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  • View in gallery

    The average change (tendency) of the index over 1 day for the (a) NAM index and (b) SAM index (gpm day−1). The cool colors denote the changes for the winter cold season, and the warm colors denote the changes for the warm season. The minimum MJO amplitudes considered in the calculation of each average tendency are indicated (Flatau and Kim 2013). MJO phases 1–3 occur in the Indian Ocean and phases 4–8 occur in the Pacific.

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    (top to bottom) Total OLR composite on lag day 0, with lagged composites of SAT on lag days 0, 5, 10, and 15 for MJO phases (left) 1 and (right) 5. The MJO phase 1 is defined when the convection occurs in the western tropical Indian Ocean while MJO phase 5 takes place when the convection occurs in the western tropical Pacific. Solid contours are positive, dashed contours are negative, and the zero contours are omitted (Yoo et al. 2011).

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    Schematic atmospheric circulation pattern in response to ENSO warm events superimposed on the corresponding SST composite (Yuan 2004). The Rossby wave train emanating from the tropics leads a high SLP anomaly in the southeast Pacific. Because of the warm SST, the Hadley cell is enhanced and contracted in the South Pacific while weakened and expanded in the South Atlantic. It results in the jet stream moving equatorward in the Pacific but poleward in the Atlantic. This change in the jet stream leads to the changes of storm distribution.

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    Partial correlation coefficients of 500-hPa geopotential height (GPH) with the normalized (a) EP and (b) CP El Niño indices for DJF during 1979–2009. The EP El Niño index is defined by the traditional Niño-3 index, while CP El Niño index is defined as IEM = Ta,C − 0.5Ta,E − 0.5Ta,W, where Ta,C, Ta,E, and Ta,W are the mean SST anomalies over the CP (10°S–10°N, 165°E–140°W), EP (15°S–5°N, 110°–70°W), and western Pacific (10°S–20°N, 125°–145°E), respectively. The term IEM reflects the pattern of warm central equatorial Pacific and cold western and eastern equatorial Pacific. Regions above the 90% confidence level are shaded. The Rossby wave train excited by CP El Niño propagates west of the wave emanated by EP El Niño and produces a less significant positive center in the Amundsen Sea (Sun et al. 2013).

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    Regression coefficients of bimonthly SST (°C; shading) and 500-hPa GPH (m; contours) on the Niño-3 index for the period of 1951–2005. SST data are from the Met Office Hadley Centre dataset, and the GPH data are from the NCAR–NCEP reanalysis dataset. The regression coefficients of GPH on the Niño-3 index for the September–October mean time series in the top-left panel show the most profound Rossby wave propagation compared to other months (Jin and Kirtman 2010).

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    Cross-spectra between (a) PSA and wave 3, (b) SAM and semiannual oscillation (SAO), (c) PSA and SAM, and (d) PSA and SAO. SAO is an index of semiannual oscillation defined as the difference between zonal-mean SLP at 50° and 65°S. The 53-yr (1950–2003) monthly time series of these indices derived from NCAR–NCEP reanalysis were standardized and detrended before calculating the cross-spectra. Dashed lines indicate the 95% confidence level. PSA and wave 3 share significant energy at 3–5-yr periods. SAM and PSA also share significant variance at interannual and decadal time scales (Yuan and Li 2008).

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    (a) SAM (solid) and Niño-3.4 (dashed) indices from 1997 to 2007. The indices’ out-of-phase periods, which produce in-phase impact in the Weddell Sea, are shaded in gray. (b) Six-month running mean of meridional wind anomalies (dashed line) at 75°S, 52.5°W, and SIC anomalies averaged over the shelf in the western Weddell Sea (solid). Dark gray shading marks calendar years when more shelf water is formed, while light gray shading marks years when less is formed. (c) Temperature anomalies at 3096 m (dashed line) and 4560 m (solid line) below sea surface in the northwest Weddell Sea. The dark gray shading indicates calendar years of anomalously cold pulses, and light gray indicates calendar years of anomalously warm pulses (mean temperature anomaly for that year, negative or positive, respectively). Negative SAM and El Niño events lead to more shelf water production in the western Weddell Sea shelf region, and consequently produce cold pulses on the Weddell Sea Bottom Water more than a year later (McKee et al. 2011).

