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  • View in gallery

    (a) Normalized time series of interannual variations of NAO index in winter (red curve) and spring (blue curve) during 1951–2015. (d) As in (a), but for the NAT SST index. Regression maps of 850 hPa winds (unit: m s−1) in (b) winter and (c) spring onto the corresponding normalized NAO index. Shading in (b) and (c) indicates either direction of the wind anomalies significant at the 95% confidence level. Wind anomalies less than 0.2 m s−1 in both directions are not shown. Regression maps of SST (unit: °C) in (e) winter and (f) spring onto the corresponding normalized NAT SST index. Stippling region in (d) and (f) indicates SST anomalies significant at the 95% confidence level.

  • View in gallery

    (a) Regression of spring SST anomalies (unit: °C) onto the normalized spring NAO index. (b) Regression of spring 850-hPa wind anomalies (unit: m s−1) onto the normalized spring NAT SST index. Stippling regions in (a) indicate SST anomalies significant at the 95% confidence level. Shadings in (b) indicate either direction of the wind anomalies significant at the 95% confidence level. Wind anomalies less than 0.2 m s−1 in both directions are not shown.

  • View in gallery

    (a) Sliding correlation coefficients between interannual variations of the spring NAO index and spring NAT SST index with a 25-yr running window (blue curve). The red curve in (a) is similar to the blue curve, but preceding winter [December–February (DJF)] ENSO signal has been removed from the spring NAO and NAT SST indices by means of linear regression with respect to the DJF Niño-3.4 index prior to calculating the sliding correlations. Horizontal black lines in (a) denote the correlation coefficient significant at the 90% and 95% confidence level, respectively. (b) Sliding mean of spring SST climatology averaged over 35°–55°N and 0°–40°W with a 25-yr running window.

  • View in gallery

    Regression of spring SST anomalies (unit: °C) onto the normalized spring NAO index during (a) 1963–87 and (b) 1988–2012. Stippling regions indicate SST anomalies significant at the 95% confidence level according to the two-tailed Student’s t test.

  • View in gallery

    Regression of spring 1000-hPa winds anomalies (unit: m s−1) onto the normalized spring NAT SST index during (a) 1963–87 and (b) 1988–2012. Shadings in (a),(b) indicate either direction of the wind anomalies that are significantly different from zero at the 95% confidence level. Wind anomalies less than 0.25 m s−1 in both directions are not shown.

  • View in gallery

    Regression of spring SST anomalies (unit: °C) onto the normalized spring NAT SST index during (a) 1963–87 and (b) 1988–2012. Stippling regions indicate SST anomalies significant at the 95% confidence level.

  • View in gallery

    Regression of spring omega anomalies averaged between 600 and 400 hPa (unit: 10−3 Pa s−1) onto the normalized spring NAT index during (a) 1963–87 and (b) 1988–2012. Negative (positive) values correspond to anomalous upward (downward) motion. Stippling regions indicate anomalies significant at the 95% confidence level.

  • View in gallery

    Regression of spring 300-hPa storm-track anomalies (unit: m) onto the normalized spring NAT index during (a) 1963–87 and (b) 1988–2012. Stippling regions indicate anomalies significant at the 95% confidence level.

  • View in gallery

    Climatology of spring 300-hPa storm-track activity (unit: m) during (a) 1963–87 and (b) 1988–2012. (c) Difference in spring climatological 300-hPa storm-track activity between 1988–2012 and 1963–87. Stippling regions in (c) indicate the differences significant at the 95% confidence level. (d) Standardized time series of spring North Atlantic storm-track intensity index (black line). Black dashed line in (d) represents 9-yr sliding mean of the spring storm-track intensity index (black curve). The red and blue horizontal lines indicate the average of storm-track intensity during 1988–2012 and 1963–87, respectively. The green curve in (d) corresponds to the results obtained from the ERA-40 reanalysis.

  • View in gallery

    Regression of spring 300-hPa extended EP flux (unit: m2 s−2) and divergence of the EP flux (unit: m s−2) anomalies onto the normalized spring NAT SST index during (a) 1963–87 and (b) 1988–2012. EP flux anomalies less than 1 m2 s−2 in both directions are not shown. Stippling regions in (a),(b) indicate either direction of the EP flux anomalies significant at the 95% confidence level.

  • View in gallery

    Regression of spring 300-hPa geopotential height tendency (unit: m day−1) onto the normalized spring NAT SST index during (a) 1963–87 and (b) 1988–2012. Stippling regions indicate anomalies that are significantly different from zero at the 95% confidence level.

  • View in gallery

    Difference in climatological mean spring SST (°C) between 1988–2012 and 1963–87. Stippling regions indicate the differences significant at the 95% confidence level.

  • View in gallery

    Regression of 850-hPa winds (unit: m s−1) anomalies onto the normalized spring NAO index during (a) 1963–87 and (b) 1988–2012, respectively. Shadings in (a),(b) indicate either direction of the wind anomalies significant at the 95% confidence level. Wind anomalies less than 0.25 m s−1 in both directions are not shown.

  • View in gallery

    Regression of spring surface net heat flux anomalies (unit: W m−2) onto the normalized spring NAO index during (a) 1963–87 and (b) 1988–2012. Regions with stippling indicate anomalies that are significantly different from zero at the 95% confidence level.

  • View in gallery

    Sliding standard deviation of interannual variation of the spring NAO index with a 25-yr running window.

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Strengthened Connection between Springtime North Atlantic Oscillation and North Atlantic Tripole SST Pattern since the Late 1980s

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  • 1 Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, and College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
  • | 2 School of Earth Sciences, Zhejiang University, Hangzhou, and Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, and College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
  • | 3 Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, and College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
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Abstract

This study reveals a marked enhancement in the relationship between the North Atlantic Oscillation (NAO) and North Atlantic tripole (NAT) sea surface temperature (SST) anomaly pattern during boreal spring since the late 1980s. A comparative analysis is conducted for two periods before and after the late 1980s to understand the reasons for the above interdecadal change. During both periods, SST cooling in the northern tropical Atlantic during the positive phase of the NAT SST pattern results in an anomalous anticyclone over the subtropical western North Atlantic via a Rossby wave–type atmospheric response. The westerly wind anomalies along the north flank of the anomalous anticyclone are accompanied by a marked decrease in synoptic-scale eddies over the midlatitudes as well as cyclonic (anticyclonic) vorticity forcings at the north (south) side. As such, an NAO-like dipole atmospheric anomaly is induced over the North Atlantic, which in turn helps to maintain the NAT SST anomaly via modulating surface heat fluxes. The intensity of the synoptic-scale eddy feedback to mean flow is stronger after than before the late 1980s, which is related to interdecadal increase in the intensity of North Atlantic synoptic-scale eddies. This is followed by a stronger NAO-like atmospheric response to the NAT SST anomaly since the late 1980s. Further analysis shows that changes in the spatial structure of the spring NAO may also partly contribute to changes in the spring NAO–NAT SST connection around the late 1980s. In particular, spring NAO-related atmospheric anomalies are weaker and shift northward before the late 1980s, which reduces the contribution of the NAO to a tripole SST anomaly pattern in the North Atlantic.

