A climate change signal in the tropical Pacific emerges from decadal variability

Domain: earth_science
Published: 2024-09-27
Editorial outcome: minor_revision

Abstract
The eastern tropical Pacific has defied the global warming trend. There has been a debate about whether this observed trend is forced or natural (i.e., the Interdecadal Pacific Oscillation; IPO) and this study shows that there are two patterns, one that oscillates along with the IPO, and one that is emerging since the mid-1950s, herein called the Pacific Climate Change (PCC) pattern. Here we show these have distinctive and distinguishable atmosphere-ocean signatures. While the IPO features a meridionally broad wedge-shaped SST pattern, the PCC pattern is marked by a narrow equatorial cooling band. These different SST patterns are related to distinct wind-driven ocean dynamical processes. We further show that the recent trends during the satellite era are a combination of IPO and PCC. Our findings set a path to distinguish climate change signals from internal variability through the underlying dynamics of each.

Introduction
The fact that under greenhouse gas (GHG)-driven global warming some parts of Earth do not warm, or even cool, presents a fascinating problem. The surface tropical eastern Pacific stands out as a region that resists warming1. Whether evaluated over recent decades or back to 1900, the tropical Pacific exhibited what is often called a “La Niña-like” trend pattern with pronounced warming in the west and lack of warming in the cold tongue region1–6. This SST pattern is associated with cooling and shoaling of the tropical Pacific Ocean thermocline over past decades5,6. In contrast, state-of-the-art climate models most often respond to anthropogenic GHG forcing by warming the eastern Pacific, a pattern that is often referred to as “El Niño-like”7,8. Numerous studies have sought to reconcile this discrepancy and two primary arguments have been proposed. One suggests that correcting the cold tongue bias in the models’ mean state would align the models’ trends with observations, which are argued to be a forced response5. The other suggests that the recent observed trend is largely due to internal variability and is within the range of climate model simulations9,10. Although debate persists11–13, the Coupled Model Intercomparison Projects (CMIP) models and Large Ensembles rarely come close to the observed trends either as a response to radiative forcing, internal variability or any combination thereof. Alternatively, we may use observations to estimate the forced climate response. However, observational analyses come with their own limitations. Beyond inescapable observational error/uncertainty14,15, the tropical Pacific is dynamically active on decadal to multi-decadal timescales, so that internally generated long-term variability may overwhelm the climate change signal16,17. For example, the transition from positive to negative phases of the IPO—the dominant climate mode in the Pacific ocean on decadal to multi-decadal timescales and closely related to the Pacific Decadal Oscillation18–21—contributed to the observed La Niña-like SST trend pattern over the past four decades16,22,23. It has been argued that some individual ensemble members appear able to reproduce the observed trend pattern over the recent four decades because their randomly generated internal variability aligns, by chance, with the observed IPO phase transition24. However, long-term change in the tropical Pacific exhibits distinctive patterns unlike those on these decadal timescales. While SST anomalies associated with the IPO in the tropical Pacific typically feature a meridionally broad pattern21, the long-term lack of warming is found to be narrowly confined to the cold tongue2,4–6,14. Seager et al.6 further elaborate that some individual model simulations, containing both internal variability and the model’s forced response, come close to the observations but nonetheless fail to represent several fundamental elements of the observed long-term trends, including the distinctive narrowness of the lack of warming and the underlying subsurface ocean dynamical processes. These findings suggest that the tropical Pacific’s responses to anthropogenic forcing might present unique characteristics that set them apart from those typically associated with internal decadal variability.

Results
Recurrent IPO pattern and emerging pattern related to Pacific Climate Change (PCC)

The SST trend pattern after the satellite data become available (1980–2022) is often used as the observational reference for assessing climate model simulations of the forced response (Fig. 1a). This SST trend pattern is characterized by meridionally broad negative anomalies in the tropical Pacific, particularly south of the equator, and positive anomalies in the northwestern and southwestern Pacific. It is akin to that of the typical IPO variability on decadal to multi-decadal scale18,20,22,23 (Fig. S1a). If this trend is the positive to negative phase transition of the IPO, then it should appear in earlier historical periods, given that the IPO has experienced several phase transitions from 1870 to 2022 (Fig. S1b). In Fig. 1d we show pattern correlations of this short-term trend during 1980–2022 with tropical Pacific SST trends across all timespans of 43 years in the observational record (e.g., 1979 to 2021, 1978 to 2020, … 1870 to 1912) over 30°S–30°N, 120°E–270°W. The pattern correlations range from around −0.8 to 1, demonstrating an oscillatory behavior matching the IPO’s phase transitions over the last century (Fig. S1b). Analyses for the whole Pacific (60°S–60°N, 120°E–270°W) or the equatorial Pacific (10°S–10°N, 120°E–270°W) yield similar conclusion.

A different SST trend pattern beginning in the mid-1950s is shown in Fig. 1b. The start year 1958 is chosen to approximate the time when the tropical Pacific warm pool starts to warm up5,6 (Fig. 1c, lower panel), and because it is the start year of the Ocean ReAnalysis System-5 (ORAs5)25. The lack of warming in the tropical Pacific is still evident in this longer trend pattern (Fig. 1b). However, it is markedly confined meridionally to the equatorial region, unlike the much broader meridional distribution in Fig. 1a that is indicative of the IPO. Also, the warm anomalies in the northwestern and southwestern Pacific are less pronounced. This long-term trend pattern during 1958–2022 shows an emerging feature as evidenced in its pattern correlation with historical trends for equivalent earlier 65-year spans. As the end year of the trend is adjusted backward, the pattern correlation shows a rapid decline and lingers around zero in earlier periods (Fig. 1e). It suggests that this long-term trend pattern has no close historical analogues or anti-analogues, and we herein referred to the trend pattern during 1958–2022, which emerges from the background “noise” of internal variability, as the PCC pattern.

