Intensification of Interannual Cross-Basin SST Interaction between the North Atlantic Tripole and Pacific Meridional Mode since the 1990s

Pei-ken Kao aSchool of Tourism and Historical Culture, Zhaoqing University, Zhaoqing, China
bSchool of Geography and Tourism, Huanggang Normal University, Huanggang, China
cDepartment of Earth and Life Science, University of Taipei, Taipei, Taiwan

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Chi-Cherng Hong cDepartment of Earth and Life Science, University of Taipei, Taipei, Taiwan

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An-Yi Huang cDepartment of Earth and Life Science, University of Taipei, Taipei, Taiwan

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Chih-Chun Chang cDepartment of Earth and Life Science, University of Taipei, Taipei, Taiwan

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Abstract

The cross-basin interaction of the second EOFs of the interannual SST in the North Atlantic and North Pacific—the North Atlantic tripole (NAT) SST and Pacific meridional mode (PMM)—is discussed. Observations revealed that the total variances of the NAT and PMM have simultaneously experienced interdecadal enhancement since the 1990s. Wavelet analysis indicated that this enhancement was associated with the interdecadal variations (8–16 years) of the NAT and PMM, which have become significantly and positively coherent since the 1990s. This interdecadal variation also changed the interannual NAT–PMM relationship from negative to positive. The regression analysis indicated that the NAT forced a Matsuno–Gill circulation anomaly, which had a substantial lag impact on the PMM SST through wind–evaporation–SST feedback. Additionally, the NAT induced oceanic temperature advection, which also partially contributed to the PMM SST. On the other hand, the PMM-associated middle–upper atmospheric teleconnection, a North Atlantic Oscillation (NAO)-like circulation anomaly in the North Atlantic, gave positive feedback to the NAT. The numerical experiments suggest that the enhancement of the NAT–PMM interaction since the 1990s was associated with the eastward shift of PMM-associated convection, which was further enhanced by eastward extension of the upper-level extratropical jet in the North Pacific.

Significance Statement

This study aimed at a better understanding of the cross-basin interaction between the North Atlantic and North Pacific. Our study indicates that the cross-basin interaction in the interannual sea surface temperature between the Pacific meridional mode (PMM) and North Atlantic tripole (NAT) became stronger since the 1990s. The observation yields that this enhancement was associated with the interdecadal variations of the NAT and PMM, which have become significantly and positively coherent since the 1990s. The observation yields that the NAT-forced atmospheric large-scale circulation anomaly had a substantial lag impact on the PMM. On the other hand, the PMM-induced middle–upper atmospheric teleconnection, a North Atlantic Oscillation (NAO)-like circulation anomaly, gave positive feedback to the NAT. The numerical experiments suggest that the enhancement of the NAT–PMM interaction since the 1990s primarily resulted from the eastward shift of PMM-associated convection.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Chi-Cherng Hong, cchong@utaipei.edu.tw

Abstract

The cross-basin interaction of the second EOFs of the interannual SST in the North Atlantic and North Pacific—the North Atlantic tripole (NAT) SST and Pacific meridional mode (PMM)—is discussed. Observations revealed that the total variances of the NAT and PMM have simultaneously experienced interdecadal enhancement since the 1990s. Wavelet analysis indicated that this enhancement was associated with the interdecadal variations (8–16 years) of the NAT and PMM, which have become significantly and positively coherent since the 1990s. This interdecadal variation also changed the interannual NAT–PMM relationship from negative to positive. The regression analysis indicated that the NAT forced a Matsuno–Gill circulation anomaly, which had a substantial lag impact on the PMM SST through wind–evaporation–SST feedback. Additionally, the NAT induced oceanic temperature advection, which also partially contributed to the PMM SST. On the other hand, the PMM-associated middle–upper atmospheric teleconnection, a North Atlantic Oscillation (NAO)-like circulation anomaly in the North Atlantic, gave positive feedback to the NAT. The numerical experiments suggest that the enhancement of the NAT–PMM interaction since the 1990s was associated with the eastward shift of PMM-associated convection, which was further enhanced by eastward extension of the upper-level extratropical jet in the North Pacific.

Significance Statement

This study aimed at a better understanding of the cross-basin interaction between the North Atlantic and North Pacific. Our study indicates that the cross-basin interaction in the interannual sea surface temperature between the Pacific meridional mode (PMM) and North Atlantic tripole (NAT) became stronger since the 1990s. The observation yields that this enhancement was associated with the interdecadal variations of the NAT and PMM, which have become significantly and positively coherent since the 1990s. The observation yields that the NAT-forced atmospheric large-scale circulation anomaly had a substantial lag impact on the PMM. On the other hand, the PMM-induced middle–upper atmospheric teleconnection, a North Atlantic Oscillation (NAO)-like circulation anomaly, gave positive feedback to the NAT. The numerical experiments suggest that the enhancement of the NAT–PMM interaction since the 1990s primarily resulted from the eastward shift of PMM-associated convection.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Chi-Cherng Hong, cchong@utaipei.edu.tw

1. Introduction

The Pacific meridional mode (PMM) is the second leading mode of coupled ocean–atmosphere variability in the tropical Pacific (Chiang and Vimont 2004). In contrast to the leading mode [i.e., El Niño–Southern Oscillation (ENSO)], which exhibits an east–west distributed pattern, the PMM is characterized by a south–north distributed sea surface temperature anomaly (SSTA) accompanied by cross-equatorial flow in the tropical eastern Pacific. Its development and maintenance are associated with the annual cycle and wind–evaporation–SST (WES) feedback (Xie and Philander 1994). The PMM exerts strong effects on the tropical climate. For example, the PMM forced lower-level cyclone anomalies, a Matsuno–Gill response (Matsuno 1966; Gill 1980) to the PMM-associated SSTA, substantially modifying the East Asian summer monsoon and tropical cyclone (TC) activity in the western North Pacific (WNP) (Zhang et al. 2016; Wu et al. 2018). Moreover, PMM-associated large-scale atmospheric and oceanic conditions provide favorable conditions for the development of the central Pacific El Niño (Yu and Kim 2011; Kim et al. 2012).

