, and f). We have revised the sentence to “This increased intermodel spread can be explained by the increased intermodel uncertainty in the forced signal of the Walker circulation change”.\nLine 194: Is the fast weakening response really ‘more robust’ or is it simply different? More robust than what? What do you mean by robust?\n17 / 20\nIn this sentence, we want to emphasize that the stronger signal in the middle and upper troposphere is related to a larger fast weakening response in the middle and upper component of the Walker circulation, compared to the surface. We have revised the phrase “more robust” to “larger” to avoid misunderstanding.\nLine 195: PWC seems to have not been defined.\nWe have modified this into “Walker circulation”.\nLine 199: ‘after a longer-term adjustment’; I am confused here. I thought the slow response was the long-term adjustment, not something that comes after the long-term adjustment.\nThanks for your comments. We have revised this sentence to “and a slow response, which is characterized by a long-term adjustment” to avoid confusion.\nLine 213: Are you referring to a direct response to increased CO2 forcing or simply to the fact that CO2 has increased in these experiments? Cite, Bony et al., 2013.\nWe are referring to a direct response to increased CO forcing. We have revised this\n2\npoint and cited the recommended literature.\nLine 244-245: Is this true by construction of your definitions? If so then it doesn’t really tell us anything new.\nAccording to the definition of ToE, the intermodel uncertainty in ToE may originate from uncertainty in the forced signal or internal variability across models. Since the Walker circulation responds to CO forcing with both a fast and slow response,\n2\nwe examined the intermodel relationships between ToE and the fast response (Fig. R2-1), ToE and the slow response (Fig. 5 in the revision), and ToE and internal variability (Extended Data Fig. 8 in the revision). We found that the intermodel spread in the slow response, rather than the fast response or internal variability, is the primary source of the intermodel spread in ToE. Based on your comments, we have added Fig. R2-1 (Extended Data Fig. 7 in the revision) and restructured the relevant paragraph. Please see L241–258 in the revised manuscript.\nL241–258: “The intermodel uncertainty in ToE may sterm from uncertainties in the forced signal or internal variability across different models. To analyze the source of intermodel uncertainty in the ToE, we calculate the ToE by simultaneously considering the forced signal and internal variability in all the models based on three indices (Fig. 5a, c, and e). Here we estimate the magnitude of the forced signal as the long-term trend of the forced Walker circulation change. The results show that the ToE is influenced by both internal variability and the forced signal, with an earlier ToE appearing when there is smaller internal variability and a larger forced signal (Fig. 5a, c, e and Extended Data Fig. 6a, c and e). Since the Walker circulation responds to CO forcing with both a fast and slow\n2\nresponse, we examined the intermodel relationships between ToE and the fast response (Extended Data Fig. 7), ToE and the slow response (Fig. 5b, d, f and Extended Data Fig. 6b, d and f), and ToE and internal variability (Extended Data\n18 / 20\nFig. 8). The highest intermodel correlation coefficient between the ToE and the slow response suggests the major role of slow response in explaining the intermodel difference of ToE (Fig. 5b, d, f, and Extended Data Fig. 6b, d and f). The stronger the slow response is, the earlier the ToE appears, and vice versa. For models showing no emergence of the Walker circulation weakening (Fig. 2b, d, f), it can be attributed to a smaller slow response rather than larger internal variability (Fig. 5 and Extended Data Fig. 8)”.\nFig R2-1 (Extended Data Fig. 7 in the revision) Role of fast response in the source of intermodel uncertainty in ToE. a–c Relationship between ToE and fast response for dSLP, dW500 and VPmax index under the SSP2-4.5 scenario, respectively. d–f are the same as a–c, but under the SSP5-8.5 scenario. The intermodel correlations 655 on the relationships are indicated in the bottom-right corner of the panels.\nLine 250: You should explain the meaning of the names of Group-E or Group-L when they are first introduced?\nBased on your suggestion, we have explained the names of Group-E and Group-L as follows: “Group-E (models with an earlier ToE)” and “Group-L (models with a later ToE)”.\nLine 267-269: This is probably one of the key results of the paper. Has this been shown\n19 / 20\nbefore? By Heede et al., for example?\nThis is one of the key results of the paper and it has not been shown before.\nLine 269: This sentence should probably be rewritten. Just tacking, ‘hence the ToE’ onto the end of the sentence doesn’t really work grammatically.\nWe have rephrased this sentence into “Therefore, the difference in the magnitude of the slow response in the zonal SST gradient across models leads to intermodel uncertainty in the slow response of the Walker circulation to CO forcing, and consequently, in the\nLine 298-299: Your results show this in CMIP6 models, but not in general. This should be noted.\nBased on your comments, we have modified this sentence into “The findings provide a physical basis for reducing the uncertainty in the emergence of large-scale tropical circulation change signals in CMIP6 models”.\nLine 358: typically 1850-1910 is not considered to be preindustrial. I thought the cutoff was either 1850 or 1870. If you want to use a period that extends up to 1910 perhaps the description or language needs to change.\nWe have removed the phrase “preindustrial” to avoid misunderstanding based on your suggestion.\n20 / 20"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have addressed all my previous concerns pretty well. In the second round, I only have two minor comments which are shown below.