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    (top) Surface temperature (K, color shading), and (bottom) 500-hPa GPH (gpm; contour interval 10 gpm) anomalies associated with the composite sum of (a) all El Niño and La Niña winters, (b) El Niño and La Niña winters in which at least one SSW occurs, and (c) El Niño and La Niña winters during which no SSWs occur. In the bottom panels, the red (blue) contours indicate positive (negative) GPH anomalies, and the black line (gray shading) indicates anomalies with p < 0.05 for a two-tailed Student’s t test. The composites were calculated from the NCAR–NCEP reanalysis dataset for the period of 1958–2013. The mean for all ENSO events in (a) cancels the linear impacts induced by El Niño and La Niña events. The composites of ENSO events with SSWs in (b) limit ENSO’s linear influence in the troposphere (no clear Rossby wave in the GPH composite) and isolate ENSO’s influence through the stratospheric pathway, which results in a warm North American and cold Europe. Without ENSO influences, the stratospheric activity produces the opposite temperature anomalies in (c) (Butler et al. 2014).

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    Principal modes of covarying tropical SST and AP surface temperature in austral fall. Maximum covariance analysis (MCA) results for MAM 1979–2009 tropical (30°S–30°N) SST and surface air temperature in the AP. (a) Mode 1 tropical SST (shading interval 0.1°C) and (b) mode 1 surface temperature in the AP (shading interval 0.2°C). (c) Mode 1 expansion coefficient of the SST (dark gray) and surface air temperature in the AP (light gray). (d) Regression of the MCA mode 1 SST times series against ERA-Interim geopotential height (contour interval of 10 m) and winds (vector; m s−1) at 200 hPa. Amplitudes in (a) and (b) are scaled by one standard deviation of the corresponding time series in (c). In (d), shading denotes regions in which the correlation of the MCA mode 1 SST time series with Z200 is significant at or above the 95% confidence level. The wind vectors are displayed if either component is significantly related to the MCA mode 1 SST time series (above the 95% confidence level) (Ding and Steig 2013).

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    (left) Composite 300-hPa zonal wind anomalies (m s−1) and (right) transient eddy momentum flux convergence (10−6 m s−2; gray lines) and stationary eddy momentum flux convergence (10−6 m s−2; black lines) for the (a) CP El Niño and (b) EP El Niño events. Light (dark) gray shading indicates the equatorward (poleward) side of the midlatitude jet. The zonal winds and momentum fluxes are derived from the NCEP–NCAR reanalysis dataset for the period of 1979–2014. The transient eddy momentum convergence and stationary momentum convergence cancel each other out in the mid–high latitudes for EP El Niño events, resulting in a weaker high-latitude ENSO impact (Yu et al. 2015).

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    During the last Ice Age or LGM, there were marked changes in temperature and precipitation relative to the present. As an example, the changes shown here are from Chiang and Bitz (2005), who used the CCM3 coupled to a 50-m slab ocean to study this period. (a) The described glacier extent (red) during the LGM. Glacier ice covered large tracts of the high (and even middle) latitudes; (b) annual-mean differences in SST and surface temperature between LGM and present-day simulations; (c) annual-mean differences in precipitation (mm day−1) between LGM and present-day simulations. Note the southward shift of the ITCZ across the globe and the marked consequential shift in precipitation patterns.

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    Climate proxy records during the last glacial to interglacial transition: (a) δ18O and CO2 (ppmv) from West Antarctica (WAIS Divide Project Members 2013; Marcott et al. 2014); (b) Opal flux from sediment core TN057–13PC9 (Anderson et al. 2009); (c) δ18O from the North Greenland Ice Core Project (Rasmussen et al. 2006) and (d) from the Hulu and Dongge Caves, China (Yuan et al. 2004). Also shown are timing of HE-1, Antarctic Cold Reversal (ACR), and YD following that used in references.