© 2020 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: Shangfeng Chen, chenshangfeng@mail.iap.ac.cn

Abstract

This study reveals a marked enhancement in the relationship between the North Atlantic Oscillation (NAO) and North Atlantic tripole (NAT) sea surface temperature (SST) anomaly pattern during boreal spring since the late 1980s. A comparative analysis is conducted for two periods before and after the late 1980s to understand the reasons for the above interdecadal change. During both periods, SST cooling in the northern tropical Atlantic during the positive phase of the NAT SST pattern results in an anomalous anticyclone over the subtropical western North Atlantic via a Rossby wave–type atmospheric response. The westerly wind anomalies along the north flank of the anomalous anticyclone are accompanied by a marked decrease in synoptic-scale eddies over the midlatitudes as well as cyclonic (anticyclonic) vorticity forcings at the north (south) side. As such, an NAO-like dipole atmospheric anomaly is induced over the North Atlantic, which in turn helps to maintain the NAT SST anomaly via modulating surface heat fluxes. The intensity of the synoptic-scale eddy feedback to mean flow is stronger after than before the late 1980s, which is related to interdecadal increase in the intensity of North Atlantic synoptic-scale eddies. This is followed by a stronger NAO-like atmospheric response to the NAT SST anomaly since the late 1980s. Further analysis shows that changes in the spatial structure of the spring NAO may also partly contribute to changes in the spring NAO–NAT SST connection around the late 1980s. In particular, spring NAO-related atmospheric anomalies are weaker and shift northward before the late 1980s, which reduces the contribution of the NAO to a tripole SST anomaly pattern in the North Atlantic.

© 2020 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: Shangfeng Chen, chenshangfeng@mail.iap.ac.cn

1. Introduction

The North Atlantic Oscillation (NAO) is the dominant mode of the atmospheric interannual variability over the North Atlantic (Walker and Bliss 1932; van Loon and Rogers 1978; Hurrell 1995; Hurrell and van Loon 1997). It features an oscillation in sea level pressure (SLP) and geopotential height variations between the subtropics and midlatitudes of the North Atlantic (Walker and Bliss 1932; van Loon and Rogers 1978). The NAO-related atmospheric circulation anomalies display a vertically barotropic structure (van Loon and Rogers 1978; Hurrell and van Loon 1997). The NAO is an important internal dynamical mode of the extratropical circulation (Hurrell and van Loon 1997). Interaction between synoptic-scale eddy and low-frequency mean flow plays an important role in forming and maintaining the NAO-related atmospheric circulation anomalies (Limpasuvan and Hartmann 1999, 2000; Lorenz and Hartmann 2003; Luo et al. 2009). Previous studies suggest that the external forcing, such as the tropical Pacific sea surface temperature (SST) (Brönnimann 2007; Jia et al. 2008; Ineson and Scaife 2009), the North Atlantic SST (Rodwell et al. 1999; Huang et al. 2002; Peng et al. 2003; Pan 2005; Hu and Huang 2006), the Eurasian snow cover (Cohen et al. 2001), the Arctic sea ice change (Jaiser et al. 2012; Nakamura et al. 2015; Chen and Wu 2018), and the Madden–Julian oscillation (MJO, Madden and Julian 1971; Lin et al. 2009) play a role in modulating the NAO variability.

A number of analyses have showed that the NAO can exert substantial influences on concurrent weather and climate over many parts of the Northern Hemisphere, especially Europe, East Asia, and North America (van Loon and Rogers 1978; Wallace and Gutzler 1981; Barnston and Livezey 1987; Hurrell and van Loon 1997; Chang et al. 2001; Sun et al. 2008). For example, pronounced increases (decreases) in surface air temperature tend to occur over many Eurasian regions during the positive (negative) phase of the NAO (Hurrell and van Loon 1997). The extreme heat waves in the summer of 2003 over many European countries, which resulted in substantial economic loss and casualties, were attributed mainly to the unusually positive NAO phase (Beniston 2004; Stott et al. 2004; Ogi et al. 2005). The record-breaking hot summer in 2010 over many parts of the Northern Hemisphere, especially Japan and Russia, were also related to the extremely positive NAO event (Barriopedro et al. 2011; Otomi et al. 2013).

The NAO can also exert substantial delayed impacts on global weather and climate (e.g., Ogi et al. 2003; Gong et al. 2014; Qiao and Feng 2016). Ogi et al. (2003) indicated that the SST anomalies in the North Atlantic and snow cover changes over Eurasia play a crucial role in prolonging the influence of the winter NAO on the following summer atmospheric circulation anomalies over subtropics of the Northern Hemisphere. Otomi et al. (2013) reported that the North Atlantic tripole (NAT) SST anomaly pattern is key in connecting the winter Arctic Oscillation (AO)/NAO to the following summer AO/NAO via case analysis. Qiao and Feng (2016) showed that the NAT SST anomaly is crucial in relaying the impact of the December NAO on the following February East Asian trough. Wu et al. (2009) reported that the spring NAO can exert significant impacts on the following East Asian summer monsoon (EASM) via inducing a NAT SST anomaly pattern that can maintain from spring to following summer. It is noted that the NAT SST pattern is the leading empirical orthogonal function (EOF) mode of SST anomalies in the North Atlantic on the interannual time scale (Wu et al. 2011; Chen and Wu 2017). The NAT SST anomalies can induce significant changes in weather and climate in the regions surrounding the North Atlantic Ocean and in remote regions via triggering atmospheric teleconnection pattern (Cassou et al. 2004, 2005; Gu et al. 2009a,b; Kushnir et al. 2010; Wu et al. 2011; Zuo et al. 2013; Chen et al. 2016). The above studies indicate the close coupled variations of the NAT SST anomalies with the NAO-related atmospheric circulation changes and their roles in prolonging impacts of the NAO.

