Why has climate change, in the form of the Pacific Decadal Oscillation, affected the land surface temperature in East Asian winter? What is the solution? What is the role of the enhanced tropical convection currents in the western Pacific under a negative phase of the PDO, atmospheric circulations in this?

The complex interaction between the Pacific decadal oscillation (PDO) and East Asian winter temperatures remains unclear. This study reveals that since the early 2000s, East Asia has experienced a strengthening of Aleutian low (AL) and Siberian high (SH) during negative PDO phases, leading to an intensified East Asian winter monsoon (EAWM). The increased pressure gradient between the SH and the AL, driven by warming in the western Pacific associated with the negative PDO phase, has significantly contributed to a shift toward cooling in East Asia (105◦–150◦ E, 20◦–50◦ N) since the early 2000s. Observations and model simulations provide evidence that the enhanced tropical convection in the western Pacific under a negative PDO phase has intensified the atmospheric circulations associated with the EAWM since the early 2000s.

Understanding these dynamics is crucial for improving winter temperature forecasts in East Asia. Sudden and unanticipated variabilities in winter temperature are closely related to extreme weather and climate phenomena [1, 2]. Accordingly, predictions and interest in temperature fluctuations are increasing. In particular, increases in the unexpected variability of winter temperatures in East Asia significantly impact social, economic, and human activities [3–5]. Therefore, understanding East Asian temperature variability drives the need for more research. The East Asia nwinter monsoon (EAWM) isacrucial component of the global climate system during boreal winter [6–8]. It is a major conduit for cold air fromhighlatitudesmovingsouthtolowlatitudes,significantly influencing East Asia’s weather and climate [9, 10]. The most prominent feature of the EAWM is characterized by strong near-surface northerly winds and cold temperatures along the coast of East Asia induced by the Siberian high (SH, an extensive semipermanent high pressure centered in northeastern Siberia), Aleutian low (AL, the lowest pressure as a climatic feature centered near the Aleutian Islands),

and East Asian troughs, etc [11–13]. In addition, several studies discuss the role of various ocean variabilities in influencing EAWM [14, 15]. These climate variabilities in East Asia significantly impact neighboring regions due to stronger northeasterly surface windsassociatedwithcoldsurges,aswellasondistant regions through planetary-scale interactions between the midlatitudes and the tropics [16–19].

It is widely recognized that both El Nino–˜ Southern oscillation (ENSO) and Interdecadal Pacific oscillation (IPO) play significant roles in influencing East Asian winter surface temperatures through atmospheric circulation and teleconnection patterns. However, this study focuses on the Pacific decadal oscillation (PDO), as it not only exhibits unique decadal variability but also has a strong association with mid-latitude climate systems, including East Asia. Furthermore, the PDO integrates both tropical signals (e.g. changes in western Pacific convection) and extratropical signals (e.g. variations in the intensity of the SH and AL), making it a critical factor for understanding the long-term variability of East Asian winter climate [20–24].

This research has focused on its impact on temperature variations and wind circulations associated with the EAWM, as well as the mechanisms driving these changes within the EAWM system [21, 22, 25– 28]. The PDO is a dominant pattern of sea surface temperature (SST) anomalies that describe climate variability in the North Pacific atmosphere, generally persisting in one phase for over ten years [21, 22, 29– 32]. The positive PDO phase is typically characterized by warm SST patterns along the tropical Pacific andcoldSSTpatternsinthewestern-to-centralNorth Pacific, and the negative PDO is vice versa [33, 34].