In the North Atlantic, the leading empirical orthogonal function (EOF) of the SST has a basinlike structure that resembles an Atlantic multidecadal oscillation (AMO) pattern. By contrast, the second EOF has a south–north distributed structure, generally referred to as the North Atlantic tripole (NAT; Deser and Blackmon 1993; Kushnir 1994). The NAT may couple with the atmospheric variability of the North Atlantic Oscillation (NAO; Deser and Timlin 1997; Fan and Schneider 2012; Schneider and Fan 2012) through surface heat flux (e.g., Bjerknes 1964; Marshall et al. 2001; Visbeck et al. 2003). It fluctuates over multiple time scales, with significant interannual and interdecadal components (e.g., Deser and Blackmon 1993; Molinari et al. 1997; Grötzner et al. 1998; Wu and Liu 2005; Fan and Schneider 2012). Additionally, the NAT exerts a substantial remote effect on the WNP subtropical high, which has been increasing gradually since 1980 (Hong et al. 2014). Studies have also revealed that the NAT-associated SST in the tropical North Atlantic has a significant interaction with the tropical Pacific SST (e.g., Saravanan and Chang 2000), especially triggering and terminating the ENSO (e.g., Enfield and Mayer 1997; Ding et al. 2012; Frauen and Dommenget 2012; Ham et al. 2013).

Recently, the possible effect of the North Atlantic SST on the Pacific Ocean has been gaining considerable attention. For example, Wang et al. (2017) reported that the Atlantic has been a key pacemaker of biennial variability in the Pacific in recent decades. The NAT-triggered stationary Rossby wave has a significant downstream effect on the East Asian summer monsoon and mei-yu rainfall (Gu et al. 2009; Wu et al. 2009; Chen et al. 2016). It also reported that the NAT forced a middle–upper atmospheric wavelike perturbation in the extratropical Eurasian continent, which may have contributed to the extreme heat wave in Northeast Asia in the summer of 2018 (Hong et al. 2021). Moreover, the effect of leading SST EOF in the North Atlantic (i.e., AMO) on the Pacific subtropical high and PMM has been enhanced since 1990 due to state change in the sea level pressure in the subtropical eastern Pacific (Yu et al. 2015).

Several studies have explored the cross-basin interaction between the Atlantic and Pacific, with most focusing on the effect of the first leading mode and one-way interaction from the Atlantic to the Pacific or Pacific to Atlantic. The interaction between the second EOFs, the NAT and PMM, and the NAT–PMM feedback remains insufficiently investigated. Our observations revealed that the PMM and NAT variance have simultaneously experienced an interdecadal enhancement since the 1990s (Fig. 1), indicating a strengthening of the PMM–NAT interaction. In this study, the cross-basin interaction and feedback between the PMM and NAT were investigated. We hypothesized that the NAT forces the Matsuno–Gill-type response, which may enhance the PMM, leading to positive feedback to the NAT. We also conducted observational analysis and numerical experiments to examine the possible causes of the enhancement of NAT–PMM interaction since the 1990s.

Fig. 1.
Fig. 1.

(a) The SSTs (shading) and 850-hPa winds anomalies (climatology: 1979–2008) in JJA 2018. The blue box and red box denote the PMM and North Atlantic tripole (NAT) regions, respectively. Shading with dots indicates the percentile of SST in JJA 2018 larger than 90% or smaller than 10%. The percentile was ranked during 1948–2018. (b) The second EOF of SST in the eastern Pacific (PMM). The EOF was obtained from monthly ERSSTv5 with removing the annual cycle and long-term trend. (c) As in (b), but for the North Atlantic.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

The rest of this study is organized as follows. The data and methodology are explained in section 2. Section 3 presents data on the intensification of the NAT and PMM since the 1990s. The modulation of interdecadal variation in the interannual relationship between the PMM and NAT is discussed in section 4. Sections 5 and 6 report the effect of the NAT on the PMM and that of the PMM on the NAT, respectively. A summary and discussion are presented in the final section.

2. Data collection and methods

Several independent datasets were used in this study. The monthly atmospheric fields from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCAR–NCEP) reanalysis (Kalnay et al. 1996) were also used in the present analyses. SST data were collected from the National Oceanic and Atmospheric Administration Extended Reconstructed Sea Surface Temperature version 5 (ERSSTv5; Huang et al. 2017). Monthly surface flux data were obtained from the European Centre for Medium-Range Weather (ECMWF) interim reanalysis (ERA-Interim; Berrisford et al. 2011). Monthly ocean data from the NCEP Global Ocean Data Assimilation System (GODAS; Behringer 2007) was used in the mixing layer heat budget. (Li et al. 2002; Hong et al. 2008) are applied in this study. Precipitation monthly data were collected from NOAA’s precipitation reconstruction (Chen et al. 2002)

The anomaly was defined as the total field subtracted from the monthly climatological mean during the period of 1979–2008. Then, a detrending was applied to the anomaly by removing the linear trend during 1948–2019. Another detrending method was tested by subtracting the anomaly from the regression of anomaly to the hemisphere averaged SSTA between 60°S and 60°N (Ting et al. 2009). It reveals that the detrending is not sensitive to the method.