A recent study of Zuo et al. (2012) revealed a significant interdecadal change in the spring NAO–EASM relation around the late 1970s. They argued that the interdecadal change in the spring NAO–EASM relation was due to change in the spring NAO–NAT SST connection. Specifically, they reported that the spring NAO-related atmospheric circulation anomalies can (not) induce a spring NAT SST anomaly pattern after (before) the late 1970s. However, the detailed characteristics of the spring NAO–NAT SST connection and the reasons of this interdecadal change is still unclear. In this study, we identify a significant interdecadal change in the spring NAO–NAT SST relationship around the late 1980s. We further investigate the plausible reasons of this interdecadal change.

The structure of the paper is as follows. Section 2 describes the data and method employed in this study. Section 3 presents observational evidences for the interdecadal change in the spring NAO–NAT SST relationship. Section 4 discusses the reasons of the interdecadal change in the NAO–NAT SST relationship. Section 5 provides a summary and discussions.

2. Data and methods

a. Data

Monthly mean winds, geopotential height, vertical velocity, surface shortwave and longwave radiation, and sensible and latent heat fluxes are extracted from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis from 1948 to the present (Kalnay et al. 1996; ftp://ftp.cdc.noaa.gov/Datasets/ncep.reanalysis.derived/). This study also employs daily mean winds and geopotential height from the NCEP–NCAR reanalysis to calculate the extended Eliassen–Palm (EP) flux and synoptic-scale eddy activity (also called storm track), respectively, as described below. The atmospheric variables from NCEP–NCAR all have a horizontal resolution of 2.5° × 2.5°, whereas the surface heat fluxes are on 192 × 94 Gaussian grid. The present study also employs the atmospheric data from the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) dataset (Uppala et al. 2005). The ERA-40 dataset is available from September 1957 to August 2002 (Uppala et al. 2005). The monthly mean SST data are derived from the National Oceanic and Atmospheric Administration (NOAA) Extended Reconstructed SST version 3b (ERSSTv3b) dataset from 1854 to the present (Smith et al. 2008; http://www.esrl.noaa.gov/psd/data/gridded/). The ERSSTv3b SST dataset has a horizontal resolution of 2° × 2°.

The monthly NAO index is obtained from the Climate Prediction Center from 1950 to the present (https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml). The CPC defines the NAO index based on rotated principal component analysis following Barnston and Livezey (1987). The spring NAT SST anomaly pattern is defined as the first EOF mode of interannual variation of SST in the North Atlantic region (0°–60°N, 0°–80°W), which displaying same-sign SST anomalies in the tropics and midlatitudes, and SST anomalies with opposite sign in the subtropics of the North Atlantic. Accordingly, the NAT SST index is defined as the principal component time series corresponding to the first EOF mode of the North Atlantic SST anomalies. In this study, the positive phase of the NAT SST index corresponds to positive SST anomalies in the subtropics and negative SST anomalies in the tropics and midlatitudes of the North Atlantic. Interannual variations of SST and all other variables are obtained by subjecting the original anomalous fields to a 2–9-yr Lanczos bandpass filter (Duchon 1979).

Statistical significances of the correlation coefficient and anomalies obtained from linear regression and composite analyses are estimated according to a two-tailed Student’s t test. In addition, the synoptic-scale eddy activity (also called storm track) is defined as the root-mean-square of the 2–8-day Lanczos bandpass filtered geopotential height at a specific pressure level (Chang and Fu 2002; Lee et al. 2012; Chen et al. 2015). In this study, we employ the “Fisher’s r-to-z transformation” method to evaluate the significance of the correlation coefficient difference between two epochs (Fisher 1921). First, a Fisher transform is employed to the two correlation coefficients (i.e., r1 and r2) as follows:
Z1=0.5×ln[(1+r1)/(1r1)],
Z2=0.5×ln[(1+r2)/(1r2)].
Next, the standard parametric test is used to estimate the null hypothesis of the equality of Z1 and Z2. Then, test statistic u = (Z1Z2)/[1/(N1 − 3) + 1/(N2 − 3)]1/2 meets the normal distribution (Fisher 1921). N1 (N2) is the sample size used to calculate r1 (r2).

b. Extended EP flux

The present study uses the Extended EP flux proposed by previous studies (Hoskins et al. 1983; Hendon and Hartmann 1985; Trenberth 1986; Lau 1988) to qualitatively estimate the dynamical interaction between low-frequency mean flow and synoptic-scale eddy activity. Following Trenberth (1986), the equation for the horizontal component of the extended EP flux is expressed as follows:
Eu=[12(υ2¯u2¯)i,uυ¯j]×cosφ,
where φ, u′, and υ′ indicate the latitude, synoptic-scale zonal, and meridional winds, respectively. Synoptic-scale zonal and meridional winds are obtained via applying a bandpass Lanczos filter to the raw daily fields to retain variations on the 2–8-day time scale. The overbar indicates the spring average [March–May (MAM) average].

c. Geopotential height tendency

Feedback of the synoptic-scale eddy to the low-frequency mean low could be quantitatively measured by the feedback term in the geopotential height tendency equation (Lau and Holopainen 1984; Lau 1988; Cai et al. 2007). Following previous studies (Lau 1988; Cai et al. 2007), geopotential height tendency due to the eddy vorticity flux forcing is shown as follows:
F=fg2[(Vζ)¯],
where f and g denote the Coriolis parameter, acceleration of gravity, respectively, and ζ′ and V′ indicate the synoptic-scale relative vorticity and winds, respectively; ζ′ is calculated based on the synoptic-scale winds.

3. Change in the spring NAO–NAT SST connection

Figure 1a displays interannual variations of the normalized winter and spring NAO indices during 1951–2015. The correlation coefficient between the winter and spring NAO indices during 1951–2015 is about 0.05. This indicates that winter NAO is independent of the spring NAO. Figures 1b and 1c show regression maps of the 850-hPa winds in winter and spring onto the corresponding normalized winter and spring NAO indices, respectively. Winter and spring NAO both display a pronounced meridional dipole pattern over the North Atlantic, with an anomalous cyclone over the midlatitudes and an anomalous anticyclone over subtropical North Atlantic (Figs. 1b,c). The spatial pattern of the spring NAO shifts considerably westward compared to that of the winter NAO (Figs. 1b,c). Figure 1d shows interannual variations of the normalized NAT SST indices in winter and spring. The correlation coefficient between the winter and spring NAT SST indices is about 0.37 during 1951–2015. This suggests that the winter tripolar-like SST anomaly pattern in the North Atlantic can maintain to following spring. The spring tripolar SST anomaly pattern in the North Atlantic also shifts slightly westward compared to that in preceding winter, consistent with the difference in the spatial structure of the winter and spring NAO.