  • View in gallery

    How a polar–subpolar North Atlantic sector could have impacted the tropics during cold glacial and deglacial climates. The large NH ice sheets that exist during the Ice Age—and their attendant impacts on tropical climate—present scenarios for which we have no precise modern analogs (cf. Figs. 3 and 4). (a) From Anderson and Carr (2010), who reviewed a scenario whereby expanded winter sea ice in the North Atlantic, following a freshwater influx, induces a southward displacement or intensification of the southern westerlies. The change in winds causes increased exchange between surface and deep waters, releasing CO2 into the atmosphere and helping to end an Ice Age (termination). The conceptual model is in part based on Anderson et al. (2009), Toggweiler and Lea (2010), and Denton et al. (2010). (b) S.-Y. Lee et al. (2011) examined the hypothesis presented in the top panel using the CCM, version 3.6. In (b), BASE represents the present climate; the bottom in (b) shows the hypothesized effects of extremely cold North Atlantic conditions, such as during Heinrich events (see text), including marked impacts to the ITCZ and Hadley cell, the effects of which can reach even the high southern latitudes and southern CDW, as envisioned in the top panel.

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    Climatological zonal-mean sea level pressure for the period of 1901–2000 in (a) February and (b) September, derived from the historical run of 42 CIMP5 fully coupled climate models. The amplification of model uncertainties in the polar regions, particularly in the Antarctic, indicates the models’ deficiencies in representing the atmosphere–ocean–sea ice coupled system as well as in representing the extreme environment of continental Antarctica.

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The Interconnected Global Climate System—A Review of Tropical–Polar Teleconnections

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  • 1 Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York
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Abstract

This paper summarizes advances in research on tropical–polar teleconnections, made roughly over the last decade. Elucidating El Niño–Southern Oscillation (ENSO) impacts on high latitudes has remained an important focus along different lines of inquiry. Tropical to polar connections have also been discovered at the intraseasonal time scale, associated with Madden–Julian oscillations (MJOs). On the time scale of decades, changes in MJO phases can result in temperature and sea ice changes in the polar regions of both hemispheres. Moreover, the long-term changes in SST of the western tropical Pacific, tropical Atlantic, and North Atlantic Ocean have been linked to the rapid winter warming around the Antarctic Peninsula, while SST changes in the central tropical Pacific have been linked to the warming in West Antarctica. Rossby wave trains emanating from the tropics remain the key mechanism for tropical and polar teleconnections from intraseasonal to decadal time scales. ENSO-related tropical SST anomalies affect higher-latitude annular modes by modulating mean zonal winds in both the subtropics and midlatitudes. Recent studies have also revealed the details of the interactions between the Rossby wave and atmospheric circulations in high latitudes. We also review some of the hypothesized connections between the tropics and poles in the past, including times when the climate was fundamentally different from present day especially given a larger-than-present-day global cryosphere. In addition to atmospheric Rossby waves forced from the tropics, large polar temperature changes and amplification, in part associated with variability in orbital configuration and solar irradiance, affected the low–high-latitude connections.

© 2018 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: Xiaojun Yuan, xyuan@ldeo.columbia.edu

This article is included in the Connecting the Tropics to the Polar Regions Special Collection.