The EOF was applied to the detrending tropical Pacific SSTA and North Atlantic SSTA, respectively, to obtain the PMM and NAT patterns. The first EOF in the Pacific and Atlantic presents the ENSO and AMO, which contribute 43% and 21% to the total variance, respectively. The second EOF yields the PMM and NAT structure, which accounts for 10% and 11% of the total variance individually. Different domains and time periods were used in calculating the EOF. It is shown that the EOF patterns were not sensitive to the domain and time. On the other hand, the lead–lag correlation yields that the NAT (EOF2) is negatively correlated with AMO (EOF1) with leads of ∼8–10 months (not shown), whereas the PMM (EOF2) leads the ENSO (EOF1) by ∼12–15 months since 1990 (not shown).

The NAT was defined as the second EOF of the detrended North Atlantic SST anomaly. To make the manuscript consistent and avoid reader confusion, the second EOF of tropical Pacific SST corresponding to principal component (PC2) was defined as the PMM index. We compared the EOF-based PMM index with the PMM index derived from the maximum covariance analysis (MCA) to SST and the zonal and meridional components of the 10-m wind field (Chiang and Vimont 2004; https://psl.noaa.gov/data/timeseries/monthly/PMM/). The correlation coefficient between the EOF-based PMM index and MCA-based PMM index reaches 0.91, and both indices with associated regression exhibit similar results. A series of numerical experiments by forcing the Simplified Parameterizations, Primitive-Equation Dynamics (SPEEDY) model (Molteni 2003; Kucharski et al. 2006) with observed PMM SST were conducted. The SPEEDY model contains eight vertical levels with a horizontal resolution of T30 (49 × 96 grid). This model is an efficient intermediate-complexity AGCM, which has been and successfully used in the studies of large dynamics (Bracco et al. 2005; Kucharski et al. 2006; Wu et al. 2020).

3. Intensification of the NAT and PMM since the 1990s

Figure 1a presents the SST and 850-hPa wind anomalies in June–August 2018. A PMM pattern in the North Pacific synchronized with the NAT in the North Atlantic was clearly identified. The PMM–NAT-associated positive SSTA formed a southwest–northeastern tilt pattern from the Pacific to the Atlantic. Notably, the year 2018 shown in Fig. 1a is not a special case. This phenomenon has occurred frequently in recent years; other similar cases, such as in 2014, 2015, and 2019 (not shown) were found. This cross-basin SST pattern has occurred frequently in recent years and substantially influenced the tropical climate (e.g., Hong et al. 2016; Wu et al. 2018; Tseng et al. 2020). The PMM and NAT are the second EOF of the interannual SST in the Pacific and North Atlantic basins, respectively (Figs. 1b,c). Figure 1a indicates that the second SST EOF in the Pacific was enhanced simultaneously to that in the North Atlantic in 2018. The PMM and NAT time series data further revealed that the PMM and NAT have experienced interdecadal enhancement approximately since the early 1990s (Figs. 2a,b). This enhancement has been accompanied by an interdecadal change in the interannual relationship between the NAT and PMM: the 241-month sliding correlation coefficient between the NAT and PMM has turned from negative to positive since the 1990s, with NAT leading PMM by approximately 2–3 months (Fig. 2c). We recalculated Fig. 2c by applying a high-pass filter (≤8 years) to the raw data to remove the influence of interdecadal variation. The enhancement of PMM–NAT relationship since 1990s (Fig. 2c) was still significantly identified except that the time span of significant lead–lag relationship became shorter. That is, the effect of interdecadal variation primarily broadens the lead–lag time of the interannual relationship between PMM and NAT. Notably, the intensification of the PMM and NAT was also clearly reflected in the total variance; the sliding variances of the PMM and NAT were amplified approximately simultaneously after the early 1990s (Fig. 3). Figure 3 also shows that the maximum variance of both indices occurs in boreal spring (March–May) and the major variance extends from boreal winter to boreal summer since the year 2000. That suggests that not only is the magnitude of second EOF in North Pacific and North Atlantic enhanced but also the duration is prolonged since 2000.

Fig. 2.
Fig. 2.

(a) The time series of second principal component for the SST-EOF2 in the North Atlantic (Fig. 1c) and (b) the SST-EOF2 in the eastern tropical Pacific (Fig. 1b). (c) The lead–lag 241-month sliding correlation between NAT and PMM indices. Positive (negative) lag months indicate that the NAT index leads (lags) the PMM index.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

Fig. 3.
Fig. 3.