In Fig. 1d we identify periods with the strongest negative (P1: 1870–1912 and P3: 1942–1984) and strongest positive (P2: 1914–1956) pattern correlations with the short-term trend during 1980–2022. However, the recent southward-displaced center of the cooling in the eastern Pacific (Fig. 1a) is less apparent in these historical periods, suggesting that it might be due to climate change rather than internal variability26,27. Additionally, we show pattern correlations of the IPO pattern (Fig. S1a) with all 43-year SST trends in the tropical Pacific (shadings in Fig. 1d), which are strongly consistent with those related to the short-term trend during 1980–2022, though less so in the most recent periods. It suggests that while the IPO generally dominates the short-term trend patterns, the PCC leaves discernable imprints on the short-term trends in recent decades.

In Fig. 1e we identify the strongest negative pattern correlation (P4: 1870–1934) with the PCC pattern (Fig. S1c–f). The trend pattern in P4 (Fig. S1f) appears to be a weak reflection of the IPO pattern rather than a negative analogue of the PCC pattern, again confirming the distinctiveness of the PCC SST trend pattern that has emerged recently. The recurring feature of the short-term trend and the emerging feature of the long-term trend identified in HadISST data were consistently found across different SST datasets (ERSSTv5, Kaplan, COBE; Fig. 1d, e and S2). Further, Fig. 2a, b shows the histogram of historical period pattern correlations with short-term trend pattern during 1980–2022 and the PCC pattern, respectively. The overall distribution for the pattern correlations with the short-term trend is an approximately symmetrical distribution around zero over time. Trend patterns of both the same and opposite signs appear in earlier and later decades. In contrast, pattern correlations with the PCC pattern increasingly skew towards positive values in recent decades and there are no past anti-analogues of the PCC pattern.

Next we quantified the IPO’s contribution to the short- and long-term SST trends (Fig. 2c) by comparing the total trend in the tropical Pacific zonal SST gradient with the IPO’s contribution. The latter is calculated as the product of the trend in the IPO index over different time spans and the IPO-related zonal SST gradient as shown in Fig. S1 (see Methods). Consistent with Fig. 2a, b, the IPO variability predominantly shapes both the short-term and long-term trends during the earlier period when the climate change signal is relatively weak. In the recent period, however, the imprints of climate change are distinctly reflected in both short-term and long-term trends (Fig. 2c). As shown in Fig. 2c, the IPO accounts for over half of the observed zonal SST gradient trend during 1980–2022 (Fig. 2c), suggesting that the trend over the past four decades is a combination of IPO and PCC. In contrast, the impact of the IPO on the most recent long-term trend during 1958–2022 is minor. Moreover, short-term trends with a negligible IPO impact, such as that from 1970 to 2012 (Fig. 2d), closely resembles the emerging PCC SST pattern (Fig. 1b).

Distinct ocean dynamics for the IPO and the PCC

A closed Bjerknes feedback loop requires changes in the surface wind stress and the subsurface thermocline depth, to accompany the SST variations28,29. In Fig. 3, we show a recent short-term dipole-like pattern of thermocline depth (Fig. 3a) that recurs historically (Fig. 3e). In contrast, the emerging PCC SST trend pattern is accompanied by an overall shoaling throughout the tropical Pacific (Fig. 3b–e). Also, the recurring surface wind stress pattern in the equatorial Pacific features a broad strengthening of the zonal wind stress across the basin (Fig. 3c–e), while the PCC wind stress trend pattern in the equatorial Pacific displays a dipole structure with strengthened wind stress in the central Pacific and weakened wind stress in the eastern Pacific (Fig. 3d–f). We also examined the variability of the surface wind stress and the subsurface thermocline depth that are directly linked to the IPO (Fig. S3). These IPO-related patterns with dipole-like thermocline variability and same-signed wind stress variability in the tropical Pacific bear a close resemblance to the short-term trends (Fig. 3a–c). This supports the argument that the short-term trends over the span of approximately an IPO cycle predominantly reflect the internal variability of the IPO, manifest across the tropical Pacific upper ocean and atmosphere.

In the tropical Pacific, the thermocline depth and SSH are closely linked to each other and exhibit similar interannual fluctuations associated with El Niño-Southern Oscillation29,30. On decadal timescales, the dipole-like pattern is characterized by much higher SSH in the tropical western Pacific compared to the east (Fig. S3b), and thermocline deepening in the west and shoaling in the east (Fig. S3a). These are also present in the short-term trends during 1980–2022 (Fig. 3a–c). Unlike the short-term trend of SSH, the PCC trend exhibits an overall, but small, sea level fall in the central-to-eastern equatorial Pacific region, which is accompanied by sea level rise in the off-equatorial regions (Fig. 3d). The PCC thermocline depth trend is also different from the short-term trend in that it has shoaling or little change across the basin, though the shoaling is greater in the east (Fig. 3b). The short-term trends of thermocline depth-SSH-wind stress associated with the IPO oscillate back and forth together (Fig. 3e) but those associated with the PCC trend are collectively emerging over time (Fig. 3f).

These observed SSH and thermocline trends were previously demonstrated to be some combination of wind-driving, thermal expansion and the influence of changes in the Earth’s gravity field due to loss of land ice31–33. While there is general consensus on zonal dipole-like SSH change being related to internal variability in both observations34 and CMIP models35, the anthropogenic contribution to SSH change remains elusive33,35,36. Our subsequent analyses use a simple 1.5-layer reduced-gravity model to investigate the wind-driven component of SSH, thermocline depth, and circulation (see details in Methods; note that the same dynamics can be formulated as describing a single baroclinic vertical mode and hence have more general applicability37,38). We simplify further by solving an equilibrium version of the reduced gravity system analytically (see Methods, Eq. (6)). As shown in Fig. 4a, b, both the IPO-related short-term trend and the PCC-related long-term trend can be simulated quite realistically with this simple model by prescribing their corresponding surface wind stress trend patterns. The pattern correlations between observations and model for the observed and wind stress-driven SSH trend patterns are 0.87 for the short-term trend during 1980–2022 and 0.72 for the PCC trend in the tropical Pacific: 76% and 52% of the variance, respectively. This demonstrates the dominant role of the wind-driven redistribution of the heat content in the tropical Pacific upper ocean for both IPO-related variability and the emerging PCC signal. According to Eq. (6), variations in SSH are determined by the surface wind stress and its horizontal gradients zonally integrated from the eastern boundary. The spatial distribution of the wind stress effects (B in Eq. (6); Fig. 4c, d) underscore that it is the wind stress and its horizonal gradients in the central tropical Pacific that are most important in redistributing the heat content and driving the SSH changes in the tropical Pacific, for both climate change and decadal variability.