The relationship between the phases of the PDO and the temperature variations over East Asia generally shows an opposite structure [35]. Similarly, it wasalsonotedthattheALsignificantlycorrelateswith the PDO [36, 37], and AL changes may be important external forcing mechanisms of the PDO [37, 38]. For example, the cooling (strong AL) over East Asia correspondstothepositivePDOphases,whilethewarming (weak AL) is associated with the negative PDO phases [11, 36]. The relationship between both structures after the 2000s (2003–2023), however, has shifted compared to the period before the 2000s (1979– 1999), particularly during the negative phase of the PDO (see figure 2). Due to the recent changes in the relationship between the PDO and the EAWM, there is an increasing need for research on their impact on winter (December to February, DJF, hereafter) temperatures in East Asia. Here, our findings offer new insights into the evolving dynamics of East Asian climate variability, filling a critical gap in the understanding of how these large-scale atmospheric and oceanic processes influence regional climate patterns. Therefore, the main purpose of this study is to investigate how the PDO-EAWM relationship has changed in terms of East Asia temperature changes during the negative phase of the PDO since the 2000s. In addition to observational analysis, we examine the change in the role of PDO through an idealized pacemaker model experiment to understand the variability in East Asian temperatures according to changes in the strength of the EAWM during the DJF season.

2. Data and methods

2.1. Reanalysis dataset

We analyzed the monthly surface temperature, sea level pressure, zonal and meridional winds, and geopotential height obtained from the fifthgeneration European Centre for Medium-Range Weather Forecasts reanalysis [39] during the wintertime of the period 1979–2023 at a global 1◦ × 1◦ spatial resolution. We used the observed monthly SST from the NOAA ERSST v5 [40]. We additionally obtained monthly observed precipitation from the Global Precipitation Climatology Project [41] version 2.3. Observed DJF anomalies were obtained by subtracting the climatological mean (1979–2023) from the total mean field. The monthly PDO index was obtained from NOAA/National Centers for EnvironmentalInformation,anditcalculatedtheseasonal average for winter. The East Asia surface temperature index was calculated by averaging the surface temperature anomaly over the East Asia (105◦– 150◦ E, 20◦–50◦ N). Only land areas are used. The SH was computed by averaging the mean sea level pressure (MSLP) anomalies over Siberia (80◦–120◦ E, 40◦–65◦ N). The AL is measured by averaging the MSLP anomalies over the North Pacific (160◦ E– 160◦ W, 40◦–60◦ N). We have used the detrended winter anomaly based on the climatology from 1979 to 2023.

Before conducting a composite analysis, we eliminate the influence of global warming by detrending all least-squares linear trends from each variable. Statistical tests for the correlation coefficients and composite difference in observation and simulation are performed based on a two-tailed Student’s t-test at the 90% (or 95%) confidence level [42].

2.2. Idealized pacemaker simulations

The Community Earth System Model version 2 (CESM2) [43] is used to identify the impact of convection in the western tropical Pacific on the relative strengthening of the AL by the southeastward shift of the positive MSLP anomaly in the North Pacific where the AL is located. CESM2 consists of coupled atmosphere (CAM6) [43], ocean (POP2) [44], and sea ice (CICE5) [45] components. The horizontal resolution of CAM6 is 2.5◦ in longitude and 1.9◦ in latitude. POP2 and CICE5 share the same horizontal resolution, a nominal 1◦, with a uniform resolution of 1.125◦ in the zonal direction. The meridional horizontal resolution varies, with the finest resolution being 0.27◦ at the equator. We perform SST nudging simulations by restoring the model-simulated SSTs to observed SSTs using observed anomalies combined with observed climatology from the NOAA extended reconstructed SST version 5 (ERSST v5) [40], in the tropics (20◦ S– 20◦ N) [46–48]. The model-simulated tropical SSTs are restored with a 5 day relaxation time scale. All the experiments have 15 ensemble members (15 different initial conditions). We conduct two idealized SST nudging simulations (PRE_exp and POST_exp) to investigate the climate responses of tropical convection to SST changes between two distinct periods: P1 (1979–1999) and P2 (2003–2023) during a negative PDO phase. We also carry out a control simulation (Ctrl_exp), in which the model SSTs are restored to the observed monthly climatology in the pacemaker region. The period of climatological SST used for model integration is 1995–2014. The initial conditions and simulation periods are the same as the idealizedsimulations.TheimpactofthenudgingSSTs on global climate can be identified by the differences between the idealized and Ctrl_exp simulations. The PRE_exp (POST_exp) uses the observed tropical SST composite anomaly pattern of figure S5(a) and (b). To isolate the climate impact attributed to convective activity in the western tropical Pacific between the two periods, the simulated results for the P1 are subtracted from those for the P2 (POST_exp minus PRE_exp). Each experiment with 15 ensemble members is integrated, affected by the same SST composite, for 14 months from January to the next year February, and only the last 3 months (DJF) of the integrations were taken for analyses.

3. Results

The composite temperature anomalies associated with the PDO phases are depicted in figures 1(a) and (b). The PDO pattern is reflected in climatevariations across the Pacific basin and North America. The contrasting winter PDO patterns between the two phases exhibit the typical characteristics of the PDO, consistent with previous studies [49, 50]. Other reanalysis datasets, such as the NCEP-DOE Reanalysis 2 and the NOAA-CIRES-DOE 20th Century Reanalysis version 3, also show an almost identical pattern (figure S1).

We explore the relationship between the observed PDO variability and East Asian temperature during the winter of 1979–2023 (figures 1(c) and (d)). The overall mutual variability between the two variables shows an out-of-phase pattern (see also figures 1(c) and (d)). Figures 1(c) and (d) highlight these changes in the relationship between the two variables, emphasizing the contrast. These characteristics are evident before the 2000s, especially between the mid-1980s and the mid-1990s. In contrast, the in-phase fluctuation characteristics become visible after 2010. Due to the changes in characteristics between the two variables, the overall temporal correlation value between them for the entire analyzed period (1979–2023) is −0.07, indicating almost no correlation. Furthermore, the explained variance of the PDO, as a measure of its contribution to East Asian winter temperature changes, shows a noticeable decrease from P1 to P2 (figure S2). These features are further demonstrated through the 19 year running correlation calculations between the PDO and temperature indices, as shown in figure 1(d). Negative correlations are consistently observed before the 2000s. Afterward, the negative correlation weakens and eventually turns positive, implying that the relationship between wintertime PDO and East Asian surface temperature is not stationary but shows rapid changes. Similar results are obtained when using other window widths, such as 21 year and 23 year (figureS3).Interestingly ,although the IPO and ENSO are recognized as key long-term drivers of winter temperature variability in East Asia [51], their interdecadal variations differ from the distinct decadal shift in the relationship between the PDO and East Asian winter temperatures (figure S4). Based on the correlation between these two variables, the entire period is divided into two periods: 21 years before the 2000s (P1, 1979–1999) and 21 years after the 2000s (P2, 2003–2023). Notably, a sensitivity test with adjusted periods validated the robustness of the conclusions, showing no impact on key findings. Each period is further classified according to the PDO phases (seetableS1) .Toinves tigate the surface temperature response associated with PDO phases in East Asia, we perform a composite analysis of the East Asian temperature anomalies separated by PDO phases for each period (figure 2). During the positive PDO phase in the P1, the composite temperature anomalies over East Asia generally exhibit a cold pattern (figure 2(a)). As expected, the negative PDO phase of the P1 is associated with warming over East Asia (figure 2(c)). The negative relationship between PDO and temperature is evident, as shown in the running correlation for the P1 in figure 1(d). In the P2, the cooling effect over East Asia still occurs during the positive phase of the PDO (figure 2(b)). However, unlike in the P1, the negative PDO phase tends to produce cold anomalies over East Asia, including Korea and eastern China, except for northeastern Asia and Japan (figure 2(d)). In other words, the recent change in the correlation betweenthePDO phasesandEastAsiantemperatures in figure 1(d) is primarily due to changes in the negative PDO phase (figures 2(c) and (d)) rather than the positive PDO phase (figures 2(a) and (b)).

3.2. Role of the negative PDO on East Asian surface temperature

In this section, we examine the mechanisms by which the warming effect in the East Asian region (105◦– 150◦ E, 20◦–50◦ N) significantly shifts to a cooling effect from the P1 to the P2 during the negative phase of the PDO (figure S9(e)). In figures 3(a) and (b), the locations of the SH (approximately 50◦ N, 100◦ E) and the AL (approximately 50◦ N, 180◦) can be roughly identified through the climatology of MSLP in winter. In addition, changes in the intensity of the SH and AL in winter can be estimated using the composite pattern of MSLP anomalies in the P1 and P2 during the negative PDO phase. In general, the SH and AL are significantly weakened during the negative PDO phase compared to the normal [11, 34, 36, 37]. During the negative PDO phase in P2, however, the less weakened SH (AL) is seen in figure 3(b) in terms of the negative (positive) MSLP composite anomalies centered on Lake Baikal (south of the Alaska Peninsula), compared to the P1.

