Stability of ENSO teleconnections during the last millennium in CESM

doi:10.21203/rs.3.rs-2567333/v1

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Stability of ENSO teleconnections during the last millennium in CESM

https://doi.org/10.21203/rs.3.rs-2567333/v1

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published 10 Jul, 2023

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El Niño-Southern Oscillation (ENSO) poses large impacts on global climate through atmospheric teleconnections. Understanding the stability of ENSO teleconnections is not only important for future weather forecast and climate projection, but also for paleo-proxy based ENSO reconstructions. In this study, we explore decadal changes in ENSO teleconnections on global land surface temperature (LST) from 850 to 2005 AD using 13 ensemble members of the Community Earth System Model-Last Millennium Ensemble (CESM-LME). The CESM can simulate the main cooling in Eurasia along with a warming Arctic over northern Canada and Greenland, known as the warm Arctic-cold Eurasia (WACE) pattern, during the boreal winter of an El Niño, as well as western Antarctic warming during El Niño developing and decaying summers. The decadal changes in ENSO teleconnections on LST show large anomalies with pattern highly similar to WACE and western Antarctic warming in winter and summers, respectively. The decadal changes are mainly caused by ENSO precipitation-excited Rossby wave source to the west or east of Hawaii, and LST response over South Siberia to ENSO and associated precipitation response over North Eurasia can even reverse sign during different phases of this decadal variability. The decadal changes in CESM may be related to the interdecadal Pacific oscillation (IPO) and thus are likely attributed to internal variability rather than external forcing. Our results suggest that the decadal variability in ENSO teleconnections should be considered when reconstructing the ENSO using proxies from the Eurasian regions.

ENSO

Atmospheric teleconnections

Stability

Last millennium

Interdecadal Pacific Oscillation

The El Niño-Southern Oscillation (ENSO) is one of the most important interannual variabilities of Earth’s climate system, which has strong global impacts on rainfall and temperature over oceans and lands (McPhaden et al. 2006; Guilyardi et al. 2009; Collins et al. 2010; Deser et al. 2010; Andréa et al. 2021). The sea-surface temperature (SST) anomalies in the central-to-eastern equatorial Pacific associated with ENSO events change tropical climate by modifying the Walker circulation (Bjerknes1969; Gill 1980; Ropelewski and Halpert 1987; Klein et al.1999; Alexander et al. 2002; Meyers et al. 2007). The ENSO also modifies extratropical temperature and precipitation through atmospheric teleconnections, i.e., via the well-known Pacific-North American (PNA) and Pacific-South American (PSA) teleconnections, resulting in Eurasian and North American cooling against the global warming background (Hoskins and Karoly 1981; Wallace and Gutzler 1981; Mo and Ghil 1987; Lau and Nath 1994; Hoerling et al. 1997; Bladé et al. 2008). The ENSO also has large impacts on polar regions; and an El Niño event can induce Arctic and Antarctic warming through weakening the polar vortex (Domeisen et al. 2019; Li et al. 2021). These ENSO teleconnections are considered to be the stationary waves emanating from a source region (Hoskins and Ambrizzi 1993; Hoskins and Karlay 1981). Hence, the Rossby wave theory (Rossby 1945; Yeh 1949) based on dispersion and group velocity are applied generally to understand the variation of teleconnections (Hoskins and Karlay 1981; Karlay 1983; Li and Li 2012; Li et al. 2015; Zhao et al. 2015).