The different wind stress patterns also drive different ocean circulation changes. Figure 5a–c presents the zonally averaged ocean current trends over 3°S–3°N, 150°E–90°W associated with the recurrent short-term (red lines) and emerging PCC-related long-term (blue lines) trends. We also display the IPO-related ocean current trends during 1980–2022 (gray lines in Fig. 5a–c), which exhibit a strong consistency with the short-term trends. The most striking difference between the PCC trends (blue line in Fig. 5a) and trends contributed by the IPO phase transition (gray line in Fig. 5a) is the opposite-signed surface zonal currents in the equatorial and north off-equatorial regions. There is a significant strengthening of the surface westward zonal currents in the central equatorial Pacific for the decadal IPO variability (gray line in Fig. 5a and shadings in Fig. 5d). In contrast, the emerging pattern shows a weakening of westward surface currents in the central-to-eastern Pacific (blue line in Fig. 5a and shadings in Fig. 5e). The changes in surface zonal currents in the tropical Pacific are predominantly governed by its geostrophic component (Eqs. (7–8); contours in Fig. 5d, e), determined by the wind-driven SSH (Fig. 4). Wind stress also impacts Ekman pumping (Eq. (11)). While the decadal IPO upwelling pattern is approximately symmetric around the equator (gray line in Fig. 5c), the meridional center of the emerging upwelling pattern is displaced to near 5°S (blue line in Fig. 5c). The overall strengthening of zonal wind stress across the equatorial Pacific linked to decadal variability fosters pronounced upwelling from the western to eastern equatorial Pacific (Fig. 5f). In comparison, the emerging PCC wind stress pattern contributes to enhanced upwelling in the central equatorial Pacific and weakened upwelling to the east, while stronger trade winds south of the equator contribute to increased local upwelling (Fig. 5g), thereby accounting for the different meridional locations of upwelling change (Fig. 5c). The meridional currents averaged in the mixed layer, indicative of the strength of the shallow overturning circulation, are quite similar for the short-term and long-term trends, showing a consistent strengthening of the poleward transport in both hemispheres, though of different magnitudes (Fig. 5b).

The IPO and PCC-related temperature changes (Eqs. (12–13)) in the equatorial Pacific occur via different wind-driven ocean dynamical processes (Fig. 6). The IPO-related short-term cooling in the equatorial eastern Pacific (Fig. 1a) is primarily driven by a strengthened zonal current (Fig. 5d) and advective cooling (UaTc) (Fig. 6a). Enhanced poleward transport (VaTc) and thermocline shoaling (WcTa) also contribute to the IPO-related cooling in the equatorial region. The PCC cooling is relatively weaker because warming due to a weaker zonal current in the east largely offsets the cooling effect related to the thermocline feedback due to the thermocline shoaling (Fig. 6b). The meridional temperature gradient strengthens more for the narrow PCC than the broad IPO (Fig. 1b), such that only for the PCC does meridional temperature gradient (VcTa) contribute cooling in the central-to-eastern Pacific (Fig. 6a, b). Although the vertical upwelling changes are evident for the equatorial region, the Ekman pumping term’s (WaTc) contributions to the wide equatorial Pacific (5°S–5°N) temperature change are minor for both the IPO and the PCC, which might be due to the immediate opposite-signed effect off the equator for both.

Methods
Datasets
The SST data used here are the Hadley Centre data HadISST version 1.1 with horizontal resolutions of 1°×1°48, the National Oceanic and Atmospheric Administration ERSSTv5 data with horizontal resolutions of 2°×2°49, the Centennial in Situ Observation Based Estimates of SST (COBE) from the Japanese Meteorological Agency with horizontal resolutions of 1°×1°50, and Kaplan Extended SST version 2 with horizontal resolutions of 5°×5°51. HadISST, ERSSTv5, and Kaplan were used from 1870 to 2022 and COBE from 1890 to 2022. We utilized subsurface temperature and surface wind stress from the ORAs5 during 1958–2022, with horizontal resolutions of 0.25°×0.25° and 75 vertical levels, the latest ocean reanalysis products provided by the European Centre for Medium-Range Weather Forecasts25. The vertical velocity for ORAs5 was derived from zonal and meridional currents based on mass continuity52. We also used subsurface temperature and surface wind stress from the Simple Ocean Data Assimilation (SODA), version 2.2.4 with horizontal resolutions of 0.25°×0.25° and 40 vertical layers during 1871–197953, in conjunction with the version 3.3.2 with horizontal resolutions of 0.25°×0.25° and 50 vertical layers during 1980–201854. The air temperature data was obtained from the National Centers for the Environmental Prediction–National Center for the Atmospheric Research (NCEP–NCAR) reanalysis 1 during 1958–2022 with horizontal resolutions of 2.5°×2.5° and 17 vertical layers55. All datasets were interpolated onto a horizontal grid of 1°×1° to enable comparison among datasets.

Statistical methods and definitions of indices
All anomalies were calculated relative to the climatology of the first 50 years (1870–1919). Statistical significance tests were performed based on the two-tailed Student’s t test with n−2 degrees of freedom, where n is the sample size. The qualitative conclusions for the significance remain consistent when evaluated using the non-parametric Mann-Kendall test56,57. The thermocline depth was identified as the depth of the 20°C isotherm. The qualitative conclusion in Fig. 3a, b remains similar based on the thermocline depth defined by the maximum vertical temperature gradient. The zonal SST gradient in the tropical Pacific was defined as the temperature difference between the western Pacific (5°S–5°N, 140°E–170°E, indicated by the left box in Fig. 1b) and the eastern Pacific (5°S–5°N, 190°W–270°W, indicated by the right box in Fig. 1b). The IPO index was calculated based on the difference between the SST anomalies averaged over the central equatorial Pacific (10°S–10°N, 170°E–90°W) and the average of the SST anomalies in the northwest (25°N–45°N, 140°E–145°W) and southwest Pacific (50°S–15°S, 150°E–160°W) following Henley et al.18. Then a 13-year low-pass filter based on Fast Fourier Transform was applied to extract the decadal-scale component of IPO variability. Trends evaluated over time periods in which the IPO phases vary can be influenced by the IPO. To assess the IPO’s contribution to the 43-year trends and 65-year trend of SST in the historical periods (Fig. 3), we regress the detrended SST against the IPO index and then multiply this by the IPO index’s linear trend for the corresponding time period. Besides, we calculate the IPO-related trends in ocean currents and Ekman pumping during 1980–2022 by regressing the detrended variables against the IPO index and then multiplying this by the IPO index’s linear trend for this period.