Fig. 1.
Fig. 1.

(a) Normalized time series of interannual variations of NAO index in winter (red curve) and spring (blue curve) during 1951–2015. (d) As in (a), but for the NAT SST index. Regression maps of 850 hPa winds (unit: m s−1) in (b) winter and (c) spring onto the corresponding normalized NAO index. Shading in (b) and (c) indicates either direction of the wind anomalies significant at the 95% confidence level. Wind anomalies less than 0.2 m s−1 in both directions are not shown. Regression maps of SST (unit: °C) in (e) winter and (f) spring onto the corresponding normalized NAT SST index. Stippling region in (d) and (f) indicates SST anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

In the following, we concentrate on investigating the connection between the spring NAO and NAT SST. The correlation coefficient between the spring NAO and NAT SST indices reaches 0.38 during 1951–2015, which is statistically significant. The regression pattern of the spring SST anomalies with respect to the spring NAO index shows significant negative anomalies in the tropics and midlatitudes around 50°–60°N and positive anomalies in the subtropical western North Atlantic around 30°–40°N (Fig. 2a), which resemble the first EOF mode of interannual variation of the North Atlantic SST (figure not shown). In addition, the spring NAT SST index-related 850-hPa wind anomalies bear a close resemblance to the positive phase of spring NAO, with a significant cyclonic anomaly over the midlatitudes and a marked anticyclonic anomaly over the subtropics of the North Atlantic (Fig. 2b). The above result indicates a close connection of the spring NAO with the spring NAT SST anomaly pattern, consistent with previous studies (Czaja and Frankignoul 2002; Huang and Shukla 2005; Hu and Huang 2006; Wu et al. 2009; Wu et al. 2011).

Fig. 2.
Fig. 2.

(a) Regression of spring SST anomalies (unit: °C) onto the normalized spring NAO index. (b) Regression of spring 850-hPa wind anomalies (unit: m s−1) onto the normalized spring NAT SST index. Stippling regions in (a) indicate SST anomalies significant at the 95% confidence level. Shadings in (b) indicate either direction of the wind anomalies significant at the 95% confidence level. Wind anomalies less than 0.2 m s−1 in both directions are not shown.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

A careful examination of Fig. 1 indicates that the spring NAO and NAT SST indices display more in-phase variations after the late 1980s, implying a plausible interdecadal change in the NAO–NAT connection. The changing spring NAO–NAT relationship is confirmed in Fig. 3, which shows the 25-yr sliding correlations between the spring NAO index and the spring NAT SST index. The year shown in Fig. 3 represents the central year of the 25-yr running window. It is clear that the spring NAO–NAT SST connection experiences an enhancement around the late 1980s (Fig. 3). Significant correlation between spring NAO and NAT SST can only be observed after the late 1980s. Using other lengths of running windows (such as 21 and 23 years) leads to similar results (not shown). In the following, we select a low correlation epoch and a high correlation epoch before and after the late 1980s, respectively, to examine the reasons of the interdecadal change. Based on the sliding correlation in Fig. 3, year 1975 represents the central year of the 25-yr window (1963–87) when the correlation is the smallest, and year 2000 is the central year of the 25-yr window (1988–2012) when the positive correlation is the largest. As such, the largest contrast of the spring NAO–NAT correlation is observed between 1988–2012 and 1963–87. Notice that the difference in the correlation coefficient between the above two epochs is statistically significant at the 95% confidence level based on the Fisher’s r-to-z transformation.

Fig. 3.
Fig. 3.

(a) Sliding correlation coefficients between interannual variations of the spring NAO index and spring NAT SST index with a 25-yr running window (blue curve). The red curve in (a) is similar to the blue curve, but preceding winter [December–February (DJF)] ENSO signal has been removed from the spring NAO and NAT SST indices by means of linear regression with respect to the DJF Niño-3.4 index prior to calculating the sliding correlations. Horizontal black lines in (a) denote the correlation coefficient significant at the 90% and 95% confidence level, respectively. (b) Sliding mean of spring SST climatology averaged over 35°–55°N and 0°–40°W with a 25-yr running window.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

Spring NAO associated SST anomalies display notable differences in the North Atlantic during 1963–87 and 1963–87. Figure 4 shows regression maps of spring SST anomalies onto the normalized spring NAO index during 1963–87 and 1988–2012. During 1963–87, significant SST anomalies in the North Atlantic are identified only in small patches (Fig. 4a). During 1988–2012, SST anomalies in the North Atlantic are dominated by a significant tripole pattern, with positive anomalies in the subtropics and negative anomalies in the tropics and midlatitudes (Fig. 4b).

Fig. 4.
Fig. 4.

Regression of spring SST anomalies (unit: °C) onto the normalized spring NAO index during (a) 1963–87 and (b) 1988–2012. Stippling regions indicate SST anomalies significant at the 95% confidence level according to the two-tailed Student’s t test.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

The spring NAT SST index-related atmospheric circulation anomalies also show notable differences between the two periods. Figure 5 exhibits spring 1000-hPa wind anomalies regressed upon the normalized spring NAT SST index during 1963–87 and 1988–2012. During the two epochs, atmospheric circulation anomalies over the North Atlantic are featured by a meridional dipole pattern, with an anomalous anticyclone over the subtropics and an anomalous cyclone over the midlatitudes (Figs. 5a,b). In comparison, the anticyclonic and cyclonic anomalies are stronger and more significant during 1988–2012 than during 1963–87. The anomalous cyclone over the midlatitudes around 60°N is weak and insignificant during 1963–87 (Fig. 5b).

Fig. 5.
Fig. 5.

Regression of spring 1000-hPa winds anomalies (unit: m s−1) onto the normalized spring NAT SST index during (a) 1963–87 and (b) 1988–2012. Shadings in (a),(b) indicate either direction of the wind anomalies that are significantly different from zero at the 95% confidence level. Wind anomalies less than 0.25 m s−1 in both directions are not shown.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

Above results collectively suggest that the connection of spring NAO with spring NTA SST anomaly pattern identified in previous studies (Wu et al. 2009; Wu et al. 2011) has experienced a significant interdecadal change around the late 1980s. Specifically, the relationship between the spring NAO and NAT SST is not robust before the late 1980s, but it is strong and significant after the late 1980s.