Due to ENSO teleconnections in affecting global surface temperature and precipitation, many long-term ENSO indices were reconstructed based on ENSO’s signals in global proxies (Gergis et al. 2006; Christie et al. 2009; Carr et al. 2013). An 1100-year long-term ENSO index was reconstructed based on tree rings over Southwest America due to the PNA teleconnections (Li et al. 2011). Undoubtedly, the certainty of the paleoclimate reconstruction must be based on the assumption of stationarity of ENSO teleconnections. However, recent studies revealed that ENSO and its regional teleconnections vary on interdecadal to centennial timescales (Diaz et al. 2001; Ault et al. 2013a; Tejavath et al. 2019). Model-based studies identified the existence of decadal to centennial timescale modulation of ENSO behaviors throughout the last millennium (Karnauskas et al. 2012; Borlace et al. 2013), which is also supported by studies based on proxy climate reconstructions (Cobb et al. 2003; Hope et al. 2017). Commonly, ENSO exhibits decadal variation in the paleo-ENSO reconstructions over the last millennium, which is likely to be the result of shifts in the teleconnections between ENSO and climate proxy records on which reconstructions are based (Hope et al. 2017). Previous studies cautioned that stationarity should not be assumed in ENSO reconstruction from proxy records (Coats et al. 2013; Gallant et al. 2013). Lewis and LeGrande (2015) revealed that there are significant changes in ENSO-associated local climate across the tropical Pacific for 100-year epochs throughout the last millennium. In addition, the non-stationarity of ENSO teleconnections is likely to be more problematic for extratropical regions. Therefore, to test whether we can use ENSO teleconnections in recent observations to reconstruct the ENSO index during the last millennium, it is necessary to study the stability of ENSO teleconnections first.

ENSO teleconnections were found to exhibit pronounced interdecadal variation (López-Parages et al. 2016; Park and Li 2019; Liu et al. 2021). The relationship between ENSO and North Atlantic Oscillation (NAO) shows significant interdecadal change (Knippertz et al. 2003; Greatbatch et al. 2004; Rodríguez-Fonseca et al. 2016). The influence of El Niño on the tropical North Atlantic SST, in terms of warming of tropical North Atlantic SST, depends on the phases of the Atlantic multi-decadal oscillation (AMO), and is usually intensified during the negative phase of the AMO (Park and Li 2019). The impact of the ENSO on rainfall over Europe is more significant in the 20th century than before (López-Parages and Rodríguez-Fonseca 2012). The relationship between ENSO and Indian Ocean SST also exhibits decadal variation, which depends on the strength of the linkage between decadal variabilities in the Pacific Ocean and Indian Ocean (Xie et al. 2010; Du et al. 2013; Tao et al. 2015; Liu et al. 2021). The ENSO-North Pacific teleconnection is significantly stronger in the late 20th century than that in the mid 20th century (Christopher 2018), while robust relationship between ENSO and Asian summer monsoon broke down in recent decades (Kumar et al. 1999; Zhou et al. 2007; He and Wang 2013; Geng et al. 2018).

Decadal-to-interdecadal changes of ENSO teleconnections were attributed to the diversity of the ENSO (Murphy et al. 2014; Ashok et al. 2007; Rodrigues et al. 2015; Zhang et al. 2015). The increased ENSO intensity after the 1970s favored the stronger ENSO-Indian Ocean teleconnections through enhancing local thermocline feedback (Chowdary et al. 2012; Xie et al. 2016). The low-frequency multidecadal variability, such as the AMO and interdecadal Pacific oscillation (IPO), can modulate the decadal change of interannual ENSO teleconnections (Wang et al. 2008; Chen et al. 2010; Watanabe and Yamazaki 2014; Geng et al. 2017; Feng et al. 2021; Li et al. 2021; Liu et al. 2021). During the positive AMO phase, the ENSO events are distinctly weaker than those in the negative AMO phase (Geng et al. 2020). The strongest external natural forcing, i.e., volcanic eruption, was found to not only increase the likelihood of El Niño (Adams et al. 2003; Emile-Geay et al. 2008; Timmreck, 2012; Stevenson et al. 2016; Liu et al. 2022), but also affect the decadal phase change of the AMO (Mann et al. 2021). Whether such ENSO decadal variability should be attributed to internal climate variability or to external forcing is an open question.