The 11-yr running total variance of the monthly (a) NAT index and (b) PMM index.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

To determine what has caused amplification in the PMM and NAT since the early 1990s, we analyzed the spectrum of the NAT and PMM by considering the time-varying frequency with wavelet analysis. The wavelet analysis revealed that the NAT was dominated by interannual (∼0.5–1 yr) and interdecadal (8–10 yr) variations in which the interdecadal fluctuation enhanced and became significant after the mid-1980s (Fig. 4a) concurrent with the phase change of the PMM–NAT relationship (Fig. 2c). The wavelet of the PMM also featured interannual (∼0.5–2 yr) and interdecadal (∼12–14 yr) fluctuations. In contrast to the NAT, the interdecadal variation was stronger after the early 2000s, approximately 10 years later than for the NAT (cf. Figs. 4b and 4a). Notably, the interannual variation in the PMM has increased since the early 1980s, and the dominant period has gradually shortened from approximately 2 years to 1 year since 2000. A regression of the SST and 850-hPa wind on the interannual-varying (∼0.5–2 yr) PMM signal suggested that this shortening was associated with enhancement of tropical–extratropical interaction of the SST in the North Pacific since the early 1990s (not shown; Di Lorenzo et al. 2008). The cross wavelet between the NAT and PMM indicated that the indices were out of phase in the interdecadal fluctuation (arrows directed to the left in the window of 8–16 years) before 1980 but terminated to almost in phase after 1980 (arrows directed to the right; Fig. 4c). The phase change in the interdecadal variation was clearly identified in the bandpass–filtered (8–16 yr) NAT and PMM: the indices were transformed from out of phase to nearly in phase after the early 1990s, with the NAT leading the PMM by approximately 2–3 years (Fig. 4d). Figure 4 suggests that the transformation of the interannual NAT–PMM relationship from out of phase to in phase since 1990 (Fig. 2c) was associated with the phase change of the interdecadal variation of the NAT and PMM.

Fig. 4.
Fig. 4.

Wavelet spectrum of the (a) NAT index and (b) PMM index. (c) Coherent spectrum of the cross wavelet between the NAT and PMM index. The vectors display the lead–lag relationship between two indices. The thick black curve denotes the cone of influence of the wavelet power spectrum. The vectors display the relation between two indices: right (left) means that they are in phase (out of phase); up (down) means PMM lead (lag) 1/4 period. The thick black lines indicate the spectrum exceeding the 95% confidence level. (d) Time series of 8–16-yr normalizing bandpass filtered NAT index (blue line) and PMM index (red line). Light (dark) gray shading denotes that the 8–16-yr filtered NAT and PMM were out of (in) phase in P1, i.e., 1970–89 (P2, i.e., 1990–2014).

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

4. Modulation of interdecadal variation on the interannual NAT–PMM relationship

On the basis of the termination of the interannual relationship between the NAT and PMM in the early 1990s (Fig. 2c), the entire period was separated into two subperiods: 1970–89 (P1) and 1990–2014 (P2). Figure 5 compares the lead–lag regression of the SST and 850-hPa wind onto the NAT between P1 and P2 for the unfiltered data. During P1, the NAT was accompanied by a La Niña–like condition—that is, a negative SSTA and an easterly wind anomaly in the equatorial eastern Pacific, in lag −3 months (Fig. 5a). The negative SSTA and easterly anomaly decayed and developed to El Niño–like SST and wind (westerly) anomalies from lag 0 to lag 3 months (Figs. 5b,c). During P2, the NAT was also accompanied by a La Niña–like condition in the equatorial eastern Pacific in lag −3 months (Fig. 5d). However, the easterly wind anomaly continued to grow and developed into a PMM pattern—a meridional dipole SSTA accompanied by cross-equatorial flow in the tropical eastern Pacific—from lag 0 to lag 3 months (Figs. 5e,f). Finally, the PMM develops to a central Pacific (CP) El Niño approximately in lag 9 months (not shown), a similar result also mentioned by Di Lorenzo et al. 2010 and Yu et al. (2015). By contrast, the SSTA develops to a La Niña condition in the P1 (not shown). The SST and 850-hPa wind anomalies in the North Atlantic also exhibited distinct features between P1 and P2. The NAT decayed rapidly from lag 0 to lag 3 months in P1 (Figs. 5b,c). Conversely, the NAT-associated tripole SSTA was sustained to lag 3 months in P2 (Figs. 5e,f).

Fig. 5.
Fig. 5.

A comparison of lead–lag regression of SSTs (shadings) and 850-hPa winds (vectors) onto the NAT index between (a)–(c) P1 and (d)–(f) P2, for lag −3, 0, +3 months respectively. Vectors and shading with dots denote the signal exceeding the 10% significant level by Student’s t test.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

According to wavelet analysis (Fig. 4), the NAT was further separated into interannual (≤8 yr) and interdecadal (8–16 yr) components. Figure 5 was recalculated with both variations instead of the raw (unfiltered anomaly) data. A comparison of Figs. 5 and 6 reveals that the total regression in the eastern Pacific primarily resulted from the interannual variation during P1, whereas both the interannual and interdecadal variations contributed substantially to the total regression, with the interannual (interdecadal) variation contributing more in the south (north) pole of PMM, in P2. Figure 6 also indicates that the NAT-associated SSTA tripole can be identified only for the interannual variation in P1. By contrast, the tripole pattern was clearly observed for both interannual and interdecadal variations in P2. Figure 6 yields that the interdecadal change of the interannual coefficient of correlation between the NAT and PMM since the 1990s (Fig. 2c) was associated with the interdecadal PMM and NAT fluctuations. Comparing Fig. 6c (interannual regression) with Fig. 6d (interdecadal regression) further revealed that the interannual regression was remarkably enhanced by the interdecadal regression, including the tripole SSTA pattern in the Atlantic and the PMM SSTA and easterly anomaly in the tropical eastern Pacific. The effect of interdecadal variation on the interannual variation was evident in P2 and was not identified in P1 (cf. Figs. 6b and 6d). That is, the interannual NAT–PMM relationship in P2 was substantially modified by the interdecadal variations of the NAT and PMM, which enhanced and became in phase in the 1990s (Fig. 4d). Moreover, the cross-basin interaction between the North Atlantic and North Pacific was enhanced in P2 (Fig. 5).