4. Reasons of the interdecadal change in the spring NAO–NAT SST connection

In this section, we investigate the plausible reasons of the change in the spring NAO–NAT SST connection. We first compare the spring NAT SST-related anomalies of SST and atmospheric circulation between the high and low correlation epochs. Then, we document the difference in the storm-track activity and its effect during the two epochs. After that, we analyze the difference in the spatial structure of the NAO and its implication.

Figures 6a and 6b display regression maps of spring SST anomalies onto the normalized spring NAT SST index during 1963–87 and 1988–2012, respectively. The North Atlantic is dominated by a significant tripole SST anomaly pattern during the two periods, with warm anomalies in the subtropical western North Atlantic, and cold anomalies in the tropics and midlatitudes (Figs. 6a,b). The spatial pattern of the EOF1 of spring SST anomalies in the North Atlantic during 1963–87 (1988–2012) (not shown) is almost identical to that shown in Fig. 6a (Fig. 6b). The pattern correlation coefficient of the EOF1-related spring SST anomalies between the two subperiods is about 0.89 over the domain of 0°–60°N and 0°–60°W. This indicates that the spatial patterns of the EOF1 of North Atlantic SST interannual variations are largely similar during the two periods. However, the negative SST anomalies in the tropical northern Atlantic extend more southwestward to the continent of South America during 1988–2012 compared to those during 1963–87. As indicated by previous study (Peng et al. 2003), this southwestward shift of the negative SST anomalies during the latter period may be more efficient in disturbing the heat sources to induce northeastward dispersing wave train because the climatological precipitation center is near the west coast of Brazil. The southwestward shift of the negative SST anomalies in the tropical Northern Atlantic in the latter period may imply a stronger connection to the NAO.

Fig. 6.
Fig. 6.

Regression of spring SST anomalies (unit: °C) onto the normalized spring NAT SST index during (a) 1963–87 and (b) 1988–2012. Stippling regions indicate SST anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

Notable La Niña–like SST anomalies are also apparent during 1963–87 in simultaneous spring (Fig. 6a) and preceding winter (not shown), indicating a close association of the spring NAT SST with the preceding El Niño–Southern Oscillation (ENSO) in this period. The negative SST anomalies in the tropical central-eastern Pacific are much weaker and less significant during 1988–2012 (Fig. 6b). Previous studies have demonstrated that preceding winter ENSO can modulate subsequent spring SST and atmospheric circulation variations over the North Atlantic via atmospheric teleconnection (Lau and Nath 1996; Alexander et al. 2002; Chiang and Sobel 2002; Huang et al. 2002; Wu and Zhang 2010). In particular, a winter El Niño (La Niña) event can lead to positive (negative) SST anomalies in the tropical northern Atlantic during following spring and summer. The different SST anomalies in the tropical central-eastern Pacific indicate that the impacts of ENSO on the North Atlantic are not the same during the two epochs.

Would the different impacts of ENSO on the North Atlantic SST explain the change in the connection between the spring NAO and spring NAT SST? To answer this question, we remove preceding winter [December–February (DJF)] ENSO signal from the spring NAT SST index and the spring NAO index by means of linear regression with respect to the winter Niño-3.4 index. The Niño-3.4 index is regional mean SST anomalies over 5°S–5°N and 170°–120°W, which is widely used to describe the ENSO interannual variability (e.g., Deser et al. 2012; Chen et al. 2014, 2018). Then, we recalculate the 25-yr running correlations between the spring NAO index and spring NAT SST index. The recalculated running correlation result is presented in Fig. 3 (red curve). The change in the connection between the spring NAO and NAT SST around the late 1980s is still obvious after removal of the preceding winter ENSO signal. We have also examined spring SST and atmospheric circulation anomalies regressed upon the spring NAT SST index after removal of the preceding winter ENSO signal during the two periods. The SST tripole anomaly pattern is still apparent in the North Atlantic during the two periods (not shown).The atmospheric circulation anomalies over the North Atlantic related to the spring NAT SST index are similar before and after removal of the preceding winter ENSO signal (not shown). This implies that the relation of the North Atlantic tripole SST anomaly pattern with the NAO is not affected by ENSO, which is consistent with previous findings (Wu et al. 2011; Chen and Wu 2017). The above results imply that interdecadal change in the spring NAO–NAT SST relationship is not attributed to change in the relationship with preceding ENSO.

Previous studies have demonstrated that NAO-related atmospheric circulation anomalies contribute to a tripole SST anomaly pattern in the North Atlantic via modulating surface net heat fluxes (Wu and Liu 2002; Timlin et al. 2002; Czaja et al. 2003; Wu and Liu 2005; Hu and Huang 2006; Wu and Zhang 2010). The NAT SST anomaly, in turn, could lead to a NAO-like atmospheric circulation anomaly via the eddy–mean flow interaction and associated synoptic-scale eddy feedback (Peng et al. 2003; Pan 2005). Studies suggested that interaction between the low-frequency mean flow and synoptic-scale eddy is a crucial source in forming and maintaining the NAO/AO-related atmospheric circulation (Hartmann and Lo 1998; Limpasuvan and Hartmann 1999, 2000). Via the above processes, the NAO and NAT are closely coupled with each other. In particular, the processes of the impact of the spring NAT SST on the NAO-like meridional atmospheric circulation can be summarized as follows. The negative SST anomalies in the northern tropical Atlantic during positive phase of the spring NAT SST index induce anomalous downward motion anomalies there (Figs. 6 and 7). The related suppression in the convection over the northern tropical Atlantic results in an anomalous anticyclone over the subtropical North Atlantic via a Rossby wave–type atmospheric response, accompanied by significant easterly wind anomalies around 20°–35°N and westerly wind anomalies around 45°–60°N (Fig. 5). As demonstrated by previous studies (Lau 1988; Cai et al. 2007; Chen et al. 2014), westerly (easterly) wind anomalies are immediately accompanied by weakened (strengthened) synoptic-scale eddy activity, which will be confirmed in Fig. 8 later, as well as cyclonic vorticity forcing to its north (south) and anticyclonic vorticity forcing to is south (north). This explains the formation of the anomalous cyclone over the midlatitudes of the North Atlantic in association with positive phase of the spring NAT SST. Hence, via feedback of the synoptic-scale eddy to the low-frequency mean flow described above, a NAO-like atmospheric circulation anomaly is formed over the North Atlantic (Fig. 5), with an anomalous cyclone over the midlatitudes and an anticyclone over the subtropics. The above mentioned interaction between the low-frequency mean flow and synoptic-scale eddy and associated feedback process helps maintaining the NAO-like atmospheric circulation anomalies, consistent with previous findings (Hartmann and Lo 1998; Limpasuvan and Hartmann 1999, 2000).

