Introduction

Since the early 1980s, the ozone hole has formed each boreal autumn in Antarctica, where about half of the total ozone column (TCO) is depleted1. The impact of the Antarctic ozone hole on the tropospheric climate of the Southern Hemisphere (SH) has been widely researched in previous studies2,3,4,5,6,7,8,9,10. The main physical mechanism is that the ozone depletion cools the stratosphere and enhances polar vortex, leading to a strengthening of the westerly wind and a poleward shift in the position of the mid-latitude jet. This phenomenon is associated with the positive phase of the Southern Annular Mode (SAM)11,12, which is the leading mode of extratropical variability in the SH13,14,15,16. Although the increase in greenhouse gases also contributes to a positive boreal winter SAM trend17,18,19,20,21,22,23, ozone depletion is demonstrated by numerical experiments as the most dominant factor of the trend of the SAM22,24,25.

The Antarctic ozone hole has not only played a role in long-term climate changes, but also influenced the interannual variability of the SH surface climate26. The year-to-year variability of Antarctic ozone depletion is mainly due to interactions between planetary waves, the mean circulation, gravity wave drag, and the quasi-biennial oscillation27. This interannual variability of ozone is also closely linked to variability in the SAM and the climate in the SH. Fogt et al.28 have demonstrated a significant relationship between boreal autumn TCO variability at the South Pole and the SAM, extending up to four months later28. Son et al.26 have suggested a noteworthy negative correlation between September ozone concentration and the October SAM index, leading to systematic variations in precipitation and surface air temperature throughout the SH26. Moreover, Bandoro et al.2 have proposed that the significant correlations between the detrended Antarctic TCO in November and winter surface temperatures in the SH midlatitudes are due to the link between boreal autumn ozone and winter SAM2. In addition to the observations, current chemistry-climate models can successfully replicate the observed relationship between boreal autumn ozone and winter Australian climate3. Antarctic ozone during boreal autumn, therefore, is likely to be a favorable factor for predicting subsequent boreal winter conditions in the SH, with the SAM playing a pivotal role in bridging the connections between them.

The climatic impacts of the SAM are not limited to the SH29,30,31,32,33, as many studies have suggested potential relationships between SAM and anomalous climate events in the Northern Hemisphere (NH). Wu et al. have revealed that the boreal autumn SAM exhibits a close linkage with the variability of the China winter monsoon34. In addition, through the ocean-atmosphere coupled bridge, a significant negative correlation has been observed between the boreal spring SAM and the following East Asian summer monsoon35,36. Zheng et al. have found that the boreal winter SAM influences precipitation over South China in the following spring37. Furthermore, the November–December SAM exhibits a significant inverse relationship with the winter precipitation over East Asia, particularly in southern China38. These studies all demonstrate that the SAM also serves as an important forecasting indicator for the climate of the NH in the subsequent season.

Given that Antarctic ozone anomalies contributes to the variability of the SAM, and the SAM is closely associated with the climate of East Asia, we propose the following hypothesis: Could Antarctic ozone potentially influence the East Asian climate through its connection with the SAM? In this study, we identify a noteworthy positive correlation between Antarctic TCO during SO and the following boreal winter precipitation in East Asia. Potential underlying physical mechanisms are illustrated as well. The structure of the paper is organized as follows. We begin by describing the relationship between Antarctic TCO during SO and East Asian winter precipitation. Following this, we discuss the physical mechanism through which ozone influences the SAM-related Indian Ocean tripole sea surface temperature anomalies (SSTA). Subsequently, we illustrate the impact of these SSTA on outgoing longwave radiation (OLR) over the Maritime Continent (MC) via ocean-atmosphere interactions. We then explore the potential influence of OLR over the southern MC on East Asian winter precipitation. Finally, we present the results of numerical experiments that assess the climatic impacts of Antarctic ozone on East Asian winter precipitation.

Results

Relationship between the SO Antarctic TCO and the East Asian winter precipitation

To ensure the reliability of Antarctic ozone data obtained from ECMWF Reanalysis 5th Generation (ERA5), we conduct a comparison between the ozone index at 75°S, 25°W calculated using ERA5 data and that derived from the ground-based ozone data collected at Halley station (75°S, 25°W). The correlation coefficient between the two indices reaches 0.96 (confidence level >99.9%), suggesting a high level of agreement and justifying the use of Antarctic ozone data derived from ERA5 (Supplementary Fig. 1).