In other words, during the P2, the winter East Asian region located between the SH and AL is more affected by the cold northerly wind (see also figure 4(d)) due to the stronger pressure gradient between the two pressure systems (i.e. SH and AL) compared to the P1 (table S2). As time progresses from the P1 to the P2 during the negative PDO phase, the relative strengthening of the AL is expected to be caused by a southeastward shift of the positive MSLP anomaly in the North Pacific region where the climatological AL is located. When examining the SST changes between the two periods (figures S5(a) and (b)), it is evident that warming SSTs are developing in the Indian Ocean and the western tropical Pacific (figures 3(c) and S6(a)). Some studies have suggested that atmospheric heating in the tropical Indian Ocean may influence the East Asian winter climate [52–54]. The western tropical Pacific also coincides well with the region of convection strengthening (figure S6(c)), where precipitation develops (figures 3(d), S5(c) and (d)) due to low-level moisture convergence (figures S6(b) and (d)). Through this process, the local airsea interactions in the western tropical region induce a cyclonic circulation and trigger changes in tropical convection (figure S6(c)), which in turn leads to differences in the subsequent precipitation structures and diabatic heating, acting as tropical forcing. These changes lead to alterations in the teleconnection patterns moving north. This modified atmospheric structure is expected to contribute to the shift of positive anomalous MSLP in the North Pacific region where the climatological AL is located. During the transition to P2, we also observe a relative strengthening of the SH (figure S7(a)), consistent with several previous studies [16, 55, 56], which suggest that strong La Nina-like SSTs and convect-˜ ive activity in the western Pacific are generally associated with the strengthening of the SH during winter (figures 3(c) and (d)).

The cause of the winter East Asian temperature change between two periods in the negative PDO phases can also be attributed to changes in the upper atmospheric structure. Figures 4(a) and (b) show the 200 hPa zonal wind climatology obtained from 1979 to 2023 and composite patterns of zonal wind anomalies during the wintertime negative PDO phases for the P1 and P2, respectively. The atmospheric circulation over extratropical East Asia is dominated by the westerly jet stream, which reaches its maximum strength south of Japan. During the P1, the jet stream weakens from East Asia to the eastern Pacific, accompanied by a significant extension of strengthened westerlies near 60◦ N. This results in a distinct meridional dipole structure of anomalous zonal wind, as shown in figure 4(a). However, during the P2, opposite anomalous wind patterns are generally observed in the western Pacific, including East Asia. Specifically, the westerly jet stream over East Asia near 30◦ N is slightly intensified, while the westerly wind in Northeast Asia around 60◦ N maintains its existing strength without showing significant changes .This relation ship causes changes in them eridional wind shear over time. As a result, the intensification of the meridional shear of the East Asian jet during the P2 (as shown in figure 4(b)) leads to enhanced cyclonic vorticity north of the jet stream (figure S7(b)), which favors a stronger East Asian trough (figures 4(c) and S8) and colder conditions over East Asia, as shown in figure 2(d) [57]. In addition, the changes in the low-level meridional wind over East Asia during the time passing from P1 to P2, as depicted in figure 4(d), intensify the previously established climatological northerly wind. These results also demonstrate the shift in East Asian surface temperature between two periods under a negative PDO phase, as shown in figures 2(c) and (d).

To summarize the overall mechanism, a heat source in the tropical western Pacific, emerging from periodic changes during the negative PDO phase, strengthens meridional atmospheric circulation and leads to the strengthening of the SH and AL. Additionally, changes in atmospheric structures related towinter monsooncirculation,specificallythe East Asian jet, the 500 hPa trough, and the 850 hPa meridional wind, influence temperature changes in East Asia.