Fig. 7.
Fig. 7.

Regression of spring omega anomalies averaged between 600 and 400 hPa (unit: 10−3 Pa s−1) onto the normalized spring NAT index during (a) 1963–87 and (b) 1988–2012. Negative (positive) values correspond to anomalous upward (downward) motion. Stippling regions indicate anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

Fig. 8.
Fig. 8.

Regression of spring 300-hPa storm-track anomalies (unit: m) onto the normalized spring NAT index during (a) 1963–87 and (b) 1988–2012. Stippling regions indicate anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

Figure 8 displays 300-hPa storm-track anomalies obtained by regression upon the normalized spring NAT SST index during 1963–87 and 1988–2012, respectively. During 1988–2012, storm-track anomalies related to the spring NAT SST index display a dipole pattern, with significant increase (decrease) in the storm-track activity around 40°–60°N (20°–35°N) (Fig. 8b), which corresponds to significant westerly (easterly) wind anomalies there (Fig. 5b). During 1963–87, spatial distribution of the storm-track anomalies also shows a dipole pattern (Fig. 8a), but with smaller amplitude and confined to a smaller region compared to those during 1988–2012, consistent with the relatively weak zonal wind anomalies (Fig. 5a). In general, the close correspondence of the spatial structures related to the zonal wind and the storm-track anomalies verifies the finding of previous studies (Lau 1988; Cai et al. 2007; Chen et al. 2014).

This analysis indicates that the formation of the cyclonic circulation anomaly over the midlatitudes of the North Atlantic related to the spring NAT SST may be partly due to feedback of the synoptic-scale eddy to the low-frequency mean flow. Figure 5 shows that the anomalous cyclone over the midlatitudes is much weaker and less significant during 1963–87 than that during 1988–2012. This implies that strength of the synoptic-scale eddy feedback to the low-frequency mean flow may be weaker during the earlier period. It has been demonstrated by previous studies (Jin et al. 2006a,b; Jin 2010) that strength of the synoptic-scale eddy feedback to the low-frequency mean flow is closely associated with the intensity of the synoptic-scale eddy activity. In particular, the strength of the synoptic-scale eddy feedback is positively correlated with the intensity of the synoptic-scale eddy activity when the low-frequency mean flow remains the same (Jin 2010). Therefore, it is reasonable to speculate that the intensity of the spring synoptic-scale eddy over the midlatitudes of the North Atlantic is much stronger during 1988–2012 than during 1963–87. We will show evidence in the following to demonstrate that this is indeed the case.

Figures 9a and 9b show the climatology of the spring synoptic-scale eddy activity over the North Atlantic during 1963–87 and 1988–2012, respectively. Distributions of the synoptic-scale eddy activity are similar over the North Atlantic during the two epochs, with a center of action around 40°–50°N. This result is consistent with previous findings (Lee et al. 2012). Figure 9c shows the difference in the spring synoptic-scale eddy activity between 1988–2012 and 1963–87. It is clear that intensity of the spring synoptic-scale eddy over the midlatitudes of the North Atlantic is significantly stronger during 1988–2012 than that during 1963–87. Figure 9d displays the standardized time series of the spring North Atlantic synoptic-scale eddy intensity index. The North Atlantic synoptic-scale eddy intensity index is defined as region-averaged synoptic-scale eddy activity over 35°–65°N and 30°–60°W following Lee et al. (2012). From Fig. 9d, the North Atlantic synoptic-scale eddy activity shows a pronounced interdecadal enhancement around the late 1980s. Interdecadal change in the springtime storm track over the midlatitude North Atlantic can also be detected by the ERA-40 dataset (green line, Fig. 9d). The correlation coefficient between the spring North Atlantic storm-track intensity derived from NCEP–NCAR and ERA-40 during 1958–2002 reaches 0.89, significant at the 99% confidence level. The enhanced synoptic-scale eddy activity may imply a stronger feedback of the synoptic-scale eddy to the low-frequency mean flow.

Fig. 9.
Fig. 9.

Climatology of spring 300-hPa storm-track activity (unit: m) during (a) 1963–87 and (b) 1988–2012. (c) Difference in spring climatological 300-hPa storm-track activity between 1988–2012 and 1963–87. Stippling regions in (c) indicate the differences significant at the 95% confidence level. (d) Standardized time series of spring North Atlantic storm-track intensity index (black line). Black dashed line in (d) represents 9-yr sliding mean of the spring storm-track intensity index (black curve). The red and blue horizontal lines indicate the average of storm-track intensity during 1988–2012 and 1963–87, respectively. The green curve in (d) corresponds to the results obtained from the ERA-40 reanalysis.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

To further confirm the change in the strength of synoptic-scale eddy feedback, we display anomalies of spring 300-hPa extended EP flux and divergence of the EP flux related to the spring NAT SST index during the two periods in Fig. 10, and geopotential height tendency anomalies in Fig. 11. As demonstrated by previous studies (Hoskins et al. 1983; Hendon and Hartmann 1985; Trenberth 1986; Lau 1988; Cai et al. 2007), the dynamical interaction between low-frequency mean flow and synoptic-scale eddy due to barotropic process can be captured by the extended EP flux. More importantly, atmospheric circulation changes induced by the synoptic-scale eddy feedback can be qualitatively estimated by the divergence of the extended EP flux and quantitatively described by the eddy-generated geopotential height tendency (Hendon and Hartmann 1985; Trenberth 1986; Lau 1988). Specifically, convergences (divergences) of the extended EP flux are immediately accompanied by forcing of the anticyclonic (cyclonic) vorticity to the north of the convergences (divergences) areas and cyclonic (anticyclonic) vorticity forcing to the south. It is obvious from Fig. 10 that the EP flux divergence over the North Atlantic around 50°N is much stronger and more significant during 1988–2012 than during 1963–87, confirming a stronger synoptic-scale eddy feedback during the later period. In addition, the EP flux divergences around the 50°N during 1988–2012 are accompanied by significant positive geopotential height tendencies to the south and significant negative geopotential height tendencies to the north (Figs. 10b and 11b). This confirms that the formation of the cyclonic circulation anomaly over the midlatitudes of the North Atlantic in association with the spring NAT SST may be partly attributed to the synoptic-scale eddy feedback. In contrast, the negative geopotential height tendencies over the North Atlantic around 60°N are weak and insignificant during 1963–87 (Fig. 11b). Significant negative geopotential height tendencies over the midlatitudes of the North Atlantic occur over North America and west Europe during 1963–87. The evidence above suggests that the strength of the synoptic-scale eddy feedback to the low-frequency mean flow over the midlatitudes of the North Atlantic is stronger during 1988–2012 compared to that during 1963–87.