Based on the monthly-mean Antarctic TCO (Fig. 1a), a gradual decline is observed from July onwards, reaching its lowest values during September to October (SO), falling below 220 DU. The main reason for this is due to the return of sunlight to the cold polar stratosphere during SO, releasing halogens such as chlorine and fluorine, thus catalyzing the decomposition of ozone39. Since the Antarctic TCO reaches its minimum and exhibits the largest standard deviation during SO, we primarily focus on the climatic impacts of interannual variations in Antarctic ozone during this period. To quantitatively measure such variations, the Antarctic TCO index (ATCOI) is defined as the detrended TCO averaged within the Antarctic region (180°W–180°E, 60°–90°S) from September to October. The time series of ATCOI shows a decline trend from 1979 to around 2000, primarily attributed to the catalytic chemistry involving man-made chlorofluorocarbons (Fig. 1b). After 2000, the index has experienced a slight increase trend, coinciding with the implementation of the Montreal Protocol and its global emission-reduction impact. Throughout the entire researched period from 1979 to 2022, ATCOI exhibits no significant trend.

Fig. 1: Monthly mean Antarctic TCO and time series of ATCOI.
figure 1

a Monthly mean of TCO (black line; DU) in Antarctic region (180°W–180°E, 60°–90°S) and its standard deviations (shadings; DU) from January to December. b Time series of the normalized ATCOI defined by the TCO averaged in Antarctic region from September to October. Black line denotes the original ATCOI and blue line denotes the detrended ATCOI.

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Figure 2a presents the regression of East Asian precipitation anomalies in boreal winter against the ATCOI. Significant positive correlations between the ATCOI and December–February (DJF) precipitation dominate East Asia, expanding northeastward from southern China to the oceanic areas south of Japan. This indicates that a higher ATCOI is typically followed by increased winter precipitation over East Asia, and vice versa. Specifically, the ATCOI accounts for ~10% of the total variance in DJF precipitation along southern China to southern Japan and around 15% of the variance over northeastern China (Fig. 2b).

Fig. 2: Precipitation anomalies in DJF associated with SO ATCOI.
figure 2

a DJF precipitation anomalies regressed against the SO ATCOI (shadings; mm/day). The dotted areas exceed the 90% confidence level. b The DJF precipitation fractional variances explained by the SO ATCOI (shadings; %).

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To further explain the observed precipitation pattern, the wind anomalies at 850 hPa regressed against the ATCOI are examined (Supplementary Fig. 2). The results reveal anomalous southwesterly wind in East Asia, particularly in the southern Yangtze-Huaihe River Basin. During winter, specific humidity generally declines from the tropics to the mid-latitudes (shadings in Supplementary Fig. 2). Concurrently, the southwesterly wind anomalies transport abundant moisture from the tropics to East Asia, contributing to positive winter precipitation anomalies regionally (red vectors in Supplementary Fig. 2). On the other hand, influenced by the East Asian winter monsoon, East Asia experiences an abundance of cold air blowing in from the north40. When the cold air mass encounters warm and moist air flowing in from the south, it becomes more favorable for the generation of winter precipitation in East Asia.

Antarctic ozone anomalies influence southern Indian Ocean SSTA through SAM

This raises the question: how does the preceding ATCOI influence winter atmospheric circulations and contribute to the observed winter precipitation anomalies in East Asia? Given the lag between ATCOI and the observed winter precipitation, and the capacity of SST to store atmospheric signals for a period, we hypothesize whether SSTA could serve as a crucial link between ATCOI and East Asian precipitation.

As seen in Fig. 3a, a significant tripole pattern of SSTA during September–November (SON) associated with ATCOI is observed in the SH Indian Ocean, characterizing by negative SSTA around 40°S and positive SSTA near 20°S and 60°S. Such a SSTA pattern can persist from boreal autumn through boreal winter. How does the variability of Antarctic ozone lead to the observed SSTA described above?