It is difficult to study decadal change of ENSO teleconnections due to the changes of ENSO intensity and structure (Torrence and Webster 1998; Greatbatch et al. 2004; An et al. 2006). The short and limited observation datasets are one reason for uncertainty in the study of decadal change. As a consequence, long-term outputs from ocean-atmosphere coupled numerical models were used to study this decadal change of ENSO teleconnections (Christopher 2018; Yu et al. 2018; King et al. 2020). The purposes of this study are to detect non-stationary behaviors of atmospheric teleconnections associated with ENSO during a millennium period and to examine their interdecadal modulators. The following two questions will be addressed in this paper: 1) What are the main features of non-stationary teleconnections during the last millennium? 2) What modulate the variation of the teleconnections on the decadal-to-multidecadal timescale? The paper is organized as follows. The datasets and analysis methods used in this study are described in section 2. In section 3, we present the main results in detail. Summary and discussion will be given in section 4.

The Community Earth System Model-Last Millennium Ensemble (CESM-LME) Project is an ensemble of global Earth System Model experiments spanning the period of 850-2005AD (Otto-Bliesner et al. 2016). These outputs have been widely used to analyze characteristics of paleoclimate (Abram et al. 2016; Shi et al. 2018; Stevenson et al. 2019; King et al. 2020; Liu et al. 2022). The monthly outputs used in this study come from 13 ensemble members under a full set of transient forcing (solar variability, volcanic eruption, land use, greenhouse gases, orbital change, and ozone aerosol) at 2º×2º resolution for the atmosphere and land and 1º×1º resolution for the ocean and sea ice.

The averaged SST in the Niño3.4 region (5ºS-5ºN; 120ºW-170ºW) in the boreal winter (December to February) is defined as a proxy of the ENSO. The other fields such as land surface temperature (LST), precipitation, geopotential height (GPH) at 200 hPa and global SST were seasonally averaged over a period from May to September (MJJAS) and from November to March (NDJFM) to provide what we refer to as the boreal summer and boreal winter fields, respectively.

To extract the decadal variability of ENSO teleconnections, empirical orthogonal function (EOF) analysis of 11-year-sliding regression was performed from 850 to 2005AD for all 13 ensemble members. First, we calculated the regression maps of LST onto the ENSO for each 11-sliding years with an interval of five years, to obtain 229 sets of 11-year-sliding regression maps for each of the 13 ensembles. Then, we performed the EOF analysis on these 229×13 maps to obtain decadal changes. To study the seasonal evolution from ENSO developing summer to decaying summer, the three regression maps for developing summer, peaking winter, and decaying summer of ENSO were connected as one regression map, as seasonal EOF analysis (Wang and An, 2005). The principal components (PCs) were normalized by their standard deviation, and each was multiplied onto the corresponding EOF pattern.

For verification, we used the NASA Goddard's Global Surface Temperature Analysis (GISTEMP; Hansen et al. 2010) and the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST; Rayner et al. 2003) spanning the period 1880–2021. The significance at 95% confidence level for regression and that for composite analyses were obtained by the two-tailed Student’s t test.

In addition, the wave ray based on the wave theory linearized on the zonal mean flow (Hoskins and Karoly, 1981), is used to depict the propagation of Rossby waves.

A wave ray is a curve depicting wave energy dispersing at its group velocity. Its displacements along the longitude Y and latitude X follow the formulas

$\frac{\text{d}\text{Y}}{\text{d}\text{t}}{|}_{{\text{c}}_{\text{g}}}={\text{c}}_{\text{g}\text{y}}$ and $\frac{\text{d}\text{X}}{\text{d}\text{t}}{|}_{{\text{c}}_{\text{g}}}={\text{c}}_{\text{g}\text{x}}$, (1)

where ${\text{c}}_{\text{g}}=({\text{c}}_{\text{g}\text{x}},{\text{c}}_{\text{g}\text{y}})$ denotes group velocity. The group velocity is in a form of