Reduced gravity system linking SSH and thermocline depth to surface wind stress
A 1.5-layer linear steady state reduced-gravity system on an equatorial β-plane (f=βy, in which f the Coriolis parameter and β= 2.3×10−11 m−1s−1) is used to relate the changes in the surface wind stress to changes in the SSH and thermocline depth. Denote the wind stress by τ=(τx, τy): Specifying a spatially-uniform climatological upper layer thickness (h1=150m)37,38,58,59 and taking Δρ=2.7kg/m3 as the density contrast between upper and bottom layers yields a first baroclinic mode gravity wave speed of c≈2.0m/s, where c2=g0h1, g0=g Δρ/ρ0, and ρ0=1025kg/m3 is the reference density. The governing equations on an equatorial β-plane are:

-fV= -g0h1∂h/∂x + τx/ρ0 (1)

fU= -g0h1∂h/∂y + τy/ρ0 (2)

∂U/∂x + ∂V/∂y = -rh1 (3)

in which h1 is the upper layer thickness between SSH (h; m) and thermocline depth (h2; m), r= 1/5.5 year−1 is the damping coefficient, U= ∫h2udz (u the zonal current; m/s), and V= ∫h2vdz (v the meridional current; m/s). Cross-differentiating Eq. (1–2) and using Eq. (3), we obtain:

∂h/∂x + βy2r/(g0h1) h= 1/(ρ0g0h1) (τx + ∂τy/∂x - ∂τx/∂y) (4)

Let λ= βy2/(g0h1) and B= 1/(ρ0g0h1) (τx + ∂τy/∂x - ∂τx/∂y)= 1/(ρ0g0h1) curl(τf), and the equation (4) can be solved as:

h= e−λ(xe-x)he + ∫xe x Be−λ(x0-x)dx0 (5)

in which xe indicates the eastern boundary, he the layer thickness at the eastern boundary. The change in the SSH can then be directly linked to the change in the surface wind stress if the change of SSH near the eastern boundary is neglected (which is approximately justified on the basis of the changes in Fig. 3):

h1= Δρ/(ρ+Δρ) ∫xe x Be−λ(x0-x)dx0 (6)

Estimation of geostrophic zonal current and Ekman pumping
The geostrophic component of the surface current can be determined by considering the balance between the Coriolis force and the pressure gradient force. The geostrophic zonal current (ug) outside of the equatorial region is expressed as:

ug= -g/f ∂h/∂y (7)

At the equator where f=0, an estimate of the equatorial semi-geostrophic zonal current (usg) is derived by calculating the second derivative of the SSH on an equatorial β-plane:

usg= -g/(β∂y2) ∂2h (8)

which are suggested to be in good agreement with measured velocities60,61. Following the approach of Zebiak and Cane59, the Ekman transport (UE, VE) in the tropical region is formulated by incorporating a frictional component as:

UE=(rsτx+fτy)/ρ0(f2+rs2) (9)

VE=(rsτy-fτx)/ρ0(f2+rs2) (10)

where rs indicates the surface layer friction coefficient (1/2 day−1). The Ekman transport away from the equator is consistent with classical Ekman theory. At the equator where f=0, the friction allows an Ekman transport in the direction of the wind stress. Ekman pumping velocity (wE) is thus derived from the divergence of the Ekman transport:

wE= ∂UE/∂x + ∂VE/∂y (11)

Mixed layer heat budget analysis for the long-term SST Change
The heat budget for the mixed layer temperature62 can be expressed as:

∂T/∂t = -ua∂T/∂x - uc∂Ta/∂x - uaTa/∂x - va∂T/∂y - vc∂Ta/∂y - vaTa/∂y - wa∂T/∂z - wcTa/∂z - waTa/∂z + R (12)

in which a denotes anomaly and c denotes climatology. The heat budget terms include changes in the mean current (UaTc, VaTc, WaTc), changes in the mean temperature gradient (UcTa, VcTa, WcTa), and their nonlinear interaction (UaTa, VaTa, WaTa). The zonal advection and meridional advection terms were averaged over a uniform mixed layer depth of 50 m. The vertical velocity was calculated at the bottom of the mixed layer, and the vertical advection between the 50–100 m and the upper 50 m layers was calculated only in the presence of upwelling. The residual term (R) for the mixed layer indicates the surface heat flux and subgrid/submonthly processes.

To evaluate the heat budget related to the PCC-related temperature changes, we identified two sub-periods during 1958–2022: the first 20 years (1958–1977) as a reference period, and the most recent 20 years (2003–2022) as the period of climate change. We then calculated the averages of each heat budget term in the quasi-equilibrium period P1 and climate change period P2 based on Eq. (12), and estimated the contributions of each term to the observed temperature changes by calculating their differences:

∂T/∂tP2 - ∂T/∂tP1 = (UaTc|P2 - UaTc|P1) + ... + (WaTa|P2 - WaTa|P1) + (R|P2 - R|P1) (13)

To reflect the contributions of these terms to the temperature change over each decade, we normalized their units to °C/month per decade by dividing by a factor of 6.5. In addition, to analyze the IPO’s impact on the temperature change on decadal timescales, the detrended heat budget terms were regressed against the IPO index. The regression coefficients were then scaled by the linear trend in the IPO index from 1980 to 2022.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "July 16, 2024\nReview for Nat. Comms.\n“A climate change signal in the tropical Pacific emerges from decadal variability”\nBy Jiang, Seager and Cane\nRecommendation: accept subject to revision\nGeneral comment:\nThis study attempts to separate the contributions from internally generated IPO and those from\nexternal forcing, mainly increases of GHGs, to tropical Pacific SST trends in the historical period.\nThe authors frame the problem (in the first line of the abstract and elsewhere) as to whether the\npost-2000 La Nina-like SST pattern in the eastern tropical Pacific was internally generated or\nexternally forced. But then there is no distinct conclusion regarding which was more important.\nInstead, there is a vague reference to an “emerging SST pattern” (is it El Nino-like or La Nina-like?)\nwith an “SST warming trend” (but wasn’t the SST trend post-2000 La Nina-like?) with a narrow\nequatorial cooling band (could that be “La Nina-like”?). In the end, it was not clear to me if the\nauthors are arguing that the post-2000 SST trend in the tropical eastern Pacific was due to negative\nIPO or some combination of negative IPO and the “emerging SST pattern” with a contribution to the\nnegative IPO from the “narrow equatorial cooling band” (Fig. 2d). So would the negative IPO phase\nhave been even more pronounced if not for the externally-forced off-equatorial warming in the\n“emerging SST pattern”? Additionally, if the IPO transitions to positive now or in the future, will the\n“emerging SST pattern”, which is presumably externally forced, mean that there will be a narrow\ncooling band in the equatorial eastern Pacific surrounded by positive SST anomalies? In short, it\nwould be good to see a bit more interpretation of what the authors actually think is going on, and\nwhat that will mean for future climate change in the tropical Pacific. In this regard, it may be\nappropriate to keep in mind previous work that has shown that when anthropogenic warming\nincreases in future in high emission forcing simulations, periods of negative IPO (with reduced\ndecadal trends in global warming) are overwhelmed by tropical eastern Pacific warming from\nincreasing GHGs (Maher, N., A. Sen Gupta, and M. H. England (2014), Drivers of decadal hiatus\nperiods in the 20th and 21st centuries, Geophys. Res. Lett., 41, 5978–5986,\ndoi:10.1002/2014GL060527).\nDetailed comments:\nLines 40-43: The authors here cite the “models are wrong” argument from Wills et al. However, at\nleast a couple of caveats should accompany this conclusion. First, in a very high resolution Earth\nsystem model simulation that arguably captures more relevant ENSO dynamics than 1 degree class\nESMs, future warming from increasing GHGs shows an El Nino-like response in the eastern tropical\nPacific (see their Fig. 2). Those authors note the important role of tropical instability waves (TIWs) in\nENSO dynamics, and the future response to increasing GHGs, that are not presently captured by\nthe 1 degree class CMIP models (Wengel, C., et al., 2021, Future high-resolution El Nino/Southern\nOscillation dynamics, Nat. Clim. Change, 11, 758–765", "reviewer_2": "Reviewer #\n‘A climate change signal in the tropical Pacific emerges from decadal variability’ by Feng Jiang,\nRichard Seager and Mark A. Cane\nThis paper evaluates the unusual cooling trend in sea surface temperatures in the tropical Pacific,\nand whether it can be attributed to external forcings or is a result of internal variability, namely the\nInterdecadal Pacific Oscillation. It shows that the IPO signal can be detected in both short-term\nand long-term trends prior to 1975, but in the more recent period, the climate change signal\ndominates. The differences in SST patterns are attributed to differences in wind stress patterns and\nthermocline shoaling. The novel results shown here are of significant interest for the community\nand for the advancement of disentangling decadal climate variability and long-term changes.\nNevertheless, the methods and presentation of the results (including time periods used) need to be\nfurther clarified for this work to be ready for publication.\nI enjoyed reading the introduction due to its clear message and inclusive language, which makes\nthe paper accessible not only for experts in the field. The aim of the paper is generally well\narticulated, and the authors get back to providing an answer to their posed research question in the\ndiscussion, making it a well-rounded piece of work. The results are well structured, and a\nsignificant amount of analysis has been carried out to support them. The figures are generally well\npresented, but labelling and descriptions, both in figure captions and in the main manuscript, need\nsome more work. The methods are well thought through but need to be better described at times\n(e.g the ‘IPO-related trend’).\nMy main suggestions for improvement are as follows:\n1) Sentence structure and vague descriptions:\nMany sentences are very long. I have pointed out a few examples. I suggest breaking them up,\nwhich will make it easier to understand your message and results. The language is also sometimes\noverly complicated, making some sentences unclear and difficult to understand. I suggest\nshortening and rewording them. I also encourage being more precise with your language by for\nexample indicating which time periods the results are showing and giving clear definitions for\nphrases you use throughout the paper (e.g. what do you define as ‘the emerging trend’; if ‘short-\nterm trend’ always refers to the time period 1980-2022 make sure that you introduce this rather\nthan letting the reader guess). Some descriptions are very vague, making it unclear to know what\nexactly is analysed. This applies especially to figure descriptions, but also to other sections\nincluding the abstract. I am aware that you probably tried to shorten the text this way, but leaving\nout details results in crucial information getting lost.\n2) Trends vs. variability\nSome more work is needed to highlight the differences between long-term trends and internal\nvariability described here. Please double check your language around the words ‘trend’, ‘change’,\nand ‘variability’. Are the words ‘trend’ and ‘change’ used interchangeably? I currently do not know,\nas it is not always clear. The difference between long-term changes and climate variability needs to\nbe much clearer too and the wording more precise. In some instances it sounds like you classify the\nIPO as a trend rather than internal variability. If you are referring to the trend during a certain IPO\nphase, please adjust your language to reflect that, as it can otherwise cause confusion - It wasn’t\nalways clear to me what exactly you were referring to. While mentioning that you calculate a\ncontribution of the IPO to the short-term trend in the methods, this should be much clearer in the\nmain text and also deserves a more detailed description in the methods section. For example in\nFigure 5 and Figure 6, it is not clearly stated what time period is used to conduct the analysis.\nNot knowing exactly what analysis was carried out I see as a caveat to the current analysis regarding the\n‘IPO-related trend’. Also sometimes it is referred to decadal changes, but then in the same\nsentence to IPO variability. I have highlighted some instances in which this is unclear and\nsometimes confusing (especially in cases where you are referencing the wrong figure, see\ncomment 4)).\n3) Figure descriptions\nIt needs to be clear which exact variables are shown in the figures, as well as the time periods and\nareas used to generate them, so be more precise with your subplot titles, figure captions and\nvariable abbreviations that are used in your equations.\n4) Figure referencing\nFigure referencing is inconsistent, particularly in the last section of the results. This makes it\ndifficult to assess them. In many cases the text refers to the wrong figure or wrong panel in a figure\n(there are many instances, in which Figure 6 is incorrectly referenced instead of Figure 5).\nThere are also some inconsistencies regarding the terms in your equations you mention (e.g. the heat budget\nterms). Please double check and correct. I have highlighted a few examples below.\n5) Methodology\nThere is some clarification needed around the methodology, and where in the paper each method\nis applied. It would be useful to indicate the section in the main text or figure, in which the results\nare shown that have been calculated using the shown equations. It would be helpful to repeat the\nsame abbreviations or symbols as used in the equations in the figure captions or titles. This will\nmake it easier to find a specific methodology and the corresponding results. The currently often\nused reference to ‘see methods’ in the figure captions is not ideal, especially when not indicated\nwhich part of the methods the reader is supposed to search for. These caveats in the methods\ndescription result in some uncertainties when trying to interpret the results.\n[Detailed comments]\nAbstract\nll. 13-14 trend pattern shaped by the IPO  this is confusing for a reader who assumes that the IPO\nis a pattern of variability. I suggest clarifying here what exactly you analyse.\nOne wonders what sort of data you have used  please indicate in your abstract that your study is\nbased on observational and reanalysis data. One also wonders which time periods you are talking\nabout here. And what is defined as an ‘emerging pattern’? What makes the IPO pattern different\nfrom the trend pattern? What sort of changes do you see in the subsurface temperature structure\nfor example? What are ‘distinctive ocean dynamical processes’ mentioned here? Be to be more\nprecise.\nIntroduction\nl. 64 variabilities  variability\nl. 67 maybe: different observational and reanalysis datasets\nResults\nl. 82 phases  phase\nl. 84 clarify time frame for observed record that is evaluated here (e.g. from 1870 to 2022)\nll.100-101 please reword and clarify the sentence as it is very confusing. It is unclear here which\nyears you are referring to.\nll.101-103 you may like to add what this result indicates\nl. 105 P2:1914-1956  I think this should be 1904-1956? Please double check, in the figure caption\nfor Figure S1 P2 is listed as 1904-1956.\nl. 106 this is very confusing. I think you need to stick to the same terminology throughout the paper\nand define what you mean by ‘long-term trend’. In line 97, the long-term trend refers to the time\nperiod shown in Figure 1b, which is 1958 to 2022. But here the long-term trend is a different time\nperiod; starting in 1870.\nl. 108 most recent 43-year (1980-2022) trend\nl. 113 latest 65-year trend (1958-2022)  it needs to be clear which time periods you are referring to\nl.122 ant-analogues  ?\nll. 134-137 this is an important finding!\nl. 145-146 The sentence is confusing. I suggest breaking this up into two sentences or reword for\nbetter readability and add the years for time periods you are mentioning. I think you are trying to say\nsomething like:\nOur analysis has established that there is a distinctive SST trend pattern detected in the extended\ntime period 1958 to 2022, which stands in contrast to the short-term (post-1980) SST trend pattern\nthat is primarily related to the IPO.\nl. 147 necessitates corresponding changes  requires changes\nl. 150 Fig. 3a,e  how does e) indicate a dipole structure?\nl. 153 strengthened  this is not clear in panel d), rather a strengthening in the SH off-equatorial\nPacific\nl. 155 changes in the surface wind stress  variability in surface wind stress\nll. 156-161 Sentence is too long! Please split up.\nl. 157 thermocline change and same-signed wind stress change  thermocline variability and same-\nsigned wind stress variability\nl. 158 trends which again substantiate the argument  trends. This supports the argument\nl. 160 reflect the recurrent influence of the IPO manifested  reflect the internal variability of the\nIPO, which is manifested\nl. 164 the dipole-like pattern characterized with much stronger sea level rise  maybe rather: the\ndipole-like pattern is characterized by much higher SSH\nl. 165 add figure references and break sentence up. Compared to the east and thermocline\ndeepening in the west  compared to the east (Fig. S3b). Thermocline deepening is evident in the\nwest and shoaling in the east (Fig. S3a), which is also present in the recent 1980-2022 trend.\nl. 166 Fig. 3a,c,f  e not f\nl. 168 region, accompanied by sea level rise in  region, which is accompanied by higher sea levels\nin ….\nl. 171 greater in the east  greater in the east (Fig. 3d).\nl. 173 for the long-term trend  reword or delete\nl. 177 SSH changes related  SSH change being related….\nl. 185 4a,b  4a and b\nl. 189 break sentence up!\nl. 194 horizontal  zonal?\nl. 199 central-to-eastern Pacific  add exact area referred to here (latitude, longitude)\nl. 201 add figure reference\nl. 202 again, decadal variability is variability, not a trend\nl. 206 please double check figure reference and clarify - I believe that you are referring to panels in\nFigure 5. I suggest adding which line in the plot indicates your mentioned information (e.g. Figure\n5a, grey line).\nl. 207 I think that you are referring to Figure 5a, blue line, not Figure 6b? Please double check.\nl. 208 again, figure reference is wrong. Please double check. I think you are referring to Figure 5 d,e\nll. 211-213 where can you see that? Figure reference missing.\nl. 215 wrong figure reference. You need to carefully check your figure referencing.\nl. 218 wrong figure reference.\nll. 219-221 where can you see that? Figure reference is missing.\nll. 223-240 please make sure that the terms you mention here are correct, and mention the terms\nwhere missing.\nl. 226 I can see in your Figure 6a that the largest contribution is made by UaTc and not UcTa. Please\ncorrect and double check.\nl. 230 muted  ? please reword. I assume you mean weaker?\nl. 232 doesn’t VcTa refer to mean meridional temperature gradient, rather than ocean current\nchange? Please clarify.\nll. 236-240 sentence is too long, which makes it confusing. Please break up.\nDiscussion\nl. l.259-261 The word selection in this sentence is confusing, please rewrite.\nl. 268 changes or variability?\nl.272 disentangle causal relationships among the long-term changes  disentangle causal\nrelationships between internal variability and long-term changes?\nl. 282 but you don’t actually analyse IPO phase transitions in your analysis! What ‘recent IPO swing’\ndo you refer to? What do you mean with an extreme and robust IPO phase swing? Again, be more\nprecise in your language and make sure that your conclusions are supported by the analysis you\nshow.\nl.264 the initial response of what?\nl. 274-276 I agree!\nMaterials and methods\nll. 294-299 Please add the timeframe analysed for ORAs5 variables  I think 1958-2022.\nll. 302-305 Please add the timeframe analysed for air temperature. It is unclear what time period is\nused, as also not indicated in Figure S4, which displays results using these data. Please clarify.\nll. 309-310 The significance of trends if often evaluated using the non-parametric Mann-Kendall test\nrather than a student’s t-test. Can you elaborate on your choice of significance test to assess trends\nhere?\nll.312-313 Which qualitative conclusions? Please elaborate which part of the results in main paper\nand figure this refers to.\nll. 321-323 so does this mean that all figure panels that relate to the ‘IPO-related trend’\nrelate to the time period used for the ‘short-term trend’? Which is 1980 to 2022? If this is the\ncase, please clarify and also mention in the figures that are related to the ‘IPO trend’. And also clearly\ndefine what the ‘short-term trend’ time period is. It is also worth including which variables x are\nused for this analysis.\nl. 341 include the abbreviations used in equation for layer thickness change and wind stress change\nll.375-376 I may have missed it, but where do you present results related to equation 13?\nl. 377 which decade?\nReferences\nl. 457 Southern Indo-Pacific*  remove *\nl. 466 Trend Attribution*  remove *\nl. 468 Cambridge University Press., 2010  Cambridge University Press, 2010\nl. 472 Equatorial Wave Theory*  remove *\nAcknowledgements\nl. 545 Data and methods availability  please change to Data availability, as you are not listing any\nlinks to code or other materials here\nFigures\nFigure 1\nI suggest adding the region used for pattern correlations in the subplot titles for c) and d) for easier\nreadability of the figure. Currently one would assume that global SSTs are used, but you are\nshowing results for the tropical Pacific.\nll. 566-568 Pattern correlations of 43-year SST trends in historical 566 period with the trend during\n1980-2022 in the tropical Pacific region (30°S-30°N, 120°E-567 270°W)  I suggest moving the\nregion used further towards the beginning of the sentence to make it clear that you are correlating\nSST trends in the tropical Pacific. The way it is written, one could assume that you correlate global\nSST trends for 1980-2022 with trends in the tropical Pacific.\nll. 570-571 I suggest adding the years for each time period indicated by P1,P2,P3 and P4 here.\nFigure 3\nI suggest adding the region used (tropical Pacific) to the subplot titles in e) and f) for easier\nreadability of the figure.\nFigure 4\nc,d) You are showing wind stress, so also indicate that in your subplot titles.\nl. 601 for decadal and climate change variability  I think you mean ‘for decadal variability and\nclimate change’\nFigure 5\nPlease add units to plots a,b,c and indicate the area used in subplot titles or in top or bottom\ncorners of subplots. What does the xlabel on a,b and c mean (‘IPO related’)? Looks like the last\nentry in legend got duplicated by accident?\nAlso, I cannot see any discussion of panels f) and g) in the main text. Either discuss these panels,\nor remove them from the figure.\nPlease mention the variable abbreviations used in your equations (e.g for geostrophic flow and\nEkman transport) in the corresponding subplots and in the figure caption. This makes it easier to\nidentify what you are showing here.\nFigure 6\nI suggest indicating in the figure caption which equation is used here. Also include time periods to\nclarify what you are showing (the change between what is shown?) – and say that this is a mixed\nlayer heat budget. Also the figure caption says Central-to-eastern SST, but in the figure description\nthe indicated area used is the eastern Pacific? Please make sure this is consistent! The figure\ncaption and titles are very confusing.\nl. 628 following equation 12, this should be UaTc, VaTc, WaTc and not UcTa, VcTa, WcTa. Please\ndouble check. You are currently duplicating the terms that indicate the mean temperature gradient\nchange here.\nSupplementary Materials\nll. 43-45 Please add the timeframe that is analysed in this figure\nl.44 Please add the subsection heading in the Methods section here, so the reader can find this\ninformation more easily.", "reviewer_author_response": "Response to Reviewers\nWe would like to thank the reviewers for their constructive comments and suggestions.\nWe have addressed the reviewers’ concerns and implemented useful suggestions in our\nrevised manuscript. The responses are listed below in blue font. In addition, on reading\nthe reviews, it appeared that the main point of our argument had not come through\nstrongly enough and had left the reviewers confused on some matters. This was clearly\nour fault and, in response, we have rewritten the paper throughout to make our\narguments clearer and also introduced a new term, the Pacific Climate Change (PCC)\npattern, to emphasize the novelty of our results.\nResponse to Reviewer#1\nGeneral Comments\nThis study attempts to separate the contributions from internally generated IPO and\nthose from external forcing, mainly increases of GHGs, to tropical Pacific SST trends\nin the historical period. The authors frame the problem (in the first line of the abstract\nand elsewhere) as to whether the post-2000 La Nina-like SST pattern in the eastern\ntropical Pacific was internally generated or externally forced. But then there is no\ndistinct conclusion regarding which was more important. Instead, there is a vague\nreference to an “emerging SST pattern” (is it El Nino-like or La Nina-like?) with an\n“SST warming trend” (but wasn’t the SST trend post-2000 La Nina-like?) with a\nnarrow equatorial cooling band (could that be “La Nina-like”?). In the end, it was not\nclear to me if the authors are arguing that the post-2000 SST trend in the tropical\neastern Pacific was due to negative IPO or some combination of negative IPO and the\n“emerging SST pattern” with a contribution to the negative IPO from the “narrow\nequatorial cooling band” (Fig. 2d). So would the negative IPO phase have been even\nmore pronounced if not for the externally-forced off-equatorial warming in the\n“emerging SST pattern”? Additionally, if the IPO transitions to positive now or in the\nfuture, will the “emerging SST pattern”, which is presumably externally forced, mean\nthat there will be a narrow cooling band in the equatorial eastern Pacific surrounded\nby positive SST anomalies? In short, it would be good to see a bit more interpretation\nof what the authors actually think is going on, and what that will mean for future climate\nchange in the tropical Pacific. In this regard, it may be appropriate to keep in mind\nprevious work that has shown that when anthropogenic warming increases in future in\nhigh emission forcing simulations, periods of negative IPO (with reduced decadal\ntrends in global warming) are overwhelmed by tropical eastern Pacific warming from\nincreasing GHGs (Maher, N., A. Sen Gupta, and M. H. England (2014), Drivers of\ndecadal hiatus periods in the 20th and 21st centuries, Geophys. Res. Lett., 41, 5978–\n5986", "reviewer_doi": "10.1038/nclimate3107).