Fig. 3: SSTA distribution associated with SO ATCOI.
figure 3

SSTA (shadings; K) in a September–November (SON), b October-December (OND), c November–January (NDJ), d December–February (DJF) regressed against the detrended SO ATCOI. The dotted areas exceed the 90% confidence level. To quantify the ozone-induced SSTA variability, a southern-hemisphere Indian Ocean Tripole (SHIOT) is defined as the difference in the area-averaged SSTA between the red box (30°–10°S, 40°–70°E; 65°–50°S, 59°E–160°W) and the blue box (50°–30°S, 40°–70°E).

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In the first section of the paper, we have proposed the hypothesis that Antarctic ozone could affect East Asian climate by influencing the SAM. Moreover, previous studies have shown that the SAM affects SSTA in the SH through atmosphere-ocean interactions41,42,43. Therefore, it is reasonable to speculate that the SAM acts as a mediator connecting ozone and the observed tripole SSTA in the Indian Ocean.

In our study, we find a close relationship between ATCOI and the SAM index (SAMI) during SON, with a significant correlation coefficient of −0.38 (confidence level >95%). This indicates that the increase of Antarctic ozone corresponds to the negative phase of SAM, which is consistent with earlier findings3. The potential underlying physical mechanisms governing the influence of ozone on the SAM have been extensively discussed and can be broadly categorized into several factors: the ozone effect on wave fluxes of heat in the lower troposphere11, the radiative and dynamical forcing of the near-surface temperature gradient11,44, etc.

To investigate whether SAM serves as a bridge linking ozone and SSTA, we first illuminate the overlying atmospheric circulation associated with the inverse SAMI. According to Fig. 4a, during negative phase of SAM, a seasaw pattern with the negative sea level pressure (SLP) anomalies near 40°S and the positive SLP anomalies south of 60°S over the SH Indian Ocean is observed. Compared with the climatology of wind fields (black vectors in Fig. 4a), the winds are weakened at high latitudes and around the eastern region of Madagascar (green vectors in Fig. 4a), leading to a reduction in the evaporation of the sea surface. This, in turn, is likely to warm the sea surface temperature (SST) at high latitudes and 20°S due to the wind-evaporation-SST (WES) feedback. Meanwhile, the wind anomalies associated with the inverse SAMI intensify the prevailing westerly winds around 40°S (green vectors in Fig. 4a), thereby amplifying the evaporation of the sea surface and potentially inducing regional cooling. Our findings align with prior research, indicating that a low SAM index induced by high ozone concentration is typically associated with surface westerly wind anomalies in midlatitudes30. When regressing ATCOI onto the same atmospheric circulation field (Supplementary Fig. 3), a similar pattern of pressure and wind anomalies to those related to the inverse SAMI is found. These results suggest that Antarctic ozone may lead to observed circulation patterns via SAM.

Fig. 4: The surface flux anomalies and SSTA associated with inverse SAM during SON.
figure 4

Regression of a 10 m wind anomalies (green vectors; m/s) and SLP anomalies (shadings; hPa), the surface b Ekman, c radiative, d turbulent, e net heat flux anomalies (shadings; W/m2) and f SSTA on the inverse SAMI (shadings; K) during SON. Positive values in (b–e) refer to the ocean gaining heat, and vice versa. The black vectors in (a) denote the climatological 10-m wind (m/s). The green vectors and the dotted areas exceed the 90% confidence level.

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To further understand the physical mechanism of the variability of SSTA related to the inverse SAMI, we conduct a regression analysis between the inverse SAMI during SON and concurrent surface heat flux (Fig. 4b–e). In response to the negative phase of the SAM, the Ekman heat transport typically exhibits a seasaw zonal pattern, characterized by positive Ekman heat flux anomalies influencing the subpolar region, while negative anomalies are observed in midlatitudes (Fig. 4b). These conditions promote the development of warm SSTA in high latitudes and cold SSTA in midlatitudes. However, the significance of the positive Ekman heat flux diminishes around the subtropical region, suggesting that the SAM-related Ekman transport might be restricted to mid-high latitudes42. Apart from the Ekman flux, the SSTA are greatly influenced by the response of the net radiative (Fig. 4c) and turbulent heat fluxes (Fig. 4d). Both two fluxes exhibit positive anomalies over the eastern Madagascan and negative anomalies over midlatitudes. According to the sum of the above three heat flux, the inverse SAMI exhibits a tripole pattern over the SH Indian Ocean (Fig. 4e), substantially contributing to the observed tripole SSTA (Fig. 4f). This is consistent with a previous finding indicating that during negative phases of the SAM in boreal autumn, negative SSTA between 30°–45°S and positive SSTA between 45°–70°S are induced43. Noticeably, the SAM-related SSTA pattern resembles the SSTA regressed against ATCOI (Fig. 3a), especially in SH Indian Ocean.

From the foregoing analysis, it is seen that ATCOI can induce a SAM-related meridional tripole SSTA pattern in Indian Ocean through the thermodynamic and dynamic processes during SON. The ocean can then retain the anomalous SAM signal43, allowing the SSTA to persist through the following winter due to the thermal inertia of the oceans.

Coupled Model Intercomparison Project Phase 6 multi-model ensemble (CMIP6 MME) is employed to verify the impact of Antarctic ozone during SO on tripole SSTA in Indian Ocean during boreal winter. The ATCOI derived from the CMIP6 MME is regressed against the boreal winter SSTA fields in CMIP6 MME. According to Supplementary Fig. 4, a significant tripole pattern of SSTA in DJF is induced, characterized by positive SSTA around 60°S and Eastern part of Madagascar, and negative SSTA around 40°S. The results are generally consistent with the observed findings, providing robust evidence that the tripole SSTA in the Indian Ocean during boreal winter can indeed be induced by Antarctic ozone variations during SO.

The role of the southern Indian Ocean SSTA on the OLR anomalies over MC

To quantitatively depict the variability of such ozone-induced SSTA, an SH Indian Ocean Tripole index (SHIOT) is defined as the difference in the area-averaged SSTA between the red box (30–10°S, 40–70°E; 65–50°S, 59°E–160°W) and the blue box (50–30°S, 40–70°E) in Fig. 3. The correlation coefficients between ATCOI and detrended SHIOT reaches 0.71 (confidence level >99.9%) during SON and 0.53 (confidence level >99.9%) during DJF. Such consistency allows us to consider SHIOT SSTA as capable of storing oceanic memory to prolong the impact of SO Antarctic ozone.

How does the SHIOT SSTA signature propagate through the tropics and influence the atmospheric circulation anomalies over East Asia during winter? To answer this question, the overlying OLR and atmospheric circulation anomalies associated with SHIOT are examined. According to Fig. 5, negative OLR anomalies are observed over the northeastern region of Madagascar Island (Fig. 5a), accompanied by negative anomalies of 200 hPa velocity potential along with 850 hPa convergent wind (Fig. 5b). Meanwhile, significant high-level positive velocity potential anomalies along with low-level divergent wind anomalies are observed over MC (Fig. 5b). As a result, local-scale zonal circulation anomalies are triggered, characterized by ascending motion anomalies prevailing over the Eastern of Madagascar and descending motion anomalies over MC.

Fig. 5: OLR anomalies and the dynamic structures of the circulation pattern associated with SHIOT during DJF.
figure 5

Regression of the a OLR (shadings; W/m2), b 200-hPa velocity potential (shadings; 105 m2/s) and 850-hPa divergent winds (green vectors; m/s) during DJF against SHIOT. OLR over MC (MCOLR) is defined by the averaged OLR in the red box (100°–160°E, 3°–17°S). The dotted areas and green vectors exceed the 90% confidence level.

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Subsequently, descending motion anomalies over MC lead to regional significant positive OLR anomalies, as observed in Fig. 5a.

To further illuminate the atmospheric circulation anomalies induced by SHIOT SSTA, two numerical experiments are executed with the Community Atmospheric Model (CAM5). One is the control run driven by the historical SST, denoted as ‘SST_Clim’. The other one is the sensitive run forced by the SHIOT SSTA forcing, referred to as ‘SST_SHIOT’. To mimic the influence of the SHIOT SSTA, the SSTA regressed against the ATCOI over the Indian Ocean in boreal winter (three boxes in Fig. 3d) are imposed on the ‘SST_Clim’ under the ‘SST_SHIOT’. Both simulations span a 30-year period, and the effects of SHIOT SSTA on OLR over the MC are assessed by comparing the differences between the last 10-year averages of the two experiments (SST_SHIOT - SST_Clim).