Abstract

This paper summarizes advances in research on tropical–polar teleconnections, made roughly over the last decade. Elucidating El Niño–Southern Oscillation (ENSO) impacts on high latitudes has remained an important focus along different lines of inquiry. Tropical to polar connections have also been discovered at the intraseasonal time scale, associated with Madden–Julian oscillations (MJOs). On the time scale of decades, changes in MJO phases can result in temperature and sea ice changes in the polar regions of both hemispheres. Moreover, the long-term changes in SST of the western tropical Pacific, tropical Atlantic, and North Atlantic Ocean have been linked to the rapid winter warming around the Antarctic Peninsula, while SST changes in the central tropical Pacific have been linked to the warming in West Antarctica. Rossby wave trains emanating from the tropics remain the key mechanism for tropical and polar teleconnections from intraseasonal to decadal time scales. ENSO-related tropical SST anomalies affect higher-latitude annular modes by modulating mean zonal winds in both the subtropics and midlatitudes. Recent studies have also revealed the details of the interactions between the Rossby wave and atmospheric circulations in high latitudes. We also review some of the hypothesized connections between the tropics and poles in the past, including times when the climate was fundamentally different from present day especially given a larger-than-present-day global cryosphere. In addition to atmospheric Rossby waves forced from the tropics, large polar temperature changes and amplification, in part associated with variability in orbital configuration and solar irradiance, affected the low–high-latitude connections.

© 2018 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: Xiaojun Yuan, xyuan@ldeo.columbia.edu

This article is included in the Connecting the Tropics to the Polar Regions Special Collection.

1. Introduction

Improving our understanding of the dynamics of the atmosphere–ocean–sea ice system and the connecting mechanisms between the high and low latitudes has become increasingly important to climate science in the face of a rapidly warming world. The polar regions and the cryosphere in both hemispheres are active components in global climate. For example, changes within the polar regions dictate the strength of the thermal gradient between the tropics and the poles.

Climate changes have been observed in both of Earth’s polar regions over the past several decades and have been magnified in the last ~10 years in terms of recorded sea ice extent (SIE) and surface temperatures. For example, in September 2012 Arctic sea ice extent set a new record low in more than three decades of satellite observations, while Antarctic sea ice extent reached a record high for the same period, reported by the National Snow and Ice Data Center (http://nsidc.org/cryosphere/sotc/sea_ice.html). While September Arctic SIE has slightly recovered since 2013, Antarctic SIE continued to reach record highs until 2014, followed by a drop in 2016 and 2017.

Near-surface temperatures in the Arctic region show a warming of ~0.7 K decade−1 (Cavalieri and Parkinson 2012), which reflects primarily an ice-albedo feedback. Since Antarctic sea ice mostly melts back to the coast in summer when the sun returns to the Southern Hemisphere (SH) and albedo is highly correlated with sea ice concentration (SIC; Shao and Ke 2015), the ice-albedo feedback is not as important as it is in northern high latitudes. There is no consistent sea surface temperature (SST) warming. Instead, surface temperatures show a strong spatial contrast, with rapid warming (~0.35°C decade−1) around the Antarctic Peninsula (AP) and a net cooling in East Antarctica (Chapman and Walsh 2007; O’Donnell et al. 2011; Turner 2016). Studies had attributed the Antarctic cooling and sea ice expansion to ozone depletion (Thompson and Solomon 2002; Turner et al. 2009). However, recent work has shown that the response to ozone depletion should be less sea ice, while the opposite is observed (Bitz and Polvani 2012). Moreover, most climate models produce declined Antarctic sea ice in the recent decades (Shu et al. 2015). On the other hand, more recent studies suggest that decadal changes in the Antarctic Peninsular surface climate may be linked to the changes in tropical SSTs (Ding and Steig 2013; Li et al. 2014). These results refocus attention on the connections from the tropics to the poles.