${\text{c}}_{\text{g}\text{x}}=\frac{2{\text{k}}^{2}{\stackrel{-}{\text{q}}}_{\text{y}}}{{\left({\text{k}}^{2}{+\text{l}}^{2}\right)}^{2}}$ , ${\text{c}}_{\text{g}\text{y}}=\frac{2\text{k}\text{l}{\stackrel{-}{\text{q}}}_{\text{y}}}{{\left({\text{k}}^{2}{+\text{l}}^{2}\right)}^{2}}$, (2)

whereas k, l are zonal and meridional wavenumbers, and ${\stackrel{-}{\text{q}}}_{\text{y}}$ is the meridional gradient of the basic-state absolute vorticity. For stationary wave, ${\text{k}}^{2}{+\text{l}}^{2}={\stackrel{-}{\text{q}}}_{\text{y}}/{\stackrel{-}{\text{u}}}_{\text{M}}$, with ${\stackrel{-}{\text{u}}}_{\text{M}}$ is the zonally mean zonal wind in the Mercator Projection $\stackrel{-}{\text{u}}/\text{c}\text{o}\text{s}{\phi }$. For a given flow and zonal wavenumber, we can integer Eq. (2) to derive its wave ray with the meridional wavenumber varying equation as following

$$\frac{\text{d}\text{l}}{\text{d}\text{t}}{|}_{{\text{c}}_{\text{g}}}=-\text{k}\frac{\partial {\stackrel{-}{\text{u}}}_{\text{M}}}{\partial \text{y}}+\frac{\text{k}}{{\text{k}}^{2}{+\text{l}}^{2}}\frac{{\partial }^{2}\stackrel{-}{\text{q}}}{\partial {\text{y}}^{2}}$$

In order to examine the effect of the zonally variation of the zonal wind on the propagation, the local quantities of basic state are used as the bar terms in the above formulas instead of the zonal-mean quantities (Hoskins and Ambrizzi, 1993). Although wave theories based on more complicated flows have been developed (Karoly 1983; Li and Li 2012; Li et al. 2015; Zhao et al. 2015), this simple theory still works well on the analysis of ENSO teleconnections in mid-high latitudes of the Northern Hemisphere. To calculate the wave ray, the fourth-order Runger-Kutta method is applied to integrate equations (2) and (3). The time interval is set as 1 hour and the total integration time is 30 days.

3.1 Climatic ENSO effects on global LST

To examine overall impact of ENSO on global LST, we diagnose the climatological seasonal-mean regression of global LST onto boreal-winter ENSO for the average of all 13 ensembles during 850-2005AD. The teleconnection patterns in the developing summer (MJJAS-1), boreal winter (NDJFM), and decaying summer (MJJAS + 1) are quite distinct (Figs. 1a-c), for both the sign and intensity. In MJJAS-1 (Fig. 1a), the impact of El Niño on LST manifests as cooling in middle latitude of Asia, central Asia, East Asia, the Maritime Continent, northern Australia, eastern and southwestern North America, while it triggers warming in Africa, Alaska, South America, and the West Antarctica near the Amundsen Sea. The ENSO-LST teleconnections intensify significantly during NJDFM when the ENSO is at its peak (Fig. 1b). The strongest cooling occurs in the northern Eurasian continent associated with an El Niño. In addition, cooling strengthens over the Tibet Plateau and mid-latitude North America, while the other parts of the world exhibit notable warming, especially West Asia, high-latitude North America, South America, Greenland, Australia, and the Antarctic. A key feature of the ENSO-LST teleconnections in the mid-to-high latitudes of the Northern Hemisphere, is the strong wintertime cooling in Eurasia along with a warming Arctic over northern Canada and Greenland, known as the warm Arctic-cold Eurasia (WACE) pattern on the interannual timescale (Cohen et al. 2012; Mori et al. 2014; Overland et al. 2015; Sun et al. 2016; Feng et al. 2021). Following the peak phase of El Niño, the intensity of the ENSO-LST teleconnections in MJJAS + 1 is weaker than that in the boreal winter, except for the persist stronger warming in South America and West Antarctic near the Amundsen Sea (Fig. 1c), whereas the signs of regression coefficients over Europe and India transit from negative to positive, indicating an opposite ENSO-LST teleconnections between boreal winter and decaying summer of the ENSO.