\nMinor comments\n(1) Line 308-309. This sentence seems to indicate that there is also an increase in the entire troposphere above the sea surface in response to CO2 increasing, which can be well represented by the tropical-mean change and is compared with the warming pattern on the sea surface. However, I find the current expression should be improved. For example, “a vertical rise in the tropical mean” is confusing.\n(2) Line 454, the fast response in abrupt 4XCO2 run is chosen as the first 10 years in the Methods. This definition can be more specific, since in a previous study by Heede and Fedorov (2021), they choose the first 25 years as a fast response.", "reviewer_2": "The authors have done an excellent job revising this manuscript. I continue to think this is a worthwhile study that many people should be interested in reading. I myself was interested. I have a few minor comments below, but no major concerns.\nAbstract Summary:\nHuman-induced weakening of the Walker Circulation tends to occur earlier in the middle-upper troposphere relative to the surface. This is attributed to the weakening response of the mid-tropospheric Walker Circulation to the CO2 radiative forcing. Spread in the models is driven by an ocean thermostat through a sort of pattern effect on the Indo-Pacific SSTs.\nMinor Comments:\nLn 38: I think this sentence should start with ‘The Walker circulation…’.\nLn 52-54: This sentence is not quite clear. Do you mean the annual mean rainfall signal?\nLn 73: I am confused about your use of the word ‘disparity’. As written above, there isn’t a disparity between the response of upper-tropospheric water vapor and temperature warming, but rather a disparity between the warming response of water vapor and temperature in the upper-troposphere to the response at the surface. Right? Or am I missing something?\nLn 86-89: I think this could be much clearer if broken into two sentences. The second clause, beginning with ‘and in models…’ is confusing. Are you saying the earlier ToE also occurs in those models? Only occurs in those models? Or something else?\nLn 241: ‘sterm’ should be, ‘stem’. But this sentence needs to be revised. You basically say that the intermodal uncertainty may stem from uncertainty. How about something like this instead, “The intermodal uncertainty in ToE likely stems from a wide range of forced signals and internal variability across the different models.”?\nLn 256-258: For the models showing no emergence of the Walker circulation weakening, are any of them neutral? Saying it is attributed to a smaller slow response implies they are all weakening, but I suspect some are not changing much and thus there simply is no slow response.\nFigure 2: in the caption, line 154, ‘Gray bars indicate models show no emergence at the end of the 21st century.’ What exactly does this mean? Do you mean that the models with gray bars show no change of the Walker Circulation, or that the Walker Circulation does change by the end of the century but there is no difference between the SSP2-4.5 and SSP5-8.5 simulations? I am guessing that if there is no difference of the response of the Walker Circulation between the SSP2-4.5 and SSP2-8.5 simulations for a particular model that the anthropogenic signal is not detectable for that model? Is that correct?\nLn 447: So, just to be clear, when you define the ToE, ‘in response to global warming’, is the warming measured relative to PiControl, to the historical experiment, or as the difference between the two future scenarios? I would imagine that relative to PiControl would be the best, but it is not clear in the text (Or I missed it)."}, "author_response": "Response to reviewers’ comments of NCOMMS-24-30437A “Early emergence and determinants of human-induced Walker circulation weakening”\nWe appreciate the reviewers for another extremely thorough and detailed review. The comments provided have once again helped improve the paper. We have addressed the comments from the two reviewers and revised the manuscript based on their suggestions. Please see our point-by-point response below. In the following, the reviewer’s comments are written in black, followed by our response in blue.\nResponse to Reviewer #1:\nReviewer #1 (Remarks to the Author):\nThe authors have addressed all my previous concerns pretty well. In the second round, I only have two minor comments which are shown below.\nWe appreciate the reviewer for all the encouraging and constructive comments that helped us to improve the manuscript.\nMinor comments\n(1) Line 308-309. This sentence seems to indicate that there is also an increase in the entire troposphere above the sea surface in response to CO2 increasing, which can be well represented by the tropical-mean change and is compared with the warming pattern on the sea surface. However, I find the current expression should be improved. For example, “a vertical rise in the tropical mean” is confusing.\nThanks for your comments. We have revised this sentence to “Moreover, in addition to the El Niño-like warming over the eastern tropical Pacific, the temperature response to increasing CO concentrations also includes a significant warming of the tropical upper troposphere”.\n2\n(2) Line 454, the fast response in abrupt 4XCO2 run is chosen as the first 10 years in the Methods. This definition can be more specific, since in a previous study by Heede and Fedorov (2021), they choose the first 25 years as a fast response.\nDone. The definition of fast response has been revised to “We define the fast response as the mean of changes during the first 10 years, from year 1 to year 10, after imposed forcing”.\nResponse to Reviewer #1:\nReviewer #2 (Remarks to the Author):\nThe authors have done an excellent job revising this manuscript. I continue to think this is a worthwhile study that many people should be interested in reading. I myself was interested. I have a few minor comments below, but no major concerns.\nWe appreciate the reviewer for all the encouraging and constructive comments that helped us to improve the manuscript.