Note that mechanisms opposite to those in the negative PDO phase are effectively at work, yielding similar results during the positive PDO phase. The cooling effect over East Asia during the positive PDO phase in P2 is weak but still persists (figures 2(a) and (b)) because the pressure gradient weakened by the relative weakening of the AL is not sufficiently weak to induce warm advection.

3.3. Changes in the observed and simulated AL in winter time during negative PDO phases

The observational results clarify an underlying mechanism responsible for the impact of convective activity in the tropical western Pacific on the relative strengthening of the AL through a southeastward shift of the positive MSLP anomaly in the North Pacific during the period shift to P2 in the negative PDO phase. However, due to the internal variability of the climate, there are limitations in explaining the observed phenomena. Therefore, we intend to use climate models to clarify the remote processes of causality. We conduct two pacemaker simulations (see section 2 for details) using SST nudging in the CESM2 coupled model [43]. The similarity between the simulated (figures 5(a) and (b)) and observed (figures S5(a) and (b)) SST patterns in the tropical Indo-Pacific Ocean region indicates that the pacemaker experiment effectively incorporated the observed SSTs into the simulations.

Figure 5(c) presents the composite differences in observed detrended MSLP anomalies, highlighting changes in AL intensity between the P2 and P1 during negative PDO phases. The shift toward negative MSLP anomalies indicates a relative strengthening of the AL. Figure 5(d) indicates the simulated changes from the difference in the MSLP anomalies between the POST_exp and PRE_exp during the negative PDO phase. As it moves on from P1 to P2, the difference in the MSLP anomaly in the North Pacific region, including the Aleutian Islands, is statistically significant. The distribution of the AL strengthening and East Asian trough-related cyclonic anomalies in observations and model experiments shows a similarity in the lower atmosphere (figures 5(c) and (d)) and the upper atmosphere (figure S9), despite certain model limitations, such as SH and the resulting surface temperature, over the Asian continent (figures 5(d) and S9(f)). Ultimately, similar to the observations, the simulated MSLP anomaly is expected to contribute to the deepening of the AL-pressure system over time. Consequently, these simulated results support the idea that the development of convective activity in the tropical western Pacific under a negative PDO phase may be the primary cause of the winter temperature change in East Asia (from war min gtocooling)sincetheearly2000s.Furthermore,the limitations in the model simulations of the observed strengthening of the SH suggest that factors beyond convective activity in the tropical western Pacific may also play a role.

4. Conclusions and discussions

This study found that East Asia has experienced a strengthening of the SH and AL during negative PDO phases since the early 2000s, leading to intensified atmospheric circulations associated with the EAWM. Additionally, the intensified pressure gradient between the SH and the AL, driven by warm convection over the western Pacific linked to the negative PDO phase, plays a crucial role in East Asia’s winter cooling. Although this study does not explicitly address it, the close relationship between the PDO and ENSO suggests that the development of the negative PDO since the 2000s is strongly associated with an increased frequency of strong La Nina events.˜ In particular, the prevalence of La Nina-type negative˜ PDOs appears to have strengthened convection over the western Pacific, which can be considered one of the main drivers of the cold pattern observed in East Asia (figure S10, tables S3 and S4).

In a further analysis of PDO intensity changes and contributing factors, the non-detrended analysis reveals an increased frequency and stronger intensity of negative PDO during P2 compared to P1, likely influenced by the interdecadal mean-state background. In contrast, the detrended analysis shows reduced frequency and intensity of negative PDO in P2 compared to the non-detrended results, suggesting a potential influence of global warming. To demonstrate that tropical western Pacific convective activity is the fundamental cause of AL intensification during the shift to the 2000s in the negative PDO phase, coupled model simulations focusing solely on tropical SST nudging were used. These simulations provide evidence of the connection between warm SST-induced convection in the tropical western Pacific and AL intensification, despite limitations in simulating the SH. The findings suggest that understanding the interaction among various climate phenomena, beyond just the PDO, is essential for improving winter temperature predictions in East Asia. Given the multiple causes of changes in variability associated with the development and decline of the AL, such as North Pacific climate and SST variability [37, 58, 59], and Bering Sea climate [11], there are limitations of this study, which assumes that tropical convective activity alone is responsible for AL changes in the model simulations. In addition, this study only focused on the 45 year data period from 1979 to 2023, which increases the limitations of data length for robust analysis related to the decadal variability cycle. Despite these limitations, the change in the relationship between the negative PDO phase and East Asian surface temperature around the 2000s is clear and distinct throughout the study period.