Figure 6 presents the distribution of OLR and atmospheric circulation anomalies under SHIOT SSTA forcing. According to Fig. 6a, negative OLR anomalies over the northeastern region of Madagascar Island and positive OLR anomalies over the MC are induced by SHIOT SSTA during DJF, which aligns well with the observations. Figure 6b confirms that SHIOT SSTA triggers significant negative anomalies of 200-hPa velocity potential in the western tropical Indian Ocean, accompanied by anomalous 850-hPa wind convergence. Over the MC, the situation is reversed, characterized by high-level convergence anomalies. Compared to observations, the numerical experiments exhibit more significant negative anomalies of 200-hPa vertical velocity in the western tropical Indian Ocean. Consequently, a weakened local-scale zonal circulation with ascending motion anomalies dominates the western tropical Indian Ocean (40–80°E), while descending motion anomalies prevail over the MC (80–140°E) (Fig. 6c). Overall, the numerical experiments provide further evidence that SHIOT influences the variability of the tropical dipole OLR by altering the tropical zonal-vertical circulation.

Fig. 6: SHIOT SSTA-induced OLR anomalies and the dynamic structures of the circulation pattern during DJF.
figure 6

Differences of a OLR (shadings; W/m2), b 200-hPa velocity potential (shadings; 105 m2/s) and 850-hPa divergent winds (green vectors; in units of m/s), c vertical velocity (shadings; 10−3 Pa/s) and meridional circulation (vectors; m/s) averaged over tropics (15°S–15°N) between two experiments (SST_SHIOT - SST_Clim). The dotted areas and green vectors exceed the 90% confidence level.

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When conducting a regression analysis of ATCOI against OLR anomalies, significant positive anomalies are also observed over the Maritime Continent (MC) (Supplementary Fig. 5a). However, if the boreal winter SHIOT signal is removed, the correlation between ATCOI and OLR over the MC becomes insignificant (Supplementary Fig. 5b). This highlights the pivotal role of SHIOT as a connecting mechanism between ATCOI and the boreal winter OLR over MC.

The atmospheric circulation anomalies induced by the OLR anomalies over MC

To quantify the interannual variations of the OLR anomalies over MC, an index is defined as the detrended OLR anomalies averaged within the red box (100°–160°E, 3°–17°S) in Fig. 5a, referred to as ‘MCOLR’. We select this red box because both ATCOI and SHIOT are significantly correlated with the OLR in this area (rATCOI, MCOLR = 0.26, confidence level >90%; rSHIOT, MCOLR = 0.44, confidence level >99%). To determine whether these OLR anomalies play a crucial role in influencing East Asian precipitation, partial-correlation analysis is conducted (Fig. 7b). After removing the signal of MCOLR, the correlation between ATCOI during SO and East Asian winter precipitation becomes insignificant, particularly in the regions south of the Yangtze River, the Korean Peninsula, and southern Japan (Fig. 7b). On the other hand, it is known that the slowly changing low boundary forcing, such as El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), may influence winter precipitation in East Asia as well. To examine whether the association between SO ATCOI and East Asian winter precipitation depends on the impacts of ENSO or IOD, the partial-correlation approach is also used to remove the DJF ENSO and IOD signal, respectively (Fig. 7c, d). According to the results, the correlation between SO ATCOI and East Asian winter precipitation remains significant after removing ENSO or IOD signal. Therefore, the OLR over the southern MC acts as a tropical signal linking the SO ATCOI and East Asian winter precipitation, and the relationship is independent of ENSO or the IOD impact.

Fig. 7: DJF precipitation anomalies associated with ATCOI.
figure 7

a DJF precipitation anomalies (shadings) correlated with ATCOI. b–d As in (a), but for partial correlation with DJF MCOLR, IOD and ENSO signal removed, respectively. The dotted areas exceed the 95% confidence level.

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To further explain how the OLR over the southern MC influences the East Asian precipitation, the relationship between detrended MCOLR and atmospheric circulation anomalies at 850 hPa is presented. Supplementary Fig. 6 indicates that the strengthened convection in the southern MC finally stimulates the anomalous anticyclone pairs in both hemispheres through the Gill response. Consequently, anomalous southwesterly winds are observed in East Asia, transporting a substantial amount of moisture from the tropics to East Asia. The anomalous atmospheric circulation over East Asia is similar with that of the ATCOI-related pattern (red vectors in Supplementary Fig. 2), which is conducive to winter precipitation in the area.