It has been long known that polar climate is strongly influenced by the tropical SST variability related particularly to the El Niño–Southern Oscillation (ENSO) phenomenon, owning to its far-reaching impact on many aspects of the global climate system. The influences of ENSO can be observed in the atmosphere, ocean, sea ice, and glacial ice in polar regions of both hemispheres (Turner 2004). The atmospheric responses at southern high latitudes include anomalies in sea level pressure, troposphere height, streamfunction, blocking events, precipitation, surface winds, and temperature (van Loon and Shea 1985; Mo and White 1985; Krishnamurti, et al. 1986; Trenberth and Shea 1987; Karoly 1989; Smith and Stearns 1993; Cullather et al. 1996; Sinclair et al. 1997; Villalba et al. 1997; Kiladis and Mo 1998; Marshall et al. 1998; Noone et al. 1999; Bromwich et al. 2000; Renwick 1998; Liu et al. 2002). Similarly, the atmospheric responses can be traced in the Northern Hemisphere (NH) extratropics (Trenberth et al. 1998; Pozo-Vázquez et al. 2005; Cassou and Terray 2001; Jevrejeva et al. 2003). The mechanisms fostering the connection between ENSO and the high latitudes through the troposphere include 1) the Rossby waves generated by tropical convection (Karoly 1989; Mo and Higgins 1998; Kiladis and Mo 1998; Garreaud and Battisti 1999); 2) jet stream changes in response to tropical SST changes (Chen et al. 1996; Bals-Elsholz et al. 2001); 3) anomalous mean meridional and zonal circulations and associated heat fluxes (Carleton and Whalley 1988; Cullather et al. 1996; Kreutz et al. 2000; Liu et al. 2002; Seager et al. 2003; Liu et al. 2004; Yuan 2004); and 4) altered transient eddy activity (Carleton and Carpenter 1990; Carleton and Fitch 1993; Sinclair et al. 1997; Carleton and Song 2000). Through the atmospheric connection, ENSO events significantly influence sea ice variability in the Antarctic (Simmonds and Jacka 1995; Yuan and Martinson 2000, 2001; Harangozo 2000; Kwok and Comiso 2002; Martinson and Iannuzzi 2003) and in the Arctic (Gloersen 1995; Loewe and Koslowski 1998; Venegas and Mysak 2000; Jevrejeva et al. 2003).

Studies of the tropical–polar teleconnection have advanced rapidly in the recent decade since earlier reviews on the subject (Trenberth et al. 1998; Turner 2004), given the accumulation of polar cryosphere observations, enhanced atmospheric data assimilation, and improved climate models. Emerging studies suggest that tropical climate variability at other (“non ENSO”) time scales also reaches the polar regions. For example, tropical variability on an intraseasonal time scale, namely, the Madden–Julian oscillation (MJO), impacts extratropical regions as far as the high-latitude Arctic (Yoo et al. 2011). At multidecadal (or long-term trend) time scales, tropical Pacific SST variability and associated Rossby wave trains influence the southern annular mode (SAM) and surface temperature around the AP and West Antarctica (Ding et al. 2011, 2012; Ding and Steig 2013; Schneider et al. 2012a,b; Clem and Fogt 2013, 2015; Clem and Renwick 2015; Yu et al. 2015). The tropical forcing that influences the high latitudes has been also found in the equatorial Atlantic (Li et al. 2014; Simpkins et al. 2014) and Indian Ocean (Nuncio and Yuan 2015). In addition to the connective mechanisms through the troposphere, teleconnections can also take stratospheric pathways (Butler and Polvani 2011). Here, we summarize some of the recent studies, including those mentioned above, which are organized by time scale from intraseasonal, interannual, decadal to multidecadal, and centennial and longer, including paleoclimate studies. In summary, this review tries to follow an overarching theme: that the problems and research findings of recent and past climates can often be appreciated better within the context of tropical–polar linkages. Also, studies of tropical–polar connections based on instrumental records can greatly help paleoclimate researchers better understand inferred processes in the past.

2. Connections at intraseasonal time scales

Tropical–polar teleconnections at intraseasonal time scales were discovered in the last decade. The most profound tropical intraseasonal variability is the MJO, which can modulate high-latitude atmospheric circulation (Matthews and Meredith 2004; Zhou and Miller 2005; Cassou 2008; L’Heureux and Higgins 2008; Flatau and Kim 2013). Based on reanalysis data, satellite observations, polar bottom pressure records, and tide gauge station data, Matthews and Meredith (2004) found that the SAM peaks approximately seven days after the MJO. Three days after this atmospheric response to the MJO, an increase in the ocean transport through Drake Passage was found. This associated oceanic intraseasonal variability is well captured by the Ocean Circulation and Climate Advanced Modelling (OCCAM) global ocean model (Webb and de Cuevas 2002), which indicates that up to 15% of oceanographic intraseasonal variance can be linearly attributed to the MJO (Matthews and Meredith 2004). On the other hand, Pohl et al. (2010) claimed that the MJO does not have a significant impact on SAM. Contrary to the conclusion of Pohl et al. (2010), Flatau and Kim (2013) found that the MJO is capable of forcing the leading modes of mid–high-latitude atmospheric circulation, namely, the northern annular mode (NAM) and SAM in both hemispheric winter and summer. They showed that Indian (Pacific) Ocean convection related to the MJO precedes the increase (decrease) in the NAM and SAM indices during the respective hemispheric cold seasons. During the hemispheric warm seasons, NAM has a similar response to that in the cold season, but SAM has the opposite response (Fig. 1), although the observational uncertainties are larger for the warm season.

Fig. 1.
Fig. 1.

The average change (tendency) of the index over 1 day for the (a) NAM index and (b) SAM index (gpm day−1). The cool colors denote the changes for the winter cold season, and the warm colors denote the changes for the warm season. The minimum MJO amplitudes considered in the calculation of each average tendency are indicated (Flatau and Kim 2013). MJO phases 1–3 occur in the Indian Ocean and phases 4–8 occur in the Pacific.

Citation: Journal of Climate 31, 15; 10.1175/JCLI-D-16-0637.1

The impact of the MJO on polar atmospheric circulation extends to the surface climate, such as surface temperature. S. Lee et al. (2011) investigated the connection of Arctic temperature variability to MJO using ERA-40 reanalysis data. They used the coupled self-organizing map (SOM) between the NH 250-hPa streamfunction and tropical convective precipitation to detect dynamic links between the low and high latitudes. They found that the tropical convection associated with MJO causes extratropical circulation changes through atmospheric Rossby wave propagation, and the circulation anomalies can be established at high latitudes in 3–6 days as the Pacific–North America (PNA) pattern. These MJO-induced circulation changes alter poleward heat transport. Together with adiabatic warming and downward infrared radiative fluxes, the anomalous poleward heat transport is capable of influencing the variability of winter surface temperature in the Arctic. This result is consistent with the results of Graversen (2006). Yoo et al. (2011) further found in observations that MJO heating in the tropical Pacific is followed 1–2 weeks later by Arctic warming through atmospheric circulation changes [similar to the finding by S. Lee et al. (2011)], whereas MJO heating in the equatorial Indian Ocean is followed by Arctic cooling (Fig. 2).

Fig. 2.
Fig. 2.

(top to bottom) Total OLR composite on lag day 0, with lagged composites of SAT on lag days 0, 5, 10, and 15 for MJO phases (left) 1 and (right) 5. The MJO phase 1 is defined when the convection occurs in the western tropical Indian Ocean while MJO phase 5 takes place when the convection occurs in the western tropical Pacific. Solid contours are positive, dashed contours are negative, and the zero contours are omitted (Yoo et al. 2011).

Citation: Journal of Climate 31, 15; 10.1175/JCLI-D-16-0637.1

In addition to the impacts on polar atmospheric circulation, ocean transport, and surface air temperature (SAT), the MJO’s influence was also found in Arctic sea ice during both winter and summer (Henderson et al. 2014). Daily sea ice concentration responds to the atmospheric circulation anomaly patterns in high latitudes that are associated with MJO variability. The sea ice responses appear larger in winter than in summer. Although the Arctic sea ice responses are statistically significant, the magnitudes of change are rather small.