Fig. 6.
Fig. 6.

As in Fig. 5, but for the comparison between (a),(c) interannual variation (1–8-yr filtering) and (b),(d) interdecadal variation (8–16-yr filtering) at lag 0 month. Vectors and shading with dots denote the signal exceeding the 10% significance level by Student’s t test.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

5. Interannual pathways of NAT impact onto PMM

The tropical circulation in the eastern Pacific exhibited a Matsuno–Gill-type response to the negative SSTA in the tropical North Atlantic in P2 (Fig. 5d). That is, easterly anomalies in the tropical North Atlantic–eastern Pacific accompanied an anomalous anticyclone in the subtropical eastern North Pacific. The southwesterly wind anomaly in the west anticyclone was against the prevailing northeasterly trade wind, which may have weakened the trade wind and led to a positive SSTA through WES feedback (Xie and Philander 1994).

The mixed layer temperature tendency equation may be written as (Li et al. 2002)
Tt=Oceanadv+1ρCPH(Surfflux)+R,
where T denotes the mixed layer temperature, and Oceanadv and Surfflux denote the 3D oceanic temperature advection and into ocean surface flux, respectively; Surfflux = QSW + QLW + QLH + QSH, where QSW, QLW, QLH, and QSH represent the net downward shortwave radiation at the ocean surface, net upward surface longwave radiation, and surface latent and sensible heat fluxes, respectively; ()′ represents the anomaly variables (i.e., total field subtracted from the climatological mean); R′ represents the residual term, ρ (=103 kg m−3) is the density of water, Cp (=4000 J kg K−1) is the specific heat of water, and H is the mixing layer depth. The mixed layer depth in the PMM region varies from 30 to 60 m. We use different mixed layer depths, including 40 and 55 m, in calculating the heat budget. It is found that the heat budget is not sensitive to the mixed layer depth. For convenience, a constant mixed layer depth of 40 m is used in the diagnosis.

The lead–lag regression of the mixed layer temperature tendency onto the NAT revealed that a positive mixed-layer temperature tendency in the subtropical eastern North Pacific (∼20°N, 120°W) was clearly seen at lag −6 months for P2 (Fig. 7a); this tendency extended southwestward to the tropical central Pacific at lag 0–3 months. Finally, a PMM pattern and cross-equatorial flow were well established in the eastern Pacific (Figs. 7b,c). Figure 7 also yields that the surface heat flux contributed substantially to the development of positive temperature tendency in the eastern North Pacific (the north pole of the PMM) was reasonably captured by the surface heat flux and ocean temperature advection (i.e., Surfflux + Oceanadv; Figs. 7d–f). That suggests the warming in the north pole of PMM was associated with the atmospheric forcing and oceanic dynamics.

Fig. 7.
Fig. 7.

(a)–(c) The lead–lag (−6, −3, 0 months) regression of mixed layer temperature tendency [shading; Eq. (1)] and 850-hPa winds (vectors) onto the NAT index during P2 (1990–2014). (d)–(f) As in (a)–(c), but for the summation of surface heat flux and oceanic 3D temperature advection. Vectors and shadings with dots denote the signal exceeding the 10% significant level by Student’s t test.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

The surface heat flux includes four terms. Figure 8 reveals that the latent heat flux was the dominant term contributing to the development of a positive mixed layer temperature tendency in the eastern North Pacific during P2 (Figs. 7a–c). Whereas the longwave radiation (QLW) also creates a PMM temperature tendency, its magnitude was relatively smaller than that of QLH, and its contribution to the temperature tendency was largely offset by the QSW (Figs. 8c and 8d). The regression demonstrates that the NAT-forced Matsuno–Gill-type circulation may create a positive temperature tendency in the subtropical eastern North Pacific through the WES feedback, a physical process also reported in recent studies (Di Lorenzo et al. 2010; Ding et al. 2015; Yu et al. 2015). The same analysis was applied to P1. The PMM mixed layer temperature tendency (Figs. 7a–c) was not observed in P1. Conversely, a westerly-anomaly-associated El Niño–like SST tendency in the equatorial eastern Pacific was identified (not shown). A possible cause of the increasing effect of NAT on the PMM in P2 was the increase in the North Pacific subtropical high beginning in the 1990s (Yu et al. 2015). A larger North Pacific subtropical high causes stronger northeasterly trade winds because the latent heat flux is proportional to wind speed. For the same unit of wind anomaly, larger wind speed and latent heat changes are created when the prevailing northeasterly trade wind is larger.

Fig. 8.
Fig. 8.

The regression of surface heat flux and mixed layer oceanic temperate advection onto the NAT index during P2 for the terms of (a) latent heat flux and 850-hPa winds, (b) sensible heat flux, (c) shortwave radiation, (d) longwave radiation, and (e) mixed layer (∼40 m) 3D oceanic temperate advection. (f) As in (e), but for the mixing layer horizontal currents (vectors) and temperature anomalies (shading; K). Vectors and shading with dots denote the signal exceeding the 10% significant level by Student’s t test.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

Besides the surface heat flux, the NAT-forced low-level easterly and anticyclone anomalies also drive a surface ocean current anomaly in the eastern North Pacific (Fig. 8f). We investigated each term of 3D oceanic temperature advection and found that the term υ(T¯/y) determined the oceanic dynamics. The effect of Bjerknes feedback [Bjerknes 1964; i.e., the zonal temperature advection u(T¯/x) and the thermocline feedback w(T¯/z)] primarily occurs in the tropics and its impact on the subtropics is insignificant. That is, the PMM-associated anomalous meridional current transports the tropical warm water to the subtropics, and consequently contributes to the PMM development. Notably, Figs. 7 and 8 yield that the cooling of SST in the south pole of PMM was not triggered by the surface flux or oceanic temperature advection. The lead–lag correlation between NAT and the Niño-3.4 index reveals that the NAT was followed by a decaying of La Niña (Fig. 9), which remains a substantial negative SSTA in the region of eastern South Pacific (i.e., the south pole of PMM). Finally, the negative SSTA in the south pole of PMM joined with the NAT-forced Matsuno–Gill-type circulation to lead a cross-equator flow and PMM SSTA in the eastern North Pacific.

Fig. 9.
Fig. 9.

The lead–lag 241 months sliding correlation between NAT and the Niño-3.4 index. Positive values mean that Niño-3.4 lags NAT.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

6. Feedback pathways of PMM impact on NAT

During P1, the PMM SST–associated extratropical teleconnection exhibited zonally distributed wave trains, with an anticyclone anomaly in the North Pacific that extended eastward to southern Greenland (Fig. 10a). Moreover, a cyclone anomaly occurred in the subtropical North Atlantic, weakening the climatological mean of the subtropical North Atlantic high and generating a negative SSTA by decreasing the climatological subsidence. This anomaly-associated westerly wind in the south weakened the prevailing northeasterly trade wind, enhancing the positive SSTA in the tropical North Atlantic. By contrast, the PMM-associated middle–upper atmospheric teleconnection resembled the NPO and NAO in the North Pacific and North Atlantic, respectively, during P2 (Fig. 10b). These two meridional dipoles were similar to the quadrupole pattern mentioned by Liang et al. (2017). Notably, the meridional dipole pattern in the North Atlantic in P2 was nearly opposite to that in P1—that is, a cyclone anomaly in southern Greenland and an anticyclone anomaly in the subtropical North Atlantic. The cyclone and anticyclone anomalies may have decreased and increased, respectively, the underlying SST, creating positive feedback to the NAT. We noted that the NAO can also result in an AMO (Delworth et al. 2016). However, for the interannual time scale, Fig. 10 suggests that the NAO was coupled with the Atlantic tripole SSTA.

Fig. 10.
Fig. 10.

A comparison of the regression of SSTs (shading), precipitation area near the equatorial Pacific (green: positive anomaly area; gray: negative anomaly area), and 500-hPa geopotential height (contours) onto the PMM index between (a) P1 and (b) P2. The elliptical shading (green: positive anomaly; gray negative anomaly) indicates the major locations in the Pacific where precipitation is significant correlated with PMM. Shading with dots denotes the signal exceeding the 10% significant level by Student’s t test.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

The middle–upper extratropical atmospheric teleconnection in response to tropical heating is associated with Rossby waveguides (e.g., Ambrizzi and Hoskins 1997), which is determined using the location and strength of a jet. A comparison of the climatological mean 200-hPa zonal wind between P1 and P2 revealed that the North Pacific jet was enhanced and extended eastward to the North Atlantic in P2 (Fig. 11a). The stationary Rossby wavenumber suggested that the eastward extension of the jet made it favorable for the stationary Rossby wave to propagate eastward to the North Atlantic (Figs. 11b,c). In addition to the mean state change in the upper-level zonal wind, the PMM-associated convection in the equatorial Pacific also exhibited a remarkable eastward shift from the date line to the eastern Pacific (Fig. 10, green elliptical shading). The partial regression with fixing Niño-3.4 index yields that the eastward shift of convection primarily determined by the PMM. The eastward shift of convection modified the atmospheric response in the North Pacific so that it resembled a sandwich-like structure and had a similar pattern to the NPO; in other words, the mean state change and the eastward shift of PMM-associated convection both modified middle–upper-level teleconnection and led to distinctions in P2.

Fig. 11.
Fig. 11.

(a) Contours: the climatology of 200-hPa zonal wind (U200) in MAM in P1. Shading indicates the difference of U200 between P1 and P2 (P2 minus P1). (b),(c) A comparison of the climatology of Rossby wavenumber (10−10 s−2) at 200 hPa in MAM between P1 and P2. The calculation of stationary Rossby wavenumber followed the definition in Ambrizzi and Hoskins (1997).

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

The effect of the PMM SST on the circulation anomaly in the North Atlantic was further investigated using the SPEEDY model. The design of numerical experiments is listed in Table 1. The control experiment (CTL-exp) was performed using the model with the climatological monthly SST during 1979–2008. Two sensitivity experiments were conducted. In the experiments of C1-exp and C2-exp, the model was forced by the same observed monthly SSTA in the PMM region (120°E–95°W, 21°S–32°N) from 1950 to 2020 that was added to distinct climatological SST during P1 and P2, respectively. Each experiment included three members, and the ensemble mean was used for analysis. The anomaly fields were derived from the sensitivity experiment data subtracted from the control experiment data.

Table 1

Design of experiments. The control experiment (CTL-exp) was performed using the model with the climatological monthly SST during 1979–2008. Two sensitivity experiments were conducted. In C1-exp and C2-exp, the model was forced by the same observed monthly SSTA in the PMM region (120°E–95°W, 21°S–32°N) from 1950 to 2020 that was added to distinct climatological SST during P1 and P2, respectively. The anomaly field was defined as the CTL-exp subtracted from the sensitivity experiment.

Table 1

The atmospheric response of the 500-hPa geopotential height anomaly in the North Pacific led to extratropical wave trains originating from the North Pacific in P1 (Fig. 12a). Compared with the observation, the cyclonic circulation anomaly in the North Pacific and southern Greenland was realistically simulated (Figs. 12a and 10a). During P2, the NPO- and NAO-like patterns in the North Pacific and North Atlantic, respectively, were realistically captured (Figs. 12b and 10b). Notably, the atmospheric response in the North Atlantic exhibited several distinctions between P1 and P2. For example, an anticyclone (cyclone) anomaly occurred in southern Greenland (i.e., the north pole of the NAT) in P1 (P2). Moreover, the southwest–northeast-tilted positive geopotential height anomaly in the subtropical North Atlantic was seen only in P2. This positive anomaly, resembling the observation, may enhance the subtropical North Atlantic high, contributing to the underlying positive SSTA by increasing the downward short radiation, and the associated northeast prevailing wind in the south may decrease the SST through WES feedback, further enhancing the negative SSTA in the tropical North Atlantic.

Fig. 12.
Fig. 12.

Sensitivity test of model response (geopotential height at 500 hPa) to PMM-associated SSTA in different climatological (mean) SSTs. Regression onto PMM (a) in period P1 for C1-exp and (b) in period P2 for C2-exp. In C1-exp and C2-exp, the model was forced by the same observed monthly SSTA in the PMM region (120°E–95°W, 21°S–32°N) from 1950 to 2020 that was added to distinct climatological SST during P1 and P2, respectively. Note that (a) and (c) are both obtained from the same sensitivity experiment of C1-exp. The details of the numerical design are documented in section 6. (c) As in (a), but for the regression calculated during P2. Shadings indicate the significance are at 90% confidence level based on Student’s t test.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

The change in mean state and PMM-associated SST together modified the atmospheric response of the 500-hPa geopotential height in P2 (Fig. 10b). Two possible factors, the mean state and the SSTA pattern, determined the distinctions between Figs. 12a and 12b. A comparison between Figs. 12b and 12c (i.e., forcing the model with same SSTA during the period of P2 but with different mean states in C2 and C1, respectively) yields the effect of the mean state. Whereas a comparison between Figs. 12a and 12c (i.e., forcing the model with same mean state in C1 but with different SSTA during the period of P1 and P2 respectively) yields the effect of SSTA (forcing). It revealed that the positive NAO-like pattern and an NPO-like pattern in the North Pacific were both identified for Figs. 12b and 12c, but the magnitude in Fig. 12c was much weaker compared with Fig. 12b. Notably, the NPO-like atmospheric response resembles a stationary Rossby wave in response to the tropical heating (Simmons et al. 1983) induced by PMM (Di Lorenzo et al. 2010). By contrast, the positive NAO-like pattern associated cyclone anomaly in the Greenland was replaced a ridge in Fig. 12a (cf. Figs. 12a and 12c). This indicates that the SSTA (forcing), that is, the eastward shift (Fig. 10) of PMM-associated SSTA in P2, plays a critical role in determining the NAO-like response. The NAO-like structure was further enhanced by the mean state change of the eastward extension of upper-level jets.

7. Conclusions and discussion

The magnitudes of the second EOFs of the SST in the tropical Pacific (PMM) and North Atlantic (NAT) have increased simultaneously since the 1990s. The cross-basin interactions between the two and the associated possible processes were investigated through observations and numerical experiments. The main results (Fig. 13) are as follows.

  1. The total variance in the monthly NAT and PMM has increased since the early 1990s. Wavelet analysis indicated that this enhancement was associated with the interdecadal variations (8–16 yr) in the NAT and PMM, which have become significantly and positively coherent since the 1990s. The change in the interdecadal variation modified the interannual NAT–PMM relationship from negative to positive from P1 (1970–89) to P2 (1990–2014).

  2. Regression analysis revealed that the NAT had a lag impact on the PMM SST. The NAT-associated negative SSTA in the tropical North Atlantic forced a Matsuno–Gill-type response, a lower-level easterly anomaly extending from the tropical North Atlantic to the tropical North Pacific, accompanied by an anticyclone in the subtropical eastern North Pacific. The anticyclone was more southwesterly, which weakened the prevailing northeasterly trade wind and consequently contributed to the PMM SSTA through WES feedback. The NAT-associated meridional ocean temperature advection also partially contributed to the PMM development. The enhancement of WES feedback since 1990 was associated with an increase in the mean state of the North Pacific subtropical high.

  3. The observation and simulation, obtaining consistent results, revealed that the PMM-associated middle–upper atmospheric teleconnection exhibited distinct features in the North Pacific and North Atlantic between P1 and P2. The teleconnection was weaker and the downstream impact on the North Atlantic was nonsignificant in P1. By contrast, the teleconnection, resembling the NPO-like and NAO-like patterns in the North Pacific and North Atlantic, respectively, was significant and strong in P2. Numerical experiments indicated that this distinction primarily resulted from the eastward shift of PMM-associated convection, which was further enhanced by the eastward extension of the upper-level jet.

  4. The PMM-associated teleconnection in the North Atlantic featured a NAO-like pattern in P2, and this pattern exerted positive feedback on the NAT in P2. That is, the NAO-like pattern-associated cyclone (anticyclone) anomaly in the north (south) created a negative (positive) SSTA by decreasing (increasing) the downward shortwave radiation. Additionally, the anticyclone-anomaly-associated easterly in the south strengthened the prevailing northeasterly trade wind and contributed to the negative SSTA in the tropical Atlantic through WES feedback. The positive feedback of the PMM SST on the NAT-SST was identified only in P2 and not in P1.

Fig. 13.
Fig. 13.

Schematic diagram to illustrate the cross-basin interaction between North Pacific and North Pacific and the feedback of PMM to NAT in P2.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0594.1

NAT- and PMM-associated SSTAs exert substantial influence on local and remote climates (Gu et al. 2009; Lee et al. 2016; Zhang et al. 2016). The present study indicates that the increasing influences of the NAT and PMM are related to their enhancement, in which the interdecadal variation of both indices has become in phase and coherent since the 1990s. The enhancement of cross-basin interaction between the NAT and PMM since the 1990s also suggests that the NA SST provides a favorable large-scale condition for the development of the PMM and central Pacific El Niño, consistent with the finding of Yu et al. (2015). On the other hand, the PMM has positive feedback to NAT. Both processes work together to enhance the NAT–PMM connection. Here, we provided a possible pathway of PMM on NAT. The numerical experiments yields that the eastward shift of PMM-associated tropical heating (SSTA) during the period of P2 plays a critical role in determining the NPO-like and NAT-like response (cf. Figs. 12a and 12b), which was further enhanced by the mean state change (cf. Figs. 12b and 12c). We know the aforementioned processes might be limited by the length of observation and the design of numerical experiments. Further mechanism study and an investigation of other possible mechanisms of PMM on NAT are required and are now under investigation.

Additionally, future studies should examine why the magnitude of the interdecadal variation in the PMM and NAT SSTs enhanced and changed from an out-of-phase to in-phase relation after the 1990s. The AMO also changed from the negative phase to the positive phase after the 1990s. The warm phase change of the AMO in the 1990s enhanced the North Pacific subtropical high, which strengthened WES feedback and favored development of the PMM (Yu et al. 2015). The possible effect of the AMO, which also experienced an interdecadal change in the 1990s, and the effect of global warming on this interdecadal change is currently under investigation and will be presented in a subsequent study.

Acknowledgments.

We appreciate the reviewers’ comments which were helpful to improve our manuscript. The observational atmospheric and oceanic data used in this study are from the NOAA Earth System Research Laboratory (https://psl.noaa.gov/data/index.html), NCEP–NCAR (https://www.esrl.noaa.gov/psd/data/reanalysis/reanalysis.shtml), NOAA_ERSST_V5 (https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html), and NOAA/OAR/ESRL PSL, Boulder, Colorado, USA (https://psl.noaa.gov/data/gridded/data.prec.html). This study was supported by the Ministry of Science and Technology, Taiwan, under Grants 108-2119-M-001-014, 108-2111-M-845-001, 108-2111-M-845-500, and 109-2111-M-845-001. This manuscript was edited by Wallace Academic Editing.

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  • Fig. 1.

    (a) The SSTs (shading) and 850-hPa winds anomalies (climatology: 1979–2008) in JJA 2018. The blue box and red box denote the PMM and North Atlantic tripole (NAT) regions, respectively. Shading with dots indicates the percentile of SST in JJA 2018 larger than 90% or smaller than 10%. The percentile was ranked during 1948–2018. (b) The second EOF of SST in the eastern Pacific (PMM). The EOF was obtained from monthly ERSSTv5 with removing the annual cycle and long-term trend. (c) As in (b), but for the North Atlantic.

  • Fig. 2.

    (a) The time series of second principal component for the SST-EOF2 in the North Atlantic (Fig. 1c) and (b) the SST-EOF2 in the eastern tropical Pacific (Fig. 1b). (c) The lead–lag 241-month sliding correlation between NAT and PMM indices. Positive (negative) lag months indicate that the NAT index leads (lags) the PMM index.

  • Fig. 3.

    The 11-yr running total variance of the monthly (a) NAT index and (b) PMM index.

  • Fig. 4.

    Wavelet spectrum of the (a) NAT index and (b) PMM index. (c) Coherent spectrum of the cross wavelet between the NAT and PMM index. The vectors display the lead–lag relationship between two indices. The thick black curve denotes the cone of influence of the wavelet power spectrum. The vectors display the relation between two indices: right (left) means that they are in phase (out of phase); up (down) means PMM lead (lag) 1/4 period. The thick black lines indicate the spectrum exceeding the 95% confidence level. (d) Time series of 8–16-yr normalizing bandpass filtered NAT index (blue line) and PMM index (red line). Light (dark) gray shading denotes that the 8–16-yr filtered NAT and PMM were out of (in) phase in P1, i.e., 1970–89 (P2, i.e., 1990–2014).

  • Fig. 5.

    A comparison of lead–lag regression of SSTs (shadings) and 850-hPa winds (vectors) onto the NAT index between (a)–(c) P1 and (d)–(f) P2, for lag −3, 0, +3 months respectively. Vectors and shading with dots denote the signal exceeding the 10% significant level by Student’s t test.