[1] Ma S, Zhu C, Liu B, Zhou T, Ding Y and Orsolini Y J 2018 Polarized response of East Asian winter temperature extremes in the era of Arctic warming J. Clim. 31 5543–57

[2] Qiu W and Yan X 2020 The trend of heatwave events in the

Northern Hemisphere Phys. Chem. Earth A/B/C 116 102855

[3] Park T-W, Ho C-H and Yang S 2011 Relationship between the Arctic oscillation and cold surges over East Asia J. Clim.

24 68–83

[4] Yu Y, Ren R and Cai M 2015 Comparison of the mass

circulation and AO indices as indicators of cold air outbreaks in northern winter Geophys. Res. Lett. 42 2442–8

[5] Gong D-Y and Ho C-H 2004 Intra-seasonal variability of wintertime temperature over East Asia Int. J. Climatol. 24 131–44

[6] Wen C, Graf H F and Ronghui H 2000 The interannual variability of East Asian winter monsoon and its relation to the summer monsoon Adv. Atmos. Sci. 17 48–60

[7] Wang L and Lu M-M 2017 The Global Monsoon System:

Research and Forecast (World Scientific) pp 51–61

[8] Chen W, Wang L, Feng J, Wen Z, Ma T, Yang X and Wang C

2019 Recent progress in studies of the variabilities and mechanisms of the East Asian monsoon in a changing climate Adv. Atmos. Sci. 36 887–901

[9] Iwasaki T, Shoji T, Kanno Y, Sawada M, Ujiie M and Takaya K 2014 Isentropic analysis of polar cold airmass streams in the Northern Hemispheric winter J. Atmos. Sci. 71 2230–43

[10] Liu Q, Chen G, Wang L, Kanno Y and Iwasaki T 2021 Southward cold airmass flux associated with the East Asian winter monsoon: diversity and impacts J. Clim. 34 3239–54

[11] Rodionov S N, Bond N A and Overland J 2007 The Aleutian low, storm tracks, and winter climate variability in the Bering Sea Deep-Sea Res. II 54 2560–77

[12] Panagiotopoulos F, Shahgedanova M, Hannachi A and Stephenson D B 2005 Observed trends and teleconnections of the Siberian high: a recently declining center of action J. Clim. 18 1411–22

[13] Wu B and Wang J 2002 Winter Arctic oscillation, Siberian high and East Asian winter monsoon Geophys. Res. Lett.

29 3–1

[14] Sun J, Wu S and Ao J 2016 Role of the North Pacific sea surface temperature in the East Asian winter monsoon

decadal variability Clim. Dyn. 46 3793–805

[15] Chen Z, Wu R and Wang Z 2019 Impacts of summer North Atlantic sea surface temperature anomalies on the East Asian winter monsoon variability J. Clim. 32 6513–32

[16] Zhang Y, Sperber K R and Boyle J S 1997 Climatology and interannual variation of the East Asian winter monsoon: results from the 1979–95 NCEP/NCAR reanalysis Mon. Weather Rev. 125 2605–19

[17] Liren J, Sun S, Arpe K and Bengtsson L 1997 Model study on the interannual variability of Asian winter monsoon and its influence Adv. Atmos. Sci. 14 1–22

[18] Wang B, Wu R and Fu X 2000 Pacific–East Asian teleconnection: how does ENSO affect East Asian climate? J. Clim. 13 1517–36

[19] Lau K-M and Li M-T 1984 The monsoon of East Asia and its global associations—a survey Bull. Am. Meteorol. Soc.

