Modulation by the QBO of the Relationship between the NAO and Northeast China Temperature in Late Winter

Jinqing Zuo aLaboratory for Climate Studies, National Climate Centre, China Meteorological Administration, Beijing, China
bCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, China

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Fei Xie cSchool of Systems Science, Beijing Normal University, Beijing, China

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Liuni Yang dBeijing Emergency Management Center, Beijing, China

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Chenghu Sun eState Key Laboratory of Severe Weather and Institute of Climate System, Chinese Academy of Meteorological Sciences, Beijing, China

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Lin Wang fCenter for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Ruhua Zhang gGuy Carpenter Asia-Pacific Climate Impact Center, School of Energy and Environment, City University of Hong Kong, Hong Kong, China

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Abstract

The North Atlantic Oscillation (NAO) generally has an in-phase relationship with surface air temperature (SAT) anomalies over Northeast China in late winter. The present study shows that such an NAO–SAT relationship becomes stronger during easterly phases of the quasi-biennial oscillation (QBO), but is relatively weak during westerly phases. Observational evidence reveals that the modulation effect of the QBO on the NAO–SAT relationship over Northeast China is attributable to QBO-induced changes in the spatial structure of the NAO and associated stratosphere–troposphere coupling. During easterly QBO phases, the NAO has a strong connection with the Northern Hemisphere stratospheric polar vortex, facilitating a hemisphere-wide structure of the NAO and thus a downstream extension of NAO signal from the Euro–Atlantic sector toward Northeast Asia. During westerly QBO phases, however, the NAO has a limited connection with the stratospheric polar vortex. In this case, the NAO features a classically regional mode, with the signal in the SAT field mainly confined to the Euro-Atlantic sector. By examining historical simulations from six climate models participating in CMIP6 and including stratospheric processes, it is found that none of these models captures a significant difference in the spatial structure of the NAO and its connection with the stratospheric polar vortex between the easterly and westerly QBO phases in late winter. A key reason may be related to the poor performance of the models in simulating the Holton–Tan effect, which is critical for linking the QBO and NAO.

Significance Statement

The QBO is the dominant mode of equatorial stratospheric variability and important for seasonal forecasting. This study aims to better understand the surface influence of the QBO by examining the relationship between the NAO and temperature anomalies over China according to the phases of the QBO during boreal winter. Our results highlight the importance of the QBO in modulating the spatial structure and thus climate impact of the NAO via stratosphere–troposphere coupling in observations, while state-of-the-art climate models perform poorly in simulating the QBO-related stratosphere–troposphere coupling and thus the QBO–NAO connection. These findings have important implications for seasonal prediction and model development in the future.

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

Corresponding author: Fei Xie, xiefei@bnu.edu.cn

Abstract

The North Atlantic Oscillation (NAO) generally has an in-phase relationship with surface air temperature (SAT) anomalies over Northeast China in late winter. The present study shows that such an NAO–SAT relationship becomes stronger during easterly phases of the quasi-biennial oscillation (QBO), but is relatively weak during westerly phases. Observational evidence reveals that the modulation effect of the QBO on the NAO–SAT relationship over Northeast China is attributable to QBO-induced changes in the spatial structure of the NAO and associated stratosphere–troposphere coupling. During easterly QBO phases, the NAO has a strong connection with the Northern Hemisphere stratospheric polar vortex, facilitating a hemisphere-wide structure of the NAO and thus a downstream extension of NAO signal from the Euro–Atlantic sector toward Northeast Asia. During westerly QBO phases, however, the NAO has a limited connection with the stratospheric polar vortex. In this case, the NAO features a classically regional mode, with the signal in the SAT field mainly confined to the Euro-Atlantic sector. By examining historical simulations from six climate models participating in CMIP6 and including stratospheric processes, it is found that none of these models captures a significant difference in the spatial structure of the NAO and its connection with the stratospheric polar vortex between the easterly and westerly QBO phases in late winter. A key reason may be related to the poor performance of the models in simulating the Holton–Tan effect, which is critical for linking the QBO and NAO.

Significance Statement

The QBO is the dominant mode of equatorial stratospheric variability and important for seasonal forecasting. This study aims to better understand the surface influence of the QBO by examining the relationship between the NAO and temperature anomalies over China according to the phases of the QBO during boreal winter. Our results highlight the importance of the QBO in modulating the spatial structure and thus climate impact of the NAO via stratosphere–troposphere coupling in observations, while state-of-the-art climate models perform poorly in simulating the QBO-related stratosphere–troposphere coupling and thus the QBO–NAO connection. These findings have important implications for seasonal prediction and model development in the future.