3.2 Decadal changes of ENSO teleconnections

Based on the above climatic regressions of three consecutive seasons, we conduct 11-year-sliding EOF analysis to examine the decadal-to-centennial changes of ENSO teleconnections on global LST, all of which are named decadal changes below. EOF1 explains about 7.7% of the total variance, which can be significantly separated from the other higher modes. For an El Niño, EOF1 mainly exhibits prominent cooling, exceeding − 0.4ºC, in the northern Eurasian continent during boreal winter (Fig. 1e), against the warming exceeding 0.3ºC in western North America from Alaska to Idaho and Greenland. Meanwhile, notable cooling exceeding − 0.2ºC distributes over the West Antarctic near the Amundsen Sea in both MJJAS-1 and MJJAS + 1. The results indicate that the pronounced decadal changes of ENSO teleconnections on global LST are located in the mid-to-high latitudes of the Northern Hemisphere in the boreal winter, and in the West Antarctic in both developing and decaying summers of the ENSO.

To identify the features of decadal non-stationary teleconnections, we employ composite analyses based on the two opposite phases of the normalized PC1, when the amplitudes are greater than + 1.0σ and less than − 1.0σ (where σ is the standard deviation of PC1), respectively. As we discussed above, the significant differences between the two opposite phases are located in the Eurasian continent during the boreal winter. When the amplitude is greater than + 1.0σ, extremely cold temperature dominates the northern Eurasia and extends to East Asia associated with an El Niño, which corresponds to the extreme warm temperature in Greenland (Fig. 2b). On the contrary, when the amplitude is smaller than − 1.0σ, cold temperature weakens over the high latitudes of Eurasia, and LST response to the El Niño over South Siberia is even reversed to show warming. At the same time, warming in Greenland is also slowing down, and the eastern part of this island even shows cooling (Fig. 2e). Since there are significant differences in the response of LST to ENSO in Eurasia, accordingly, we hereafter refer the two phases PC1 > + 1.0σ and PC1 < -1.0σ to as the “EA-cold phase” and “EA-warm phase,” respectively. In the EA-cold phase, the WACE pattern associated with an El Niño is enhanced. Meanwhile, remarkable decadal change of teleconnections also occurs in the Antarctic during MJJAS-1 and MJJAS + 1; and the warming of Antarctic LST during the EA-warm phase is much stronger than that during the EA-cold phase associated with El Niño, especially in the West Antarctic.

Figure 3 shows composite ENSO-related precipitation anomalies during the above two opposite phases. In MJJAS-1, differences of precipitation anomalies associated with two different phases are located in the middle and lower reaches of the Yangtze River in East China, with less rainfall in the EA-cold phase and more rainfall in the EA-warm phase (Figs. 3a and 3d). Meanwhile, the opposite east-west distribution of precipitation anomalies in Greenland is reversed in terms of different phases. During the boreal winter, northern Eurasia tends to experience less rainfall in the EA-cold phase and more rainfall in the EA-warm phase (Figs. 3b and 3e), and opposite rainfall responses also occur in eastern Greenland. During the El Niño decaying summer, the difference of precipitation responses to different phases is relatively weak. Over southwest North America, precipitation responses to El Niño for the EA-cold and warm phases are similar, indicating a stable wet response to El Niño from its developing summer to decaying summer during the last millennium.