Fig. 10.
Fig. 10.

Regression of spring 300-hPa extended EP flux (unit: m2 s−2) and divergence of the EP flux (unit: m s−2) anomalies onto the normalized spring NAT SST index during (a) 1963–87 and (b) 1988–2012. EP flux anomalies less than 1 m2 s−2 in both directions are not shown. Stippling regions in (a),(b) indicate either direction of the EP flux anomalies significant at the 95% confidence level.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

Fig. 11.
Fig. 11.

Regression of spring 300-hPa geopotential height tendency (unit: m day−1) onto the normalized spring NAT SST index during (a) 1963–87 and (b) 1988–2012. Stippling regions indicate anomalies that are significantly different from zero at the 95% confidence level.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

Previous studies (Lau and Nath 1991; Kug and Jin 2009; Chen and Wu 2017) indicate that changes in the strength of the wave–mean flow interaction may be related to the change in the background mean flow. We have calculated differences in spring zonal wind climatology at 200 hPa between 1988–2012 and 1963–87 (not shown). It turns out that the differences are weak and statistically insignificant over the North Atlantic region. This implies that change in the background mean flow may not play a role in the change in the wave–mean flow interaction around the late 1980s.

In summary, climatological springtime synoptic-scale eddy activity over the North Atlantic is much stronger during 1988–2012 than during 1963–87. This leads to a stronger synoptic-scale eddy feedback to low-frequency mean flow and contributes to stronger NAO-like dipole atmospheric circulation anomalies in association with the spring NAT SST. The above difference explains a stronger connection between the spring NAT SST and the spring NAO after the late 1980s.

The analysis above has shown that significant negative SST anomalies in the tropical Northern Atlantic can lead to significant anticyclonic anomaly over the subtropical North Atlantic with different strength. From Fig. 6, magnitudes of the NAT SST anomalies in the tropical northern Atlantic are similar during the two periods. It is noted that response of the atmospheric circulation to the SST anomalies may also depend on the magnitude of the mean SST state. Specifically, under a higher mean SST, the similar northern tropical Atlantic SST anomalies could induce larger atmospheric circulation response over the North Atlantic. Hence, a question is whether spring mean SST in tropical North Atlantic displays notable differences between the two periods. To address this issue, we display the difference in climatological mean spring SST between 1988–2012 and 1963–87 in Fig. 12. The SST differences between the two periods are fairly weak south of the 30°N. Hence, change in the intensity of the anticyclonic circulation anomalies over the subtropical North Atlantic may not be due to the mean SST state change. It is interesting to note that the spring mean SST in the midlatitudes of the North Atlantic is much higher during 1988–2012 than during 1963–87. Previous studies (Hall et al. 1994; Tomita and Kubota 2005; Sampe et al. 2010) have showed that increase in SST may lead to decrease in the static stability in the lower troposphere, which is favorable for the development of the baroclinic wave and may further contribute to enhancement of the North Atlantic storm-track activity. We have also calculated spring SST climatology averaged over 35°–55°N and 0°–40°W, which is shown in Fig. 3b. The change in the spring NAO–NAT SST connection (Fig. 3a) seems to match well with the change in the climatology of spring SST in the midlatitude North Atlantic (Fig. 3b). In particular, spring NAO tends to have a stronger (weaker) connection with the spring NAT SST when spring SST climatology in the midlatitude North Atlantic is higher (lower) (Figs. 3a,b). Change in the spring SST climatology in the midlatitude North Atlantic may be partly related to the anthropogenic climate change. The relative role of the anthropogenic climate change and natural climate variability in the increasing trend of the spring SST climatology in the midlatitude North Atlantic during recent decades remains to be explored.

Fig. 12.
Fig. 12.

Difference in climatological mean spring SST (°C) between 1988–2012 and 1963–87. Stippling regions indicate the differences significant at the 95% confidence level.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

The analyses above mainly focus on the impact of the spring NAT SST on the NAO-like atmospheric circulation anomalies via wave–mean flow interaction as proposed by previous studies (Peng et al. 2003; Pan 2005). It is noted that NAO-related atmospheric circulation anomalies can also lead to a tripole-like SST anomaly pattern in the North Atlantic via changes in surface heat fluxes (Wu and Liu 2002; Timlin et al. 2002; Czaja et al. 2003; Hu and Huang 2006). The surface heat flux anomalies depend upon the distribution of wind anomalies. Hence, change in the association of the spring NAO with NAT SST may also be related to change in the NAO’s structure.

Figure 13 displays regression maps of 850-hPa winds anomalies onto the normalized spring NAO index during 1963–87 and 1988–2012, respectively. The spatial structures of the NAO-related atmospheric circulation anomalies show notable differences between the two periods. During 1963–87, the anticyclonic anomaly over the subtropical North Atlantic is weak and located over the western part (Fig. 13a). Correspondingly, the easterly wind anomalies are weak and mainly located around 30°N. By contrast, during 1988–2012, the significant easterly wind anomalies are large and extend southward to 15°N (Fig. 13b).

Fig. 13.
Fig. 13.