New research also has revealed mechanisms by which MJO anomalies affect high-latitude climate. Modeling studies reveal that the MJO influences polar surface temperature through the Rossby wave train propagation (Yoo et al. 2012a,b). Based on a budget analysis of zonal-mean winds, Sakaeda and Roundy (2014) found that the MJO triggers anomalies in the global zonal-mean zonal winds in the upper troposphere at the intraseasonal time scale, starting from the tropics and propagating to the extratropics. The complicated interaction between the background state and zonal-mean zonal winds, as well as the feedback from the modulated synoptic-scale circulation, facilitate the poleward propagation of the MJO-related anomaly.

The Rossby wave propagation and zonal-mean zonal wind changes in the troposphere are not the only mechanisms linking MJO and high-latitude climate. Garfinkel et al. (2012) found that MJO has a strong connection with the NH wintertime stratosphere polar vortex, consequently influencing the tropospheric Arctic Oscillation one to two months later. The magnitude of MJO-induced stratosphere temperature anomaly can reach 4 K, which is comparable to that associated with tropical forcing at interannual time scales. The authors hypothesized that MJO-excited Rossby wave trains propagate both poleward and upward, altering the stratospheric polar vortex. Through the downward propagation of stratospheric signal and the coupling between the stratosphere and troposphere, this tropical forcing is then related to the NAM. This stratospheric pathway links the tropical forcing to the polar atmospheric circulation with a longer delay when compared with the Rossby wave connection through the troposphere.

In summary, MJO-associated tropical convection can impact polar atmospheric circulation in both hemispheres, and in both winter and summer seasons. The strong tropical intraseasonal variability propagates to high latitudes within a week. The modulated atmospheric circulation forces the corresponding changes in polar surface air temperature, oceanic transport, and sea ice in as little as a few days to a week. Evidence shows that polar regions respond more strongly to the MJO in hemispheric winter than summer. The mechanism that can explain the connection between the tropics to polar regions is the Rossby wave train propagation in the troposphere, which is supported by both modeling experiments and data diagnostic analyses. The Rossby wave can also disturb the stratosphere and result in a delayed response in the NAM. Also, the MJO-related circulation anomaly in the tropics can propagate poleward in the global zonal-mean zonal winds. Although the connections are identified as statistically significant, MJO-related variability accounts for only 10%–20% of the polar intraseasonal variability, at least in the ocean.

3. Connections at interannual time scales

ENSO is the primary variability in the climate system at the interannual time scale. Its far-reaching impacts on the lower atmosphere, ocean surface, and cryosphere in the polar regions of both hemispheres have been documented in numerous studies and prior review papers (Trenberth et al. 1998; Turner 2004). Advances over the last decade have provided a better understanding of the connecting mechanisms and of different source areas of the tropical forcing and revealed the interactions between low-latitude-induced variability and high-latitude modes of climate variability.

a. The tropics–southern high latitudes connections through the troposphere

In the Southern Ocean, the largest ENSO impacts occur on the surface temperature and sea ice fields, as coherent, large-scale, out-of-phase anomalies between the Pacific and Atlantic sectors of the Antarctic; Yuan and Martinson (2000) termed this pattern the Antarctic dipole (ADP). The ADP anomalies grow into their maximum values in the austral winter following ENSO, by which time the tropical forcing has diminished (Yuan 2004). Yuan (2004) synthesized the mechanisms that link ENSO events to ADP variability, as illustrated in Fig. 3 for the El Niño condition. These mechanisms include 1) Rossby wave trains emanating from the tropical Pacific, leading to an anomalous high pressure center in the Amundsen Sea (weakened Amundsen Sea low); 2) meridional circulations exhibiting zonal asymmetry because of contrasting SST anomalies in the tropical Pacific and tropical Atlantic: the Hadley cell is strengthened and contracted (weakened) in the South Pacific (South Atlantic); 3) equatorward shifting of the subtropical jet and storm tracks in the South Pacific and poleward shifting of storm tracks in the South Atlantic; and 4) an enhanced (weakened) Ferrel cell in the South Pacific (South Atlantic). All of these mechanisms contribute to more poleward heat transport in the lower atmosphere of the South Pacific, and less poleward heat transport in the South A