A numerical experiment using the linear baroclinic model (LBM) is designed to further validate the response of OLR over MC on East Asian atmospheric circulation. The thermal forcing aligns with the red box in Fig. 5a, distributed within an elliptical region centered at 130°E, 10°S, with radiuses of 30° and 10° in the latitudinal and longitudinal directions, respectively (Fig. 8a). To mimic the diabatic cooling effect induced by MCOLR, we use an idealized cooling profile with a maximum value of 2.5 K/day at the 0.45 sigma level (around 300 hPa) (Fig. 8b). This experiment is performed with a basic state of the winter climatology. The LBM is integrated for 30 days, and the variables during the last 10 days are averaged to obtain the stabilizing state for further analysis.

Fig. 8: Atmospheric response to a prescribed forcing over MCOLR region.
figure 8

a The spatial pattern of the cooling forcing (shadings; K/day) at the sigma level of 0.45 and b the vertical profile of the cooling forcing (black curve; K/day) around the horizontal maximum heating centre (10°S, 130°E). c Simulated response of geopotential height (shadings; gpm) and wind (vectors; m/s) at 850 hPa to the cooling forcing added to the climatological winter atmospheric circulation.

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Figure 8c shows the simulated response of the atmospheric circulation anomalies at 850 hPa to the cooling forcing over the southern MC. Positive geopotential height anomalies are induced over both the southern MC and Southeast Asia, accompanied by an anticyclone system over South China Sea. In the region south of the Yangtze-Huaihe River, strong southwesterly winds prevail, while the area north of the Yangtze-Huaihe River experiences much weaker southeasterly winds compared to the southwesterly winds in the southern region. As a result, a wind shear line forms in the Yangtze-Huaihe region. The wind field over East Asia is consistent with observed results (Supplementary Fig. 6), allowing more water vapor to be transported from the tropics to the East Asia. Consequently, the wind shear line promotes the convergence of water vapor in the Yangtze-Huaihe River Basin, thereby enhancing the generation of precipitation in East Asia.

Response of East Asian winter precipitation anomalies to the SO Antarctic ozone anomalies

To validate the impact of Antarctic ozone anomalies on East Asian winter climate, we employ the Specified-Chemistry version of the Whole Atmosphere Community Climate Model (SC-WACCM) to conduct two experiments with different ozone prescriptions. In the control experiment, denoted as ‘less_ozone’, monthly mean ozone concentrations from the year 2000 are prescribed, and the model is run for a duration of 30 years. In the sensitivity experiment, referred to as ‘more_ozone’, we implement the removal of the Antarctic ozone hole by replacing ozone mixing ratio from September to October at each level over the Antarctic region (180°E–180°W, 60°–90°S) with annual mean ozone values. The sensitivity simulation is also run for a 30-year period. We evaluate the effects of the Antarctic ozone variability on East Asian climate by comparing the differences between the last 15-year averages of the ‘more_ozone’ and ‘less_ozone’ simulations.

Figure 9 illustrates the simulated differences in DJF precipitation, 500 hPa omega, and atmospheric circulation between two experiments (more_ozone - less_ozone), reflecting the anomalies induced by the recovery of the Antarctic ozone hole. An extensive rain band extending from southeastern China to the southern regions of Korea and Japan is observed, with the peak center located in southern China, reaching up to 0.4 mm/day (Fig. 9a). This corresponds to negative anomalies of omega at 500 hPa in the region (Fig. 9b). Furthermore, at 500 and 850 hPa, the presence of an anticyclone over the South China Sea facilitates the transport of moisture from the tropics to East Asia, thereby providing favorable conditions for increased precipitation locally. These findings from SC-WACCM are consistent with the observations shown in Fig. 2a and Supplementary Fig. 2. In conclusion, the increase in Antarctic ozone during SO has been verified to result in enhanced boreal winter precipitation in East Asia.

Fig. 9: Precipitation and atmospheric circulation anomalies forced by the SO Antarctic ozone in DJF.
figure 9

a DJF precipitation difference (shadings; mm/day), b omega difference at 500 hPa (shadings; Pa/s), geopotential height difference (shadings; gpm) and wind difference (vectors; m/s) at c 500 hPa, and d 850 hPa between two experiments (more_ozone - less_ozone). The dotted areas and red arrows exceed the 90% confidence level.