Regression of 850-hPa winds (unit: m s−1) anomalies onto the normalized spring NAO index during (a) 1963–87 and (b) 1988–2012, respectively. Shadings in (a),(b) indicate either direction of the wind anomalies significant at the 95% confidence level. Wind anomalies less than 0.25 m s−1 in both directions are not shown.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

As the NAO’s structure in spring shows pronounced differences, net surface heat fluxes anomalies induced by the NAO also display marked differences between the two periods. Figure 14 displays anomalies of spring surface net heat flux obtained by regression upon the normalized spring NAO index during 1963–87 and 1988–2012, respectively. Surface net heat flux is the sum of surface latent and sensible heat fluxes and surface longwave and shortwave radiation. In this analysis, surface heat fluxes are taken to be positive when their directions are downward, which contribute to SST warming. During 1988–2012, spring NAO associated surface net heat flux anomalies display a tripole pattern over the North Atlantic with significant negative anomalies over the tropics and midlatitudes and positive anomalies over the subtropics of the North Atlantic (Fig. 14b). The negative net heat flux anomalies in the tropics and midlatitudes are to a large part due to the enhanced wind speed as anomalous winds are in line with climatological mean winds in these regions. The correspondence of spatial distribution between SST and surface net heat flux anomalies indicates that the NAO-related atmospheric circulation can in turn maintain the NAT SST anomaly pattern via modulating surface net heat flux. During 1963–87, surface net heat flux anomalies are insignificant south of 40°N, in particular over the eastern part (Fig. 14a), which may be related to the weak atmospheric circulation changes associated with the NAO. In this period, significant negative surface net heat flux anomalies appear around 50°–60°N and 30°–60°W, and positive anomalies are seen over the high latitudes of the North Atlantic. This evidence suggests that the interdecadal change in the spring NAO–NAT SST relationship may also be partly attributed to change in the spring NAO’s structure.

Fig. 14.
Fig. 14.

Regression of spring surface net heat flux anomalies (unit: W m−2) onto the normalized spring NAO index during (a) 1963–87 and (b) 1988–2012. Regions with stippling indicate anomalies that are significantly different from zero at the 95% confidence level.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

5. Conclusions and discussion

Previous studies have demonstrated that interannual variation of the NAO is closely connected with the NAT SST anomaly pattern. The NAO-related atmospheric circulation anomalies contribute to the NAT SST variation via change in surface heat fluxes. The NAT SST changes, in turn, lead to a NAO-like atmospheric anomaly via the wave–mean flow interaction and associated eddy feedback process. This study reveals that interannual relationship of the spring NAO with spring NAT SST has experienced a notable interdecadal change around the late 1980s. Before the late 1980s, connection of the spring NAO with the spring NAT SST anomaly pattern is weak and statistically insignificant. By contrast, the spring NAO-related atmospheric circulation changes have a close relation with the spring NAT SST anomalies after the late 1980s.

Two periods (1963–87 and 1988–2012) before and after the late 1980s are further selected to understand the interdecadal change in the spring NAO–NAT SST connection. During 1988–2012, significant negative SST anomalies in the tropical northern Atlantic associated with the positive phase of the NAT SST induce pronounced downward motion anomalies and a significant anomalous anticyclone over the subtropical western North Atlantic as a Rossby wave–type atmospheric response. Accordingly, significant easterly wind anomalies are seen around 20°–30°N and marked westerly wind anomalies are observed around 45°–60°N over the North Atlantic. The westerly wind anomalies over the midlatitudes are accompanied by significant increase in the synoptic-scale eddy activity as well as a cyclonic vorticity forcing to the north and an anticyclonic forcing to the south. Hence, a NAO-like atmospheric circulation anomaly is induced and maintained via the wave–mean flow interaction and the eddy feedback process. The NAO-related atmospheric circulation changes can in turn result in a tripole-like SST anomaly pattern over the North Atlantic via changing surface net heat flux. Through the above processes, the spring NAO is strongly coupled with the spring NAT SST anomalies during 1988–2012.

During 1963–87, the spring North Atlantic storm-track activities are weak. Accordingly, the strength of the synoptic-scale eddy feedback to the low-frequency mean flow is weak. As a result, NAT SST-induced NAO-like atmospheric circulation anomalies over the North Atlantic are much weaker and less significant during 1963–87 than during 1988–2012. In addition, the spatial structure of the spring NAO displays notable differences during the two periods. The spring NAO-related anticyclonic anomaly over the subtropical North Atlantic is much weaker and shifts northward during 1963–87 than during 1988–2012. As a result, surface net heat flux anomalies induced by the NAO during the earlier period are generally weak south of 30°N. This also contributes to the weak spring NAO–NAT SST connection during 1963–87. The factors responsible for change in the spatial structure of the spring NAO remain to be explored in the future.

Interannual variability of the spring NAO index seems to be much larger after the late 1980s. Figure 15 displays 25-yr moving standard deviations of the spring NAO index. It is interesting to note that the time series of the 25-yr moving standard deviation of the spring NAO index is similar to the change in the spring NAO–NAT SST relation. In particular, spring NAO index tends to have a closer connection with the spring NAT SST index when the standard deviation of the spring NAO index is larger. This suggests that change in the amplitude of the spring NAO index may have a close relation with the change of the spring NAO–NAT SST connection. The reason for the change in the amplitude of the spring NAO index remains to be explored. In addition, it should be mentioned that the period of transition in the spring NAO–NAT SST relation around the late 1980s is different from the phase transitions of the Pacific decadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO) (Mantua et al. 1997; Kerr 2000). This suggests that the PDO and AMO may not have a clear effect on the spring NAO–NAT SST connection change.

Fig. 15.
Fig. 15.

Sliding standard deviation of interannual variation of the spring NAO index with a 25-yr running window.

Citation: Journal of Climate 33, 5; 10.1175/JCLI-D-19-0628.1

This study focuses on the connection of the NAO and NAT SST in simultaneous spring. Previous studies suggested that there exists a connection between the winter NAO and winter NAT SST (Czaja et al. 2003; Otomi et al. 2013; Qiao and Feng 2016). We have examined the winter NAO–NAT SST connection (not shown). The relation of the winter NAO index with the simultaneous winter NAT SST index also experiences a notable enhancement around the late 1980s. The correlation coefficient between the winter NAO index and winter NAT SST index is 0.59 during 1988–2012, significant at the 99% confidence level, but 0.14 only during 1963–87. Interdecadal enhancement of the winter NAO–NAT SST connection around the late 1980s may also be partly due to change in the North Atlantic storm-track intensity (not shown). The detailed factors for the change in the winter NAO–NAT SST need to be further investigated. We note that the change in the winter NAO–NAT SST connection is not totally similar to that in the spring NAO–NAT SST relation. This may be due to differences in the background mean flow between winter and spring as well as differences in the spatial structures of the NAO and NAT SST.

Acknowledgments

We thank three anonymous reviewers for their constructive suggestions, which helped to improve the paper. This study is supported by the National Natural Science Foundation of China Grants (41530425, 41605050, 41775080), and the Young Elite Scientists Sponsorship Program by the China Association for Science and Technology (2016QNRC001).

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