65 114–25

[20] Chen W, Yang S and Huang R-H 2005 Relationship between stationary planetary wave activity and the East Asian winter monsoon J. Geophys. Res. Atmos. 110 D14110

[21] Wang L, Chen W and Huang R 2008 Interdecadal modulation of PDO on the impact of ENSO on the East Asian winter monsoon Geophys. Res. Lett. 35 L20702

[22] Kim J-W, Yeh S-W and Chang E-C 2014 Combined effect of El Nino-Southern Oscillation and Pacific decadal oscillation˜ on the East Asian winter monsoon Clim. Dyn. 42 957–71

[23] Kao P-K, Chih-wen H and Huang-Hsiung H 2016 Decadal variation of the East Asian winter monsoon and Pacific decadal oscillation TAO: Terr. Atmos. Ocean. Sci. 27 6

[24] Han L, Long J, Xu F and Xu J 2022 Decadal shift in sea fog frequency over the northern South China Sea in spring: interdecadal variation and impact of the Pacific decadal

oscillation Atmos. Res. 265 105905

[25] Feng J, Wang L and Chen W 2014 How does the East Asian summer monsoon behave in the decaying phase of El Nino˜ during different PDO phases? J. Clim. 27 2682–98

[26] Ding S, Chen W, Feng J and Graf H-F 2017 Combined impacts of PDO and two types of La Nina on climate˜ anomalies in Europe J. Clim. 30 3253–78

[27] Jia X and Ge J 2017 Modulation of the PDO to the relationship between moderate ENSO events and the winter

climate over North America Int. J. Climatol. 37 4275–87

[28] Chen W, Zhang R, Wu R, Wen Z, Zhou L, Wang L, Hu P, Ma T, Piao J and Song L 2023 Recent advances in understanding multi-scale climate variability of the Asian monsoon Adv. Atmos. Sci. 40 1429–56

[29] Budikova D 2005 Impact of the Pacific decadal oscillation on relationships between temperature and the Arctic oscillation in the USA in winter Clim. Res. 29 199–208

[30] Zhou W, Wang X, Zhou T, Li C and Chan J 2007 Interdecadal variability of the relationship between the East Asian winter monsoon and ENSO Meteorol. Atmos. Phys. 98 283–93 [31] Lee S-S, Lee J-Y, Wang B, Ha K-J, Heo K-Y, Jin F-F, Straus D M and Shukla J 2012 Interdecadal changes in the storm track activity over the North Pacific and North Atlantic Clim. Dyn. 39 313–27

[32] Ding Y, Liu Y, Liang S, Ma X, Zhang Y, Si D, Liang P, Song Y and Zhang J 2014 Interdecadal variability of the East Asian winter monsoon and its possible links to global climate change J. Meteorol. Res. 28 693–713

[33] Fang J and Yang X-Q 2016 Structure and dynamics of decadal anomalies in the wintertime midlatitude North Pacific ocean–atmosphere system Clim. Dyn. 47 1989–2007

[34] Chen W, Feng J and Wu R 2013 Roles of ENSO and PDO in the link of the East Asian winter monsoon to the following summer monsoon J. Clim. 26 622–35

[35] Guo R, Huang J, Yu H, Zhao H and Hu Z 2024 Decadal

modulation of temperature pattern over East Asia by Pacific Decadal Oscillation Atmos. Res. 300 107248

[36] Mantua N J, Hare S R, Zhang Y, Wallace J M and Francis R C 1997 A Pacific interdecadal climate oscillation with impacts on salmon production Bull. Am. Meteorol. Soc.

78 1069–80

[37] Wang P, Wang J X, Zhi H, Wang Y and Sun X 2012

Circulation indices of the Aleutian low pressure system: definitions and relationships to climate anomalies in the Northern Hemisphere Adv. Atmos. Sci. 29 1111–8

[38] Schneider N and Cornuelle B D 2005 The forcing of the

Pacific decadal oscillation J. Clim. 18 4355–73 [39] Hersbach H et al 2020 The ERA5 global reanalysis Q. J. R. Meteorol. Soc. 146 1999–2049

[40] Huang B, Thorne P W, Banzon V F, Boyer T, Chepurin G,

Lawrimore J H, Menne M J, Smith T M, Vose R S and

Zhang H-M 2017 NOAA extended reconstructed sea surface temperature (ERSST) version 5 (NOAA National Centers for Environmental Information) vol 30 pp 25

[41] Adler R F et al 2018 The Global Precipitation Climatology Project (GPCP) monthly analysis (new version 2.3) and a review of 2017 global precipitation Atmosphere 9 138

[42] Brownlee K A 1965 Statistical Theory and Methodology in Science and Engineering 2nd edn (Wiley)

[43] Danabasoglu G et al 2020 The community earth system model version 2 (CESM2) J. Adv. Model. Earth Syst.