To understand why there are significant decadal changes in ENSO-LST teleconnections, we examine composite El Niño SST structure and its 200-hPa teleconnections for the two phases (Fig. 4). The SST anomalies exhibit the well-known El Niño evolution, the Indian Ocean dipole (IOD) (Klein et al. 1999; Meyers et al. 2007; Du et al. 2009; Chowdary et al. 2014; Zhang et al. 2015; Stuecker et al. 2017) and the North Atlantic Tripole (NAT) anomalies (Sutton and Hodson 2003; Rodríguez-Fonseca et al. 2016; Jiménez‐Esteve and Domeisen 2018) from MJJAS-1 to MJJAS + 1. The most substantial difference between the EA-cold and warm phases is the location of the maximum SST warming in the tropical Pacific during the boreal winter. In the EA-cold phase, the maximum SST warming associated with the El Niño is located closer to the dateline, more like the Central-Pacific (CP) El Niño (Ashok et al. 2007). This westward shift of the maximum SST warming is also observed during the boreal summer. In the EA-warm phase, the maximum SST warming is located in the eastern Pacific, as the Eastern-Pacific (EP) El Niño.

Associated with the central-to-eastern equatorial Pacific warming, a PNA-like wave train, represented by 200-hPa high + low + high + low pressure anomalies from central equatorial Pacific to North America, appears in the Northern Hemisphere during the boreal winter (Figs. 4b and 4e). A PSA-like wave train, represented by southward high + low + high pressure anomalies from the equatorial Pacific to the Antarctic along 120^oW, is observed in the Southern Hemisphere during the austral winter for both ENSO developing (Figs. 4a and 4d) and decaying (Figs. 4c and 4f) years.

Atmospheric teleconnections associated with these different types of El Niño are quite different. For the EA-cold phase related to CP-like El Niño, the PNA teleconnection shows a zonal-type teleconnection from the North Pacific through Greenland to the North Atlantic (Fig. 4b); thus, the polar vortex is enhanced over Greenland while it is weakened over northern Eurasia, resulting in strong northerly wind and cooling over northern Eurasia. The PNA teleconnection for the EA-warm phase (Fig. 4e), however, exhibits a meridional-type teleconnection from the North Pacific through Canada to northern Eurasia. The strengthened polar vortex over northern Eurasia tends to weaken the northerly wind there, resulting in weak northern Eurasian cooling.

During MJJAS-1 and MJJAS + 1, a robust PSA-like wave train pattern characterized by a low-pressure system over the middle latitudes of the South Pacific, a high-pressure system near the Amundsen Sea of the West Antarctic and a low-pressure system over South America and the South Atlantic are emanated from the tropical Pacific in both phases. The Amundsen Sea low (ASL) weakening related to West Antarctic high-pressure anomalies induces a substantial warming in the West Antarctic. The PSA-like wave train is stronger for EP-like El Niño (Figs. 4d and 4f) than for CP-like El Niño (Figs. 4a and 4c), resulting in greater ASL weakening and western Antarctic warming for the EP-like El Niño.

3.3 IPO-determined decadal changes in ENSO teleconnections

To understand what contributes to the decadal variation of ENSO teleconnections, we conduct regression analysis of global SST anomalies against PC1. Figure 5a exhibits typical negative phase of the IPO, with significant negative SST anomalies in the central and eastern equatorial Pacific and positive SST anomalies in the North and South Pacific. Accompanying this simulated negative IPO, the North Atlantic exhibits negative SST anomalies. The SST patterns of the IPO usually last for 20–30 years, with dominated oscillation peaks at 30, 34, and around 20 years in the spectrum analysis of PC1 (Fig. 5b).

ENSO teleconnections are usually triggered by its associated convection anomaly over the tropical Pacific. Compared to the EP-like El Niño during the EA-warm phase and positive IPO phase, the positive convection anomaly associated with CP-like El Niño during the EA-cold phase and negative IPO phase moves westward (Fig. 5a), which may contribute to different ENSO teleconnections during these positive and negative IPO phases.