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Discussion

The variability of Antarctic ozone and its resulting climatic impacts have triggered fervent attention. Previous research has predominantly focused on the long-term variations of Antarctic ozone and its influence on SH climate factors, such as surface temperatures and atmospheric circulation patterns. However, the research exploring the impact of Antarctic ozone on the climate of the NH is limited. Our findings enhance understanding of the interaction between climate systems of both hemispheres and fills a gap in existing research.

This study reveals a significant positive correlation between the interannual variations of Antarctic ozone during SO and boreal winter precipitation in East Asia. The schematic diagram presented in Fig. 10 illustrates the underlying physical mechanism of this study. First, the increase in Antarctic TCO during SO triggers a tripole pattern of SSTA in the southern Indian Ocean, facilitated by the association between Antarctic TCO and the negative phase of the SAM. After then, the observed SSTA persist from SON through DJF, weakening the tropical zonal-vertical circulation. This is characterized by ascending motion anomalies over eastern Madagascar and descending motion anomalies over the MC, subsequently leading to positive OLR anomalies over southern MC. Consequently, the atmospheric circulation anomalies in Yangtze-Huaihe River Basin in response to non-adiabatic heating over southern MC are characterized by anomalous low-level southwesterly winds. This phenomenon facilitates the transport of abundant moisture from the tropics to East Asia, contributing to increased precipitation in the region. Numerical experiments have validated the impact of Antarctic ozone on East Asian precipitation and elucidated each step of the physical mechanism, thereby strengthening the robustness of the findings. The relationship between the Antarctic ozone during SO and the East Asian winter precipitation is independent of ENSO or IOD, suggesting that incorporating Antarctic ozone variability could enhance forecasts of East Asian winter precipitation.

Fig. 10: Schematic illustration showing the remote influence of the Antarctic ozone during SO on East Asian precipitation in boreal winter.
figure 10

‘SAM-’ indicates the negative phase of SAM. The color belts in the SH indicate the SSTA related with ATCOI. The blue vertical vectors denote the anomalous zonal circulation. The red ellipse denotes the positive OLR anomalies in DJF. The dark green vector over East Asia indicates the anomalous wind associated with ATCOI. The green shaded areas and the rain symbol indicate an increase in precipitation over East Asia.

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Our study proposes that the SO Antarctic ozone can be imprinted into the meridional Indian Ocean tripole SSTA through SAM. Why does the influence of ozone manifest itself on the Indian Ocean SSTA, subsequently affecting East Asian circulation, rather than through other oceans? One plausible explanation is the relative shallowness of the Indian Ocean basin, which makes it more responsive to atmospheric influences. In addition, previous studies have indicated that due to regional differences in circulation and precipitation impacts, surface climate changes associated with ozone-driven variabilities in the SAM at SH midlatitudes do not exhibit an annular pattern2. Other possible reasons merit further investigation. On the other hand, some studies suggest that SSTA in the Atlantic Ocean could also trigger the atmospheric teleconnection to impact the East Asian climate45,46. It is noticeable that according to Fig. 3, in addition to the Indian Ocean SSTA, there is a positive SSTA in the Atlantic Ocean during SON. However, in comparison to the SHIOT SSTA, the Atlantic Ocean SSTA lack persistence from SON through DJF. Therefore, we primarily focus on the Indian Ocean SSTA in this study.

Previous studies have highlighted an increase in winter precipitation and a rise in the frequency of extreme precipitation events in East Asia47,48, underscoring the importance of accurately predicting East Asian winter precipitation in the future. Our results suggest that the Antarctic ozone during SO may serve as an additional predictor for subsequent winter precipitation over East Asia. However, developing a predictive model based on Antarctic ozone data to enhance the accuracy of forecasting winter precipitation over East Asia remains a huge challenge. In the future, with the gradual recovery of Antarctic ozone, how will East Asian winter precipitation be impacted? These unsolved issues require further investigation.