\nAbstract Summary:\nHuman-induced weakening of the Walker Circulation tends to occur earlier in the middle-upper\n1 / 4\ntroposphere relative to the surface. This is attributed to the weakening response of the mid-tropospheric Walker Circulation to the CO2 radiative forcing. Spread in the models is driven by an ocean thermostat through a sort of pattern effect on the Indo-Pacific SSTs.\nThanks for the thorough and accurate summary.\nMinor Comments:\nLn 38: I think this sentence should start with ‘The Walker circulation…’.\nDone.\nLn 52-54: This sentence is not quite clear. Do you mean the annual mean rainfall signal?\nYes. We have clarified this point to make it clearer.\nLn 73: I am confused about your use of the word ‘disparity’. As written above, there isn’t a disparity between the response of upper-tropospheric water vapor and temperature warming, but rather a disparity between the warming response of water vapor and temperature in the upper-troposphere to the response at the surface. Right? Or am I missing something?\nThanks for your comments. We have revised this sentence to “This difference in the responses between the upper troposphere and the surface may lead to differing impacts on the Walker circulation at various tropospheric levels30, resulting in distinct emergence times across these layers” to avoid confusion.\nLn 86-89: I think this could be much clearer if broken into two sentences. The second clause, beginning with ‘and in models…’ is confusing. Are you saying the earlier ToE also occurs in those models? Only occurs in those models? Or something else?\nThanks for your comments. Based on your suggestion, we have revised these sentences to “We demonstrate that the ToE of the Walker circulation weakening potentially occurs earlier in the middle-upper troposphere than on the surface. An earlier ToE is also more evident in models that exhibit a stronger weakening of the zonal SST gradient after a long-term adjustment to CO increase”.\nDone.\nLn 256-258: For the models showing no emergence of the Walker circulation weakening, are any of them neutral? Saying it is attributed to a smaller slow response implies they are all weakening, but I suspect some are not changing much and thus there simply is no slow response.\nThanks for raising this question. Only the IPSL-CM6A-LR model projects a slightly strengthened Walker circulation based on the VPmax index. For models that show Walker circulation weakening but no emergence, this can be attributed to a smaller slow response rather than larger internal variability. Based on your comments, we have revised the sentence to “For models showing Walker circulation weakening but no emergence (Fig. 2b, d, f), this can be\n2 / 4\nattributed to a smaller slow response rather than larger internal variability (Fig. 5 and Extended Data Fig. 8)”.\nFigure 2: in the caption, line 154, ‘Gray bars indicate models show no emergence at the end of the 21st century.’ What exactly does this mean? Do you mean that the models with gray bars show no change of the Walker Circulation, or that the Walker Circulation does change by the end of the century but there is no difference between the SSP2-4.5 and SSP5-8.5 simulations? I am guessing that if there is no difference of the response of the Walker Circulation between the SSP2-4.5 and SSP2-8.5 simulations for a particular model that the anthropogenic signal is not detectable for that model? Is that correct?\nThanks for your question. The gray bars in Figure 2 indicate models that show no emergence of the forced Walker circulation change by the end of the 21st century. If a model has two gray bars, it means that the forced Walker circulation change is not detectable under either the SSP2-4.5 or SSP5-8.5 scenarios. Based on your comments, we have changed the gray bars to lighter blue and red to distinguish between the different scenarios. The relevant text has been revised to “Lighter blue and red bars indicate models in which no emergence of the forced Walker circulation intensity change is detected by the end of the 21st century for the respective scenarios”.\nFig.R2-1 (Fig. 2 in the revision) Comparison of detectability of the Walker circulation intensity change at different tropospheric levels. a Signal-to-noise ratio of Walker circulation intensity change relative to the 1980-2009 baseline calculated based on the sea-level\n3 / 4\npressure gradient (dSLP). Blue (red) thick line denotes the ensemble mean of models under the SSP2-4.5 (SSP5-8.5) scenario, while blue (red) shading indicates the model spread. The gray dashed lines denote the signal-to-noise ratio of 1 or -1. b ToE for annual-mean Walker circulation intensity change based on dSLP index, under the SSP2-4.5 (blue bars) and SSP5-8.5 (red bars) scenarios. Lighter blue and red bars indicate models in which no emergence of the forced Walker circulation intensity change is detected by the end of the 21st century for the respective scenarios. c–d and e–f are the same as a–b but based on the 500-hPa vertical velocity gradient (dW500) and the maximum absolute value in the 200-hPa velocity potential over the western tropical Pacific (VPmax), respectively.\nLn 447: So, just to be clear, when you define the ToE, ‘in response to global warming’, is the warming measured relative to PiControl, to the historical experiment, or as the difference between the two future scenarios? I would imagine that relative to PiControl would be the best, but it is not clear in the text (Or I missed it).\nThe global warming signal is measured relative to the period of 1850-1910 based on historical experiments. We have clarified this point in L417–418 based on your comments.\nL417–418: “The global mean surface air temperature (GSAT) increase is computed using the near-surface air temperature measured at 2 meters, based on historical experiments, relative to the period of 1851–1910”.\n4 / 4"}]

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