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

Corresponding author: Fei Xie, xiefei@bnu.edu.cn

1. Introduction

Northeast China is located in the east of Eurasia, and it is an important crop-growing and heavy-industry region in China. Extreme cold events have profound economic and social impacts in Northeast China during boreal winter (Wang and Lu 2017; Dai et al. 2018; Zhuang et al. 2018). Thus, a better understanding of the Northeast China winter temperature variability would have great benefits for society and the economy, and in particular for events such as the Harbin International Ice and Snow Festival that is held in mid- to late winter.

During boreal winter, northwesterly winds associated with the East Asian winter monsoon prevail over Northeast China, providing favorable conditions for the southward intrusion of mid–high-latitude cold air and thus frequent occurrence of cold events over this region. Hence, variations in the Northeast China surface temperature are closely related to the dominant modes of atmospheric low-frequency variability in the extratropical Northern Hemisphere during boreal winter (Chen et al. 2005, Chen et al. 2013a; He et al. 2017). Among them, the impact of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) and associated quasi-stationary planetary wave activity has been widely explored (Wu and Huang 1999; Gong et al. 2001; Wu and Wang 2002; Chen et al. 2005, Chen et al. 2013, Chen et al. 2013b; Kang et al. 2009; Wang et al. 2009; Wang and Chen 2010; Zhuang et al. 2018). The NAO is generally considered to be the regional manifestation of the AO, and their spatial patterns bear the highest resemblance in late winter (Watanabe 2004). Previous studies have suggested that the negative phase of the AO and NAO tends to coincide with a strong East Asian winter monsoon, leading to frequent outbreaks of cold air and thus cold conditions in Northeast China, and vice versa (Wu and Huang 1999; Gong et al. 2001; Wu and Wang 2002; He et al. 2017; see also references therein).

The influence of the NAO on surface temperature anomalies is sensitive to its spatial structure (Watanabe 2004; Gong et al. 2018), which might be modulated by other factors. Quadrelli and Wallace (2002) reported that the NAO features a wider spatial structure and thus a stronger impact on the surface temperature over much of Siberia during warm winters of the ENSO cycle than during cold winters. During boreal winter, variation in the tropospheric and near-surface NAO is closely related to that of the Northern Hemisphere stratospheric polar vortex (Gray et al. 2018; Gong et al. 2019; Nie et al. 2019, and references therein). Thus, changes in the stratospheric polar vortex and associated stratosphere–troposphere coupling processes provide a new perspective on the mechanism for the modulation of the spatial structure and climate impact of the NAO (Kodera et al. 1999; Black 2002; Chen and Zhou 2012; Gong et al. 2019). In particular, Kodera et al. (1999) revealed that a stronger connection between the NAO and the Northern Hemisphere stratospheric polar vortex coincides with a more annular-like structure and thus a wider surface impact of the NAO during boreal winter. Kodera (2002, 2003) found that the zonal wind anomalies produced by solar activity in the stratopause can propagate downward into the troposphere through interaction with planetary waves and hence result in a hemisphere-wide structure of the NAO during solar maximum winters of the 11-yr solar cycle, whereas this is not true during solar minimum winters. These results imply that the spatial structure of the NAO might be modulated by the intensity of the stratosphere–troposphere coupling in the extratropical Northern Hemisphere during boreal winter.

The quasi-biennial oscillation (QBO) of the stratosphere, an oscillation of the equatorial stratospheric zonal winds between easterlies and westerlies with an average period of 28 months (Baldwin et al. 2001), is one of the most important factors affecting changes in the Northern Hemisphere stratospheric polar vortex (J. Zhang et al. 2019; see also references therein) and thus variations in the northern surface climate during boreal winter (Anstey and Shepherd 2014; Gray et al. 2018; Rao et al. 2020a). Compared to the westerly QBO phase, the easterly QBO phase tends to induce a weaker and thus more disturbed Northern Hemisphere stratospheric polar vortex during boreal winter (referred to as the Holton–Tan effect; Holton and Tan 1980), facilitating a negative phase of the NAO in the troposphere and near-surface (Baldwin and Dunkerton 2001; Baldwin et al. