1

Tropical and Antarctic sea ice impacts of observed Southern Ocean warming and2cooling trends since 1949

3

Xiyue Zhang1 and Clara Deser2

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5

1

Department of Physics, University of Nevada, Reno, USA.

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2

National Center for Atmospheric Research, Boulder, USA.

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Corresponding author: Xiyue Zhang (xiyuez@unr.edu)

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Abstract

9Southern Ocean (SO) sea surface temperatures (SSTs) warmed from approximately 1949–197810

and cooled slightly from 1979–2013. We compare the remote impacts of these SO trends using

11

historical coupled model experiments in which the model’s SO SST anomalies are nudged to12

observations. Compared to the control (no nudging) ensemble, the nudged ensemble shows

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enhanced SST warming in the tropical southeast Pacific and Atlantic, and greater Antarctic sea ice

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loss, during the SO warming period: analogous to the impacts of SO cooling but of opposite sign.

15

The SO-driven response in the tropical Pacific (Atlantic) is statistically significant when

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considering the trend difference between the two periods, and accounts for 34% (59%) of the17

observed non-radiatively forced trend. Surface heat budget analysis indicates wind-evaporation-

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SST feedback dominates over shortwave cloud feedback in amplifying the SO-driven SST trends

19in the tropics during the SO warming period, opposite to that for the SO cooling period.

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Introduction

21

Sea surface temperatures (SSTs) averaged over the Southern Ocean (SO) increased from the late22

1940s to the late 1970s and decreased slightly thereafter, in contrast to the nearly monotonic rise23

in global-mean SSTs over the past seven decades (Figure 1a). These warming and cooling trends

24

were accompanied by widespread opposite-signed changes in surface climate over the SO and25

coastal Antarctica as well as in Antarctic sea ice, providing physically-consistent independent

26

evidence for their existence1–3. Whether the sign reversal of the SO and Antarctic trends reflects

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underlying naturally-occurring multidecadal variability as suggested by paleoclimate proxy2

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records and some coupled climate model simulations 4–6, or whether it is a part of the forced

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response to anthropogenic emissions is still under debate 2,7–10.

30

Regardless of its origin, the recent SO SST cooling trend from 1979 to 2013 has been shown to31

drive remote teleconnections to lower latitudes 11,12,9 and Antarctic sea ice expansion 11,13. In

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particular, coupled model experiments reveal that the observed SO cooling induces significant

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cooling in the tropical eastern Pacific and Atlantic via the wind-evaporation-SST (WES)

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feedback mechanism, amplified by positive SST-low-cloud shortwave radiative feedbacks 11,9.

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Idealized studies show an analogous response of the tropical eastern Pacific to Southern

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Hemisphere high-latitude cooling 14–16. The teleconnection pathway from the SO in recent

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decades has significant implications for the role of the “pattern effect” 17,18 in estimated climate

38

sensitivity. This is because the observed cooling in the tropical eastern Pacific opposes the39

expected weakening of the tropical Pacific zonal SST gradient induced by anthropogenic

40

greenhouse gas emissions 19–21. Furthermore, it remains unclear how much of the observed

41

tropical SST trends that are not radiatively forced can be attributed to teleconnections from the

42

SO.

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While the low-latitude and Antarctic sea ice response to the recent SO SST cooling trend has

44

been well studied 11,9, the impacts from the earlier SO SST warming phase have not yet been45

investigated. Here, we broaden the perspective on the role of the SO in tropical climate

46

variability and Antarctic sea ice to include both the SO warming and cooling periods. Our

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experimental protocol follows that of Zhang et al.11 and Kang et al. 9 in which SO SST anomalies

48

in a global coupled model under historical radiative forcing are nudged to follow the observed

49

SST anomaly evolution. This so-called “SO Pacemaker” ensemble is then compared with a50

control historical ensemble without nudging to identify the impact of observed SO SST
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variability on the global climate system. If the mechanisms of the SO-induced teleconnections

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are robust and symmetric with respect to sign, we expect to find a warming of the tropical53

eastern Pacific and Atlantic, as well as reduced Antarctic sea ice, in response to observed SO

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warming during 1949–1978, in analogy with the cooling response during 1979–2013 identified

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previously. However, we note that the spatial pattern of SST trends within the SO differs

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somewhat between the SO cooling and warming phases, which may affect the magnitude of the57

tropical response12. For example, SO SST trend amplitudes are largest in the Pacific sector

58

during the cooling phase (Figure 1c) and the Atlantic sector during the warming phase (Figure

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1d).

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We employ the Community Earth System Model (CESM) version 1 as in Zhang et al.11, which is61

known to be deficient in its SST-low cloud feedback strength over the southeast Pacific 22,9.

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Thus, our results should be viewed as a lower bound on the impact of SO multi-decadal SST

63variability on tropical Pacific climate since 1949. To amplify the signal of the SO-induced

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response, we also examine the difference between the simulated trends during the SO warming65

and cooling periods. This is particularly helpful for obtaining a statistically significant SO-driven

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response over the tropical Pacific where “noise” from internal variability associated with ENSO

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is large. Our study does not address the origin of the SO multi-decadal SST variability, which4

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may be influenced by teleconnections from the tropics. Rather, the objective of our study is to69

quantify the impact of SO SST variability on the tropics and Antarctic sea ice.

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Results

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Observed and simulated SST trends

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The observed SST trends associated with the SO cooling and warming periods reveal somewhat

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distinctive spatial patterns, not only within the SO but throughout the global oceans (Figures 1c74

and 1d). In particular, the SO cooling period features a negative phase of the Pacific Decadal

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Oscillation (PDO) 23/ Interdecadal Pacific Oscillation (IPO) 24, with cooling in the eastern76

tropical Pacific and a zonal dipole pattern of cooling in the east and warming in the west over77

North and South Pacific (Figure 1c). This period also features strong warming in the North

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Atlantic and weaker cooling in the South Atlantic, reminiscent of the positive phase of Atlantic

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Multidecadal Variability (AMV) 25. On the other hand, the SO warming period is characterized

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by a hemispherically asymmetric pattern in both the Pacific and Atlantic sectors, with general81

cooling over much of the northern extratropics and warming in the southern extratropics (Figure821d). The Pacific warming is concentrated in the southeast basin, in sharp contrast to the coherent

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SST trend patterns in the SO cooling period.

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Although the global SST trend pattern during the SO warming period is not exactly opposite to85

that in the SO cooling period, many regions show trend reversals, including southeast Pacific86(Figure 1b), equatorial eastern Pacific, as well as the North and South Atlantic (compare Figures87

1c and 1d). Thus, it is not surprising that these regions also display prominent trend differences88

between the two periods (Figure 1e). In particular, the trend difference exhibits amplified cooling89

within the Atlantic and Pacific sectors of the SO, which extend into the tropical South Atlantic5

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and tropical southeast Pacific (Figure 1e). In addition, the Atlantic shows a strong

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interhemispheric SST gradient that resembles the positive phase of AMV, while the Pacific is92characterized by a strong zonal gradient reminiscent of the negative phase of the PDO/IPO.

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Next, we examine how much of the observed SST trend patterns can be explained by the94

radiatively-forced response, represented by the ensemble-mean of the CESM1 large ensemble

95([LENS], where squared brackets denote ensemble-mean, Figures 1i–1k). The radiatively-forced

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response during the SO cooling period shows a typical global warming pattern with strong97

equatorial warming and muted warming in the tropical southeast Pacific (Figure 1i)26. On the98

other hand, the radiatively-forced response during the SO warming period shows pronounced

99

hemispheric asymmetry with cooling across the Northern Hemisphere and warming in limited

100

regions of the Southern Hemisphere including the tropical southeast Pacific and the Indian sector

101of the SO (Figure 1j). The [LENS] trend pattern during the SO warming period has been102

attributed to anthropogenic aerosol emissions over North America and Europe27,28. The

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difference in the radiatively-forced SST trends between the two periods is characterized by

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enhanced warming in the equatorial Pacific, the western Indian Ocean and the western North and

105South Pacific, with prominent cooling in the tropical southeast Pacific, the Sea of Okhotsk, and106

North Atlantic (Figure 1k). The Atlantic warms overall and has slightly stronger warming to the107north than the south (Figure 1k).

108

When the impact of observed SO SST variability is added to the radiatively-forced response,109

given by the SOPACE ensemble-mean [SOPACE], the simulated SST trend pattern shows

110

greater similarity to observations for both periods (Figure 1f-h). In the SO warming period, the111

SST trend pattern correlation for 40°S to 40°N between [LENS] and observations is 0.42, while

112that between [SOPACE] and observations is 0.55. In the SO cooling period, although the pattern6

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correlations are generally lower, we still find a higher correlation between observations and

114[SOPACE] (0.25) than with [LENS] (0.15).

115

We can isolate the SO-driven response by subtracting the radiatively-forced response from

116

[SOPACE] (e.g., SO-driven = [SOPACE] – [LENS], Figures 1l–1n). As shown in Zhang et al.11,

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SO cooling induces a significant cooling in the tropical South Atlantic but only has a weak118

impact on the tropical Pacific (Figure 1l). SO warming, on the other hand, leads to significant

119

warming in the tropical South Atlantic and a broad warming (albeit not statistically significant)120

in the tropical Pacific that reaches the Maritime Continent (Figure 1m). Furthermore, the North

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Pacific shows a positive PDO pattern in the SO warming period. This could result from the more

122

extensive tropical Pacific warming that reaches the central Pacific, driving an atmospheric123

teleconnection to the North Pacific which then produces a PDO-like SST response. The stronger

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SO-driven teleconnection in the SO warming period may result from the more equatorward

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location of the positive SST trend in the Pacific sector of the SO (Figure 1d).

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Although the tropical Pacific response is not statistically significant in either period, the trend127

difference between the two periods is significant in the equatorial and tropical southeast Pacific128(Figure 1n). This is an important result: it suggests that stronger forcing from the SO (obtained129

here by calculating the trend difference) can result in a statistically significant (at 95%

130

confidence level) response in the tropical Pacific even in a model with deficient SST–low cloud131

feedback strength22,9. Unlike the tropical Pacific, the SO-driven response in the tropical South

132

Atlantic is statistically significant in both periods and in the trend difference. The weaker internal

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variability in the tropical Atlantic29 compared to the tropical Pacific could explain the higher

134

level of statistical significance of the SO-driven response.

135

To further quantify the SO-driven response in the tropics and to consider it in the context of136

internal variability, we average the SST trends within the tropical southeast Pacific and South137

Atlantic (regions highlighted in Figure 1c-e) for each ensemble member of SOPACE and LENS

138

(Figure 2a and 2b). In the tropical southeast Pacific, the SOPACE distribution is shifted slightly

139

towards the observed value compared to the LENS distribution in both periods, although there is

140

considerable spread across members due to internal variability (Figure 2a). When we consider

141

the trend difference between the two periods, while the observed value would be an outlier in

142

LENS, it is no longer an outlier in SOPACE. This suggests that the inclusion of observed SO

143

SST variability increases the likelihood that CESM1 can simulate the magnitude of the observed

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SST trend difference in the tropical southeast Pacific.

145

A more prominent impact of SO SST variability is found in the tropical South Atlantic. As

146

pointed out by Zhang et al. 11, SO cooling induces significant cooling in the tropical South

147

Atlantic, making the SOPACE ensemble distinct from the LENS ensemble (Figure 2b). The

148

observed SST trend lies within the middle 50th percentile of the SOPACE distribution. As for the149

SO warming period, although the observed SST trend is outside of the range of both SOPACE

150

and LENS distributions, the SOPACE ensemble is significantly warmer and closer to the151

observed trend than the LENS ensemble. The trend difference between the two periods in this152

region is characterized by two contrasting ensembles: all LENS members show positive values,

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while nearly half of SOPACE members show negative values consistent with the sign in154

observations.

155

Next, we quantitatively assess SO’s contribution to observed SST trends in the tropical southeast

156

Pacific and South Atlantic. Because there is little resemblance between the SO SST trends in157

observations and those simulated in [LENS], we conclude that SO warming and cooling are not a158

radiatively forced response in CESM1. We then subtract the radiatively-forced response [LENS]

159

from observations to represent the observed SST trends that are not radiatively forced in the160

tropical southeast Pacific and South Atlantic (black bars on Figures 2d and 2e). A part of this161

unforced SST trend can be attributed to the SO, which is represented by the SO-driven response

162([SOPACE] – [LENS], green hatched bars on Figures 2d and 2e). For both periods in both163

basins, the SO-driven response has the same sign as the observed unforced SST trends (Figures164

2d and 2e).

165

In the tropical southeast Pacific, the SO-driven response explains 19% of the observed unforced

166

SST trend in the SO cooling period. This is in sharp contrast to the SO warming period, where167

the SO-driven response explains 113% of the observed unforced warming. This suggests that168

other modes of variability act to cool the tropical southeast Pacific during this period. When we

169

combine the two periods, 34% of the observed unforced SST trend difference can be explained

170by the SO (Figure 2d). The tropical South Atlantic shows an even larger contribution from the171

SO (Figure 2e). In this region, the SO-driven response accounts for 85% of the observed

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unforced cooling, 47% of the observed unforced warming, and 59% of the observed unforced

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trend difference. These results point to a major role for the SO in driving multi-decadal SST

174

trends in the tropical southeast Pacific and South Atlantic.

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Surface mixed-layer heat budget analysis

176

Kim et al.22 probed the mechanisms for the SO-driven equatorward teleconnection using

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idealized coupled model experiments in which the zonal-mean solar insolation over the SH

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extratropics (45º–65ºS) is abruptly reduced by 0.8 PW (equivalent to 1.6 W/m2 in the global

179mean). They found that the dominant mechanism for the transient SST response involves an

180

initial northward advection of the high-latitude SST anomalies into the subtropics via the

181

climatological winds on a time scale of a few years, followed by amplification within the182

subtropical southeast Pacific via the wind-evaporation-SST feedback, coastal upwelling, and183

subtropical low-cloud feedback.

184

While it is difficult to analyze the transient adjustment pathways in our time-evolving SOPACE

185

simulations, we can quantify how processes suggested by Kim et al.22 contribute to the SO-

186

driven SST response in the tropics by diagnosing the upper ocean mixed-layer heat budget 26,30,14

187

following the procedure in Zhang et al. 11. Briefly, the mixed-layer heat storage is determined by188

net surface shortwave and longwave fluxes, sensible and latent heat fluxes, and heat flux due to189

ocean dynamics. The dependency of latent heat flux on SST (Newtonian cooling) enables us to

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diagnose SST trend (denoted by superscript ) based on trends of radiative and turbulent heat191

flux terms:
=−

192

193
194

Here,

is SST,

=

(

+

+

≈ .

K-1,

is shortwave flux,

+

+

+

+

)

(1)

is latent heat flux (overbar denotes climatology),

is longwave flux,

is sensible heat flux, andis heat flux due to195

ocean dynamics. The latent heat flux

is decomposed into atmospheric forcing due to changes

196

in near-surface wind speed (197

temperature difference (198

We analyze the surface heat budgets for SST trends during the SO cooling and warming periods,

199

as well as the difference in trends between the two periods. First, we compare the SO-driven SST

200

trends from [SOPACE] – [LENS] (Figure 3a-c) with those estimated from equation (1) (Figure

2013d-f). The general cooling and warming patterns in the tropical oceans are qualitatively captured

202

by the net surface heat budget calculation, but their amplitudes are overestimated especially in203

the cooling period. In the SO warming period, the heat budget quantitatively captures the204equatorial warming trend maxima in all three ocean basins, the meridional dipole in the Atlantic,

205

and the zonal gradients in the Indian Ocean and North Pacific (Figure 3e). However, in the SO

206

cooling period, the heat budget overestimates the equatorial cooling maxima (Figure 3d), which

207

results in exaggerated tropical cooling in the difference between the two cooling and warming

208

periods (Figure 3f). This overestimation may be due to nonlinear interactions between the LH), near-surface relative humidity (), and air-sea, see Methods for more details).

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terms, or errors in estimating the air-sea temperature difference due to the extrapolated 2-m air

210

temperature.

211

Among the terms in equation (1), the shortwave flux

212

dynamics

213, latent heat flux

, and ocean

have the most prominent contributions to the SST trends in both periods (are small, Figure S1). We will focus our discussion on

214

a residual term and harder to interpret physically.

215

•

and

, as

and

is computed as: As highlighted in Zhang et al. 11, the shortwave flux plays a dominant role in the SST

216

cooling off the west coasts of South America and Africa (Figure 3g). This is due to the local

217

positive low-cloud feedback that contributes to SO-driven cooling 22,9. Indeed, we find high218

spatial correlation between the responses of cloud liquid water path and shortwave cloud219

radiative effect (which dominates the net shortwave flux, Figure S2). Interestingly, we also

220

find shortwave cooling (and a corresponding increase of liquid water path) off the coast of221

Chile that extends to the northwest during the SO warming period (Figure 3h). This may

222

seem counterintuitive, as subtropical low cloud fraction is expected to decrease with SST

223

warming 31, which is the case in the subtropical Atlantic. However, other factors such as

224

estimated inversion strength or horizontal temperature advection can also affect low clouds in225

the subtropical Pacific 32.

226•: In the SO cooling period,

dominates the equatorial Atlantic via southeasterly227

surface wind anomalies (Figure 3j). In the tropical Pacific,

contributes to cooling in228

the northeast and near the South Pacific convergence zone. In the SO warming period,229

is the main contributor of the SST warming in the tropical Pacific and Atlantic via

230

northwesterly surface wind anomalies (Figure 3k). The difference between the two periods is
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dominated by232

Atlantic and Pacific driven by SO cooling (Figure 3l). The contributions from

233
234

, suggesting strong wind-induced latent heat cooling in the equatorial

are not consistently robust in both periods comparing toand, although locally they

can be important (Figure S1).

235

To summarize, while shortwave cloud feedback plays a major role in amplifying the SO-driven

236

cooling in the tropical southeast Pacific and South Atlantic, this is not the case for the SO

237

warming period. Wind-induced latent heat flux, hence the wind-evaporation-SST feedback,238

dominates the SO-driven surface heat budget during the SO warming period.

239

Antarctic sea ice response

240

We compare the simulated Antarctic sea ice concentration trends for the SO warming and241

cooling periods, with and without the influence of observed SO SST variability. Antarctic sea ice

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concentration trends in the SO cooling and warming periods in [SOPACE] share some similar243

features, with a pattern correlation of 0.73 (Figures 4b and 4c). For example, there is significant

244

sea ice loss in the Weddell Sea and the Indian sector north of 60°S, while south of 60°S in the

245

Indian sector the sea ice fraction trend is positive. However, the contribution from radiative

246

forcing differs in the two periods: in the SO cooling period, [LENS] shows ice loss nearly

247

everywhere (Figure 4e), while in the SO warming period, the [LENS] sea ice trends are weaker248

and less homogeneous (Figure 4f). The trend difference between the two periods shows a nearly249

opposite pattern for [SOPACE] and [LENS] (Figure 4d and 4g), suggesting that the SO-driven

250

response tends to oppose the radiatively-forced sea ice loss.

251

Indeed, the SO-driven sea ice response is opposite to [LENS] in both periods (Figure 4h and 4i).

252

The pattern correlation between SO-driven and [LENS] sea ice trends is -0.63 for the SO cooling
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period and -0.30 for the SO warming period. Furthermore, the sea ice trend differences between

254

the two periods are almost exactly opposite between SO-driven and [LENS], with a pattern255

correlation of -0.85. This further highlights the opposing effect of radiative forcing (which leads

256

to ice loss) and SO SST cooling (which leads to ice gain) on Antarctic sea ice trends.

257

The inclusion of observed SO SST variability also affects individual ensemble members by

258

narrowing the ensemble range of total Antarctic sea ice extent (SIE) trends (Figure 2c). For the259

SO cooling period, all LENS members show negative SIE trends, while a few SOPACE

260

members show positive SIE trends that are consistent in sign with the observed trend, albeit

261

weaker in magnitude. SO-driven sea ice gain can explain 54% of the observed unforced SIE

262

trend during the SO cooling period (Figure 2f). For the SO warming period, a few LENS

263

members show positive SIE trends while all SOPACE members show negative SIE trends.

264

Although there are no passive-microwave satellite measurements of Antarctic sea ice before

265

1979, visual satellite imagery beginning in 1973 suggests there was a marked decrease in SIE

266from 1973-19791. Reconstructed Antarctic SIE suggests a weak negative trend during the SO

267

warming period; this trend lies near the middle of the LENS distribution and at the upper end of268

the SOPACE distribution (Figure 2c). Overall, SOPACE members show more sea ice loss during

269

the SO warming period than LENS members, though the range of SOPACE lies fully within the270

range of LENS (Figure 2c). The trend difference between the two periods, however, shows ice

271

loss in nearly all LENS members but ice gain in nearly all SOPACE members. Thus, in the trend272

difference, observed SO cooling more than offsets the radiatively forced response, leading to a273

net gain in Antarctic sea ice in nearly all ensemble members of SOPACE. Only the SOPACE

274

ensemble can capture the positive reconstructed Antarctic SIE trend difference. While the SO-

275

driven Antarctic sea ice response explains more than 50% of the observed and reconstructed
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unforced Antarctic SIE trend during the SO cooling period, its contribution in the SO warming

277

period is much weaker. The SIE trend difference is dominated by the SO cooling period, where278

SO-driven response explains 77% of the reconstructed Antarctic SIE trend difference (Figure 2f).

279

Discussion

280

We have broadened the perspective on the role of the SO in recent tropical climate trends by281

introducing a SO Pacemaker ensemble for the period of SO warming (1949-1978) using the282same protocol as Zhang et al. 10. Combined with Zhang et al.’s SOPACE experiments for the SO

283

cooling period (1979-2013), this new ensemble allows us to assess the robustness of the284mechanisms of the SO induced teleconnections and whether they are symmetric with respect to285

the sign of the SO SST trends. It also allows us to strengthen the signal of the SO-induced

286

response by computing the difference in trends between the SO cooling and warming periods.

287

We find that the SO-driven response in the tropical southeast Pacific is statistically significant

288

when we consider the trend difference between the two periods and accounts for 34% of the289

observed unforced trend difference. In the tropical South Atlantic, the SO-driven response

290

explains 59% of the observed SST trend difference that is not radiatively-forced. In both the291

tropical southeast Pacific and South Atlantic, SO-driven cooling offsets radiatively-forced

292

warming in the observed SST trend difference. The inclusion of SO SST variability allows the293

model ensemble to better capture the observed tropical SST trends and Antarctic sea ice trends,

294

as well as reconstructed Antarctic SIE trends before 1979.

295

With our existing experiments, we cannot isolate the relative roles of the Atlantic and Pacific296

sectors of the SO on influencing the tropical oceans. However, we find that during the SO

297

warming period, the Atlantic sector of the SO warmed nearly twice as much as the Pacific sector

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of the SO, with a similar ratio of SO-induced warming between the tropical South Atlantic and299

southeast Pacific. But during the SO cooling period, the Pacific sector of the SO cooled more

300

than the Atlantic sector, yet the SO-driven cooling in the tropical southeast Pacific was less than301

the cooling in the tropical South Atlantic. This contrasts with the results of Dong et al. 12 who

302

used slab-ocean experiment with prescribed q-flux cooling in the eastern Pacific and Atlantic

303

sectors of the SO separately. They found that for the same magnitude of cooling, the eastern

304

Pacific sector of the SO drives in stronger cooling response in the equatorial eastern Pacific305

compared to the Atlantic sector of the SO. Further coupled model experiments are needed to306

investigate the regional impacts of SST variability from different sectors of the SO.

307

While we have confirmed that by differencing the SO warming and cooling periods, the SO-

308

driven tropical Pacific response becomes stronger, we also acknowledge that the magnitude of309

this response is sensitive to the strength of the shortwave cloud feedback 15. Contrary to previous

310

studies that highlight a prominent role of the shortwave low cloud feedback 22, here we find a311

weaker contribution from the shortwave flux in the SO warming period. This is not surprising,312

given that the shortwave cloud feedback in CESM1 is known to be weaker than observed 22,9.

313

Given this sensitivity, it would be immensely valuable to conduct long historical SO Pacemaker

314

experiments with other coupled models. Additionally, the role of mean state biases in the315

strength and pattern of the SO-driven response warrants future investigation with targeted316

numerical experiments.

317

A major implication of the tropical warming induced by observed SO warming is that future SO

318

warming may also contribute to tropical Pacific and Atlantic warming. Because the SO SST

319

warming is delayed due to SO heat uptake2, on centennial time scales it could contribute further

320

to the projected tropical warming. On the other hand, modeling evidence suggests that enhanced
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melting from Antarctic Ice Sheet can lead to SO cooling that further influences tropical SST 33–

322

35

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contribution to the projected evolution of tropical Pacific and Atlantic SSTs.

324

Methods

325

CESM1 pacemaker simulations

326

The original “SO Pacemaker” (SOPACE) simulations include a 20-member ensemble for the327

period 1975–2013 using CESM1 11. Here, we use the same model and experimental protocol, but

328

for the earlier period 1945–1978. Briefly, we conduct a 20 member ensemble of SOPACE

329

simulations with the global fully-coupled CESM version 1.1.2 at 1º horizontal resolution under330

historical radiative forcing. For each member, the model’s SST anomalies (e.g., deviations from331

the model’s seasonally-varying climatology) are nudged to the observed SST anomaly evolution

332

south of 40ºS with a linear buffer zone at 35–40ºS. For consistency, we use observed SSTs from333

the NOAA Extended Reconstruction Sea Surface Temperature version 3b (ERSSTv3b) data set

334

on a 2º grid36. All 20 SOPACE members are initialized from the first member of the 40-member

335

CESM1 Large Ensemble (LENS)37 on 1 Jan 1920, with a random initial atmospheric temperature

336

perturbation of O(10-14) K to create ensemble spread. The first 4 years of the simulations are

337

considered as spin-up and excluded from trend calculations. The ensemble mean of LENS,

338

denoted [LENS], represents the model’s radiatively-forced response, and the ensemble mean of

339

SOPACE, denoted [SOPACE], represents the model’s radiatively-forced response plus the. The relative balance and time scales of the two processes will affect the SO’s ongoing

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response to observed SO SST variability. The difference between [SOPACE] and [LENS], which341

we call the SO-drive response, isolates the influence of observed SO SST variability.

342

Statistical methods

343

Linear trends over the early SO warming period (1949–1978) and the late SO cooling period344(1979–2013) are calculated from annual averages of monthly anomalies for observations,

345

Antarctic SIE reconstruction, and both the ensemble–mean and individual members of LENS

346

and SOPACE. We also calculate the difference in trends between the SO cooling and warming

347

periods, where the trends in each period are expressed in units of decade-1 in order to compare

348

their rates of change. The observed and ensemble-mean trend significance for either the SO

349

cooling or warming period is assessed using the two-sided student’s t-test adjusted for350

autocorrelation38,39 at 95% confidence level. The statistical significance of the difference

351

between the trends for the SO warming and SO cooling periods in observations is assessed by352

comparing the adjusted 95% confidence intervals of trends estimated with the two-sided

353

student’s t distribution38. Regions without overlapping trend intervals are interpreted as having

354

statistically significant trend differences. For simulations, the significance of the trend difference

355

between two periods is assessed by comparing whether the ensemble-mean of each period is356

different relative to the ensemble spread of the trends in each period using a two-sided student’s

357

t-test at 95% confidence interval.

358

Observational data359

We compare the model’s simulated SST trends with the ERSSTv3b data set at 2° global

360

resolution (i.e., the same data set used for the Pacemaker ensemble), and the model’s simulated

361

Antarctic sea ice concentration trends with the passive-microwave NASA Goddard Bootstrap
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version 2 sea ice product on a 25 km x 25 km grid 40, which begins in 1979. We also use the363

reconstructed Antarctic sea ice extent 3 to compare the model’s simulated Antarctic sea ice extent

364

trend for both periods.

365

Mixed-layer budget366

In equation (1), the trend of heat storage on the left hand side is negligible11. This allows us to367

compute the heat flux due to ocean dynamics as a residual term. To diagnose the SST trends with368

equation (1), we start with the approximated surface latent heat flux formula

369

−

370

transfer coefficient,371

atmospheric model level,372

difference,

( −

)

(

), whereis the latent heat of vaporization,is the wind speed at 10 m,=≈ .

is air temperature at 2 m,

=

K-1,

is theis the relative humidity at the lowest=

is SST, and−is the air-sea temperatureis the saturation specific

19

373
374

=

humidity. We can linearize the latent heat flux trend (superscript ) as
+

375

=

376

=

377

=

+

=

+

. The last 3 right-hand-side terms are defined as

,

(2)

=−

=−

, (3)

,

(4)

378

while the first term of the right-hand-side is the SST damping term=379

and S1 show the SST contributions from these terms normalized by −.

380

Data availability

381

The full CESM1 LENS dataset is available from NCAR’s Climate Data Gateway at382

https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.cesmLE.html. The ERSSTv3b data383

are available at NOAA Physical Sciences Laboratory384

https://psl.noaa.gov/data/gridded/data.noaa.ersst.v3.html. The sea ice data are available at the

385

National Snow and Ice Data Center. The satellite sea ice data are available at386

https://nsidc.org/data/nsidc-0079/. The reconstructed Antarctic sea ice extent data are available at387

https://doi.org/10.7265/55x7-we68. The CESM1 SOPACE dataset is available upon request

388

from the corresponding author.

389

Code availability. Figures 3

20

390

The Python code used to generate manuscript figures is available upon request from the391

corresponding author.

392

Acknowledgments393

We thank the editor and two anonymous reviewers for their constructive comments that have394

improved the article. This study was partially supported by the Advanced Study Program

395

postdoctoral fellowship from the National Center for Atmospheric Research (NCAR) and the396

National Science Foundation (NSF) Office of Polar Programs. The materials are based upon

397

work supported by NCAR, which is a major facility sponsored by the NSF under cooperative398

agreement 1852977. The authors would like to acknowledge high-performance computing

399

support from Cheyenne provided by NCAR’s Computational and Information Systems

400

Laboratory, sponsored by the NSF.

401

Competing interests

402

The authors declare no Competing Financial or Non-Financial Interests.

403

Author contributions

404

Both authors designed the research, discussed the results, and wrote the manuscript. X. Z. carried

405

out the experiments and analyzed data.

21

406

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511

Figure 1. Observed and simulated SST for the SO cooling period (1979–2013) and SO

512

warming period (1949–1978). Time series of observed (a) global mean (black) and SO (blue),513

and (b) tropical southeast Pacific (green, region highlighted in Figure 1c–e) SST anomalies from

514

ERSSTv3b. Thin lines show the annual-mean anomalies, while the thick lines show smoothed

515

time series with 10-year running mean. Red shading indicates the SO warming period and blue

516

shading indicates the SO cooling period. SST trend maps from ERSSTv3b (c–e), SOPACE

517

ensemble mean (f–h), LENS ensemble mean (i–k), and SO-driven ([SOPACE]-[LENS], l–n).

518

Left column is for the SO cooling period, middle column is for the SO warming period, and right519

column is the difference between two periods. Dashed lines indicate 50°S and 70°S. Regions

520

with statistically significant trends at 95% level are stippled.

521

Figure 2. Observed and simulated trends of tropical SST and Antarctic sea ice. (a) Tropical522

southeast Pacific SST trends, (b) tropical South Atlantic SST trends, and (c) Antarctic sea ice

523

extent (SIE) trends. Box and whiskers show the distribution of ensemble members from524

SOPACE (orange) and LENS (blue) in the SO cooling period, SO warming period, and525

difference between the two periods. The box extends from the first quartile to the third quartile,526

with the line showing median value. The whiskers extend from the box to the farthest data point527

lying within 1.5x the inter-quartile range from the box. Observed values are shown by the black528

horizontal lines, and reconstructed SIE trends are shown by magenta horizontal lines. Individual529

ensemble members are shown in dots. Bottom panels show the SO-driven response (green

530

hatched bars) and observed unforced trends (black bars) of (d) tropical southeast Pacific SST, (e)531

tropical South Atlantic SST, and (f) Antarctic SIE. Reconstructed unforced SIE trends are shown532

in magenta bars.

27

533

Figure 3. Mixed-layer budget for SO-driven SST trends. Left column shows the SO cooling

534

period, middle column shows the SO warming period, and right column shows SO cooling–535

warming difference. Simulated SST trends (a–c) are compared to the SST trends computed from536

the surface energy budget (d–f). Terms that dominate the contribution to the SST trends include

537(g–i) surface net shortwave flux

538

dynamics

539

are shown in gray grids.

540

Figure 4. Observed and simulated Antarctic sea ice fraction trends. Left column shows the541

SO cooling period, middle column shows the SO warming period, and right column shows SO

542

cooling–warming difference. (a) Observed trends, (b-d) SOPACE ensemble mean trends, (e-g)

543LENS ensemble mean trends, (h-j) SO-driven trends. Regions with statistically significant trends544

at 95% level are stippled.

, (j–l) wind-induced latent heat flux

, and (m–o) ocean

as a residual. Latitudes of 20°S, 0°, 20°N and longitudes of 0°, 90°W, 180°, 90°E

28