12 e2019MS001916

[44] Smith R, Jones P, Briegleb B, Bryan F, Danabasoglu G,

Dennis J, Dukowicz J, Eden C, Fox-Kemper B and Gent P 2010 The parallel ocean program (POP) reference manual ocean component of the community climate system model

(CCSM) and community earth system model (CESM) LAUR-01853 vol 141 pp 1–140

[45] Hunke E, Lipscomb W, Turner A, Jeffery N and Elliott S 2015 CICE: the Los Alamos Sea Ice Model documentation and software user’s manual version 5.1. Doc. LA-CC-06-012

[46] Jeong H, Park H-S, Stuecker M F and Yeh S-W 2022 Distinct impacts of major El Nino events on Arctic temperatures due˜ to differences in eastern tropical Pacific sea surface

temperatures Sci. Adv. 8 eabl8278

[47] Jeong H, Park H-S, Stuecker M F and Yeh S-W 2022 Record low Arctic sea ice extent in 2012 linked to two-year La

Nina-driven sea surface temperature pattern˜ Geophys. Res.

Lett. 49 e2022GL098385

[48] Jeong H, Park H-S, Chowdary J S and Xie S-P 2023 Triple-dip La Nina contributes to Pakistan flooding and˜ southern China drought in summer 2022 Bull. Am. Meteorol. Soc. 104 E1570–E86

[49] Newman M et al 2016 The Pacific decadal oscillation, revisited J. Clim. 29 4399–427

[50] Chen Z, Gan B, Huang F, Li J, Wu L, Fan L and Diao Y 2023 The influence of Pacific-North American teleconnection on

the North Pacific SST anomalies in wintertime under the global warming Clim. Dyn. 60 1481–94

[51] Dong B and Dai A 2015 The influence of the interdecadal Pacific oscillation on temperature and precipitation over the

globe Clim. Dyn. 45 2667–81

[52] Ma T et al 2022 Different ENSO teleconnections over East Asia in early and late winter: role of precipitation anomalies in the tropical Indian Ocean and far western Pacific J. Clim.

35 7919–35

[53] Watanabe M and Jin F-F 2002 Role of Indian Ocean warming in the development of Philippine Sea anticyclone during ENSO Geophys. Res. Lett. 29 116–1–4

[54] Yuan Y, Yang S and Zhang Z 2012 Different evolutions of the

Philippine Sea anticyclone between the eastern and central Pacific El Nino: possible effects of Indian Ocean SST˜ J. Clim. 25 7867–83

[55] Fu J, Liu M, Wang R, Wang Y and Zhao S 2022 Possible impact of boreal winter Siberian high on ENSO development

in the following year Front. Earth Sci. 10 885846

[56] Ma T, Chen W, Nath D, Graf H-F, Wang L and Huangfu J 2018 East Asian winter monsoon impacts the ENSO-related teleconnections and North American seasonal air temperature prediction Sci. Rep. 8 6547

[57] Miao J and Wang T 2020 Decadal variations of the East Asian winter monsoon in recent decades Atmos. Sci. Lett. 21 e960

[58] Giamalaki K, Beaulieu C, Henson S, Martin A, Kassem H and Faranda D 2021 Future intensification of extreme Aleutian low events and their climate impacts Sci. Rep. 11 18395

[59] Lapointe F, Francus P, Lamoureux S F, Vuille M, Jenny J-P, Bradley R S and Massa C 2017 Influence of North Pacific decadal variability on the western Canadian Arctic over the past 700 years Clim. Past 13 411–20

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