\nReviewer #1 (Remarks to the Author):\nSeptember 6, 2024\nSecond Review for Nat. Comms.\n“A climate change signal in the tropical Pacific emerges from decadal variability”\nBy Jiang, Seager and Cane\nRecommendation: accept subject to minor revision\nGeneral comment:\nOverall, the authors have done a good job in responding to my comments and those from the other\nreviewer, in particular by better defining and distinguishing the characteristics associated with the\nPCC pattern from the IPO. I have only one last issue for them to address.\nLines 50-52: While the authors wrote a very well-thought-out and insightful response to my\ncomment 1, their curt and dismissive one sentence addressing that comment in the revised text\nmostly replays, in truncated form, their “models are wrong” statements they had in the original\nmanuscript, and thus really miss the point that needs to be made here. The issues are subtle but\nvery important to state clearly (reviewer 2 also noted the lack of specificity and clarity in the text in\nhis/her review). I understand the authors are facing length restrictions, but this initial point, which\nprovides the rationale for the rest of their paper, demands a bit more clarification. I suggest\nreplacing the sentence in lines 50-52 with the following:\n“Although debate persists (11-13), especially considering new evidence from high resolution Earth\nsystem models, it has been recognized that a handful of ensemble members from the one degree\nresolution CMIP models can simulate the observed negative IPO phase in the early 21st century\nwith the correct timing. This can only happen when a model ensemble member’s randomly\ngenerated internal variability aligns, by chance, with randomly generated internal variability in the\nsingle realization of the observations. This alignment has a low chance of occurrence, but the\nmodels do have enough correct physics to simulate these internally generated decadal timescale\nevents. However, the models face greater challenges simulating the longer term observed SST\ntrends for 1958-2022 that represent the externally forced response when averaged over both\npositive and negative phases of the IPO during that time period.”\nReviewer #2 (Remarks to the Author):\nI thank the authors for their thorough consideration of my comments and detailed revisions. The\nauthors have satisfactorily responded to my comments, and significantly improved the manuscript.\nThe revised manuscript is well-written and the key messages are much clearer.\nI can now recommend acceptance of the manuscript for publication. I have a few minor additional\ncomments for their consideration, which are listed below. I suggest double checking time periods\nand figure panel references, and subplot titles (a,b,c etc.) again, as there were still a few\ninconsistencies.\n[Detailed comments]\nl. 81 Figure 1c  I think you are referring to Figure 1d?\nl. 90 Fig. 1c  Fig. 1c, lower panel\nl.98  add figure reference\nl.101-102  shouldn’t this be the other way around? I can see positive correlations for P2 and\nnegative for P1 and P3 in Figure 1d. Please double check\nl. 112 the figure title in Figure S1 (d) needs to be corrected. P2 is 1914-1956 and not 1904. I suggest\ndouble checking the other time periods as well to make sure they are all consistent.\nl. 119 pattern corrections  pattern correlations\nl. 139-153 please double check and correct references to Figure panels throughout this paragraph\nas I think some are incorrect\nl. 156 much higher sea level rise  much higher SSH\nl.158 Fig. S3a  please correct the subplot title in Fig.S4. Both subplots are currently labelled as (b).\nl. 239 we call it the PCC, one with distinctive…  Split sentence: we call it the PCC. The PCC is\ncharacterized by distinctive ….\nl.261 remove `\nl. 633 UaTc, VaTa, WcTc  I believe this should be UaTc, VaTa, WaTc? Please double check.\nResponse to Reviewers\nWe would like to thank the reviewers for their helpful suggestions. We have addressed\nthe reviewers’ concerns and implemented useful suggestions in our revised manuscript.\nThe responses are listed below in blue font.\nResponse to Reviewer#1\nGeneral Comments\nOverall, the authors have done a good job in responding to my comments and those\nof the other reviewer, in particular by better defining and distinguishing the\ncharacteristics associated with the PCC pattern from the IPO. I have only one last issue\nfor them to address.\nLines 50-52: While the authors wrote a very well-thought-out and insightful response\nto my comment 1, their curt and dismissive one sentence addressing that comment in\nthe revised text mostly replays, in truncated form, their “models are wrong” statements\nthey had in the original manuscript, and thus really miss the point that needs to be made\nhere. The issues are subtle but very important to state clearly (reviewer 2 also noted\nthe lack of specificity and clarity in the text in his/her review). I understand the authors\nare facing length restrictions, but this initial point, which provides the rationale for the\nrest of their paper, demands a bit more clarification. I suggest replacing the sentence\nin lines 50-52 with the following:\n“Although debate persists (11-13), especially considering new evidence from high\nresolution Earth system models, it has been recognized that a handful of ensemble\nmembers from the one degree resolution CMIP models can simulate the observed\nnegative IPO phase in the early 21st century with the correct timing. This can only\nhappen when a model ensemble member’s randomly generated internal variability\naligns, by chance, with randomly generated internal variability in the single realization\nof the observations. This alignment has a low chance of occurrence, but the models do\nhave enough correct physics to simulate these internally generated decadal timescale\nevents. However, the models face greater challenges simulating the longer term\nobserved SST trends for 1958-2022 that represent the externally forced response when\naveraged over both positive and negative phases of the IPO during that time period.”", "reviewer_2014": "Climate model simulations of the observed early-2000s hiatus of\nglobal warming. Nature Climate Change, 4, 898—902", "reviewer_2016": "Contribution of the Interdecadal\nPacific Oscillation to twentieth-century global surface temperature trends. Nature\nClimate Change, 6"}, "author_response": ""}]

Decision letter