Methods

Reanalysis datasets

The datasets applied in this work include: (1) monthly TCO, temperature, geopotential height, specific humidity, 10-m wind speed, SLP, omega, horizontal and vertical wind components gridded at 0.25° × 0.25° resolution, available from the European Centre for ECMWF ERA5 reanalysis; (2) ground-based TCO from the Halley Station (75°S, 25°W), which measures ozone variability at a single grid point; (3) monthly SST data on a 2.0° × 2.0° grid obtained from the National Oceanic and Atmospheric Administration (NOAA) Extended Reconstructed SST version 5 (ERSST v5)49; (4) monthly OLR data acquired from the Nation Centers for Environment Prediction-National Center for Atmospheric Research Reanalysis I (NCEP/NCAR) with 2.5° × 2.5° grid; (5) monthly precipitation data acquired from the Global Precipitation Climatology Project (GPCP) with 2.5° × 2.5° grid; (6) monthly SAM index defined by Marshall (2003)50. In this study, autumn and winter all refer to boreal seasons. All datasets employed in this study are from 1979 to 2023.

Methodology

In this study, we utilize statistical methods including linear regression analysis and correlation coefficient analysis. The statistical significance is assessed through a two-tailed Student’s t-test.

The Ekman heat fluxes mentioned in our work are derived from wind stress and SST field data obtained from reanalysis datasets. \({Ekman\; heat\; flux}\,=\,\rho {C}_{\rho }({U}_{{ek}}\nabla {SST})\), where \({U}_{{ek}}\) denotes the Ekman transport and \(\nabla {SST}\) denotes the SST gradient. \({U}_{{ek}}=\) (1/\(\rho f\))(−\({\tau }^{y},{\tau }^{x}\)), in which τx and \({\tau }^{y}\) represent the zonal and meridional wind stress, \(\rho\) and \({C}_{\rho }\) represent the density and specific heat capacity of seawater, and f is the Coriolis parameter. Surface net radiation fluxes are the sum of the net longwave fluxes and the net shortwave fluxes, while surface turbulent heat fluxes are calculated as the sum of latent and sensible heat fluxes.

The CMIP6 MME is utilized to validate the impact of Antarctic ozone on SSTA. At the time of the preparation of this paper, 7 models (IPSL-CM5A2, IPSL-CM6A, GFDL-ESM4, GISS-E2-1-G, GISS-E2-2-G, MPI-ESM-1-2-HAM, MRI-ESM2-0) have provided TCO and SST as diagnostics. The CMIP6 MME is created by averaging across the individual CMIP6 model ensemble means, ensuring each model contributes equally to the CMIP6 MME. This methodology effectively mitigates potential biases inherent in individual models, thus enhancing the reliability and robustness of the ensemble’s findings.

To validate the mechanisms underlying the impact of SHIOT SSTA on OLR anomalies over MC region, numerical experiments are conducted using the CAM5. CAM5 is the atmospheric component of the Community Earth System Model (CESM)51, which is coupled to the Community Land Model (CLM). We employ the CAM5 with a horizontal resolution of 1° × 1° and 17 vertical levels. This model is designed to be run with prescribed SST forcing, allowing us to control the initial SST and investigate the resulting climate effects.

To examine the linear response of the circulation anomalies over East Asia to the positive OLR anomalies over southern MC, we conduct numerical experiments using the LBM model. This model is developed based on the dynamical core of the Atmospheric General Circulation Model (AGCM), which is a collaborative effort between the Center for Climate System Research at the University of Tokyo and the National Institute for Environmental Studies in Japan. Nonlinearity processes are removed in the LBM model to easily interpret the sequence of feedback. We utilize the dry version of the model with a horizontal resolution of T42 and 20 vertical sigma levels. To ensure a stable atmospheric response to the prescribed thermal forcing, we employ the time integration method, which has been widely adopted in previous studies52,53.

To verify the observed impact of the Antarctic ozone hole on East Asian winter precipitation, SC-WACCM is employed in this study. The model is derived from the National Center for Atmospheric Research (NCAR) Community Earth System Model version 1.2 (CESM1.2), which has a horizontal resolution of 1.9° × 2° and 66 vertical levels from the surface to 5.96 × 10−6 hPa. This atmospheric model is coupled to land, ocean, and sea ice components54, providing a comprehensive representation of the Earth’s climate system. SC-WACCM is designed to be run with prescribed ozone concentrations, allowing us to control the initial ozone concentrations and explore the subsequent climate effects. This model has been widely employed in previous studies to examine the effects of ozone depletion in different regions54,55,56. Therefore, SC-WACCM is ideally suited for addressing the purpose of this paper.