In a linear theory (Hoskins and Karoly 1981; Liu et al. 2013), the upper-troposphere teleconnections are usually determined by the background wind and Rossby-wave source associated with convection. To understand why the westward shift of CP-like El Niño convection can produce zonal-type teleconnection while EP-like El Niño favors a meridional one, we use the wave ray theory, which has been widely used to depict the propagation of Rossby-wave energy based on zonal flow or wave theory (Hoskins and Karoly 1981; Hoskins and Ambrizzi 1993; Li and Li 2012; Li et al. 2015; Zhao et al. 2015), to investigate these two terms. In the CESM-LME, differences in the zonal wind between EA-cold and EA-warm phases are quite small (Fig. 6); and wave rays starting from the same location did not show significant difference in the trajectory (not shown). Since the shift of convection in different El Niños, the wave ray in the EA-cold phase related to CP-like El Niño is set to start at 163°W to the west of Hawaii, and that in the EA-warm phase related to EP-like El Niño starts at 145°W to the east of Hawaii. The wave rays with initial zonal wavenumber 1 show different propagation patterns during these two phases, although both display “great circle”-like trajectory. For the EA-cold phase, the ray becomes more zonally approach to the Greenland, while for the EA-warm phase, it exhibits more meridionally propagating pattern (Fig. 6), consistent with the CESM simulations. This result means that the shift of the wave source location rather than the background flow that determines different ENSO teleconnections pattern between the two phases.

To investigate whether this decadal variation of ENSO teleconnections is attributed to internal variability or to external forcing, we use the average of the 13 ensembles to remove internal variability; then, remained significant signals can be attributed to external forcing (Zanchettin et al. 2013). During the last millennium from 850 to 2005AD, global temperature experienced Medieval warm period around 1000AD, cold Little Ice Age from the 14th century to 19th century, and current modern warm period (Chai et al. 2018). The average of these PC1s of all 13 ensembles, however, does not show significant signals except for significant negative-to-positive transition around 1258 Samalas eruption, and negative signals around 1710AD and 1975AD (Fig. 7a). The latter two periods were not close to famous large eruptions at 1695 and 1982AD (Liu et al. 2022). From 850 to 2005AD, there were more than 40 large tropical eruptions, while significant signals in ensemble average only appeared three times, which means that the significant ensemble average was due to the small ensemble size of 13. The interannual variability maybe cannot be totally removed by the average of only 13 ensembles. To check whether the long-term forcing from solar radiation and anthropogenic greenhouse gas concentration, we perform EOF analysis on the 50- and 100-year-sliding regression, and still no signals can be simulated in the 13-ensemble average (Figs. 7b and 7c). These results suggest that the decadal variation of ENSO teleconnections in the CESM-LME is mainly attributed to interannual variability rather than to external natural or anthropogenic forcing.

3.4 Observed decadal changes of ENSO teleconnections

To explore whether the simulated decadal changes of ENSO teleconnections exist in the observations, we perform the same analyses based on the NASA Goddard's Global Surface Temperature Analysis (GISTEMP) and the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) spanning the period 1880–2021. As shown in Figs. 8a-8c, the ENSO-LST teleconnections in the observations are similar to that in the simulations (Figs. 1a-c), presenting strong wintertime cooling trend in Eurasia along with a warming Arctic over northern Canada and Greenland, i.e., the WACE pattern (Cohen et al. 2012; Mori et al. 2014; Overland et al. 2015; Sun et al. 2016; Feng et al. 2021). In the observations, EOF1 of 11-year-sliding regression, explaining about 19.7% of the total variance, also exhibits prominent wintertime cooling over northern Eurasia, consistent with the simulations, although North America displays an opposite pattern to that of the simulations (Fig. 8e). The IPO-like pattern can be also detected as a decadal modulator for ENSO teleconnections in the observations (Fig. 9). These results mean that the simulated decadal ENSO teleconnections on LST mimics the observations very well, although the tropical North Atlantic exhibits significant warming related to cold IPO in the observations against cooling in the simulations.

In this study, we investigate decadal variation of ENSO teleconnections on LST from associated ENSO developing summer to decaying summer. The CESM simulates substantial climatic teleconnections during the peak phase of El Niño, i.e., boreal winter, which exhibits a cooling trend in Eurasia along with a warming Arctic over northern Canada and Greenland, known as the WACE pattern. It also simulates the western Antarctic warming during both El Niño developing and decaying summers. The decadal variation of ENSO teleconnections exhibits large perturbations with a pattern similar to WACE pattern in the boreal winter, and over the western Antarctic for ENSO developing and decaying summers.

During the positive and negative phases of this decadal variability, Eurasian winter LST response to an El Niño exhibits opposite “EA-cold phase” and “EA-warm phase” accordingly, which are attributed to the distinct patterns of Arctic polar vortex forced by the diversity of El Niño. During the positive phase, El Niño shows a CP type and its precipitation-excited Rossby wave source is located to the west of Hawaii. This Rossby wave forcing tends to excite a zonal-type teleconnection and weaken the Arctic polar vortex centered near Eurasia, leading to a cold and dry winter over the high latitudes of Eurasia and a warm and dry winter in the high latitudes of North America. During the negative phase, El Niño exhibits an EP type with its Rossby-wave source to the east of Hawaii, and it will excite a meridional-type teleconnection and weaken the polar vortex over Greenland, resulting in warmer and wetter winter over Eurasia compared to the positive phase. We show that the simulated decadal changes of ENSO teleconnections during the last millennium are mainly caused by internal IPO mode rather than by external forcing.

The stationary of ENSO teleconnections is a crucial issue for paleo-ENSO reconstruction based on proxy records, such as coral, tree rings, and sediment cores. A number of studies revealed the decadal-to-centennial variability of the ENSO (Diaz et al. 2001; Hope et al. 2017), and the non-stationarity relationships between ENSO and distant climates in specific oceans (Lewis and LeGrande 2015; Christopher 2018; Park and Li 2019; Liu et al. 2021), land areas (López-Parages 2012, 2016; Coats et al. 2013), and even polar regions during the last millennium (Feng et al. 2021; Li et al. 2021). As a supplement and extension of previous studies, we investigate the non-stationary behaviors of atmospheric teleconnections associated with the ENSO during a millennium period by using the outputs of the CESM-LME. The large perturbation in the WACE pattern requires that the decadal variability need to be considered in the reconstruction of ENSO based on proxies from these regions. Note that the precipitation response over southwestern North America is quite stable from this decadal variability, which builds up confidence on the reliability of using tree rings over this region to reconstruct the ENSO (Li et al. 2011).

Author Contributions XH and YL were responsible for design of the research. Material preparation, data collection, and analysis were performed by XH, YL and FL. JL, XZ and LF helped interpret the results. XH wrote the first draft of the manuscript. All authors provided comments on different versions of the manuscript. All authors read and approved the final manuscript.

Funding This work was jointly supported by the Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004), and the Natural Science Foundation of China (42175061; 41975107).

Data Availability Statement CESM1 Last Millennium Ensemble (LME) database was downloaded from https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.cesmLME.html. For details regarding the LME, see https://www.cesm.ucar.edu/projects/community-projects/LME/.

Conflicts of Interest The authors declare that they have no competing interests.

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Stability of ENSO teleconnections during the last millennium in CESM

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Abstract

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1 Introduction

2 Data And Method

3 Decadal Change Of Enso Teleconnections On Global Lst

3.1 Climatic ENSO effects on global LST

3.2 Decadal changes of ENSO teleconnections

3.3 IPO-determined decadal changes in ENSO teleconnections

3.4 Observed decadal changes of ENSO teleconnections

4 Summary And Discussion

Declarations

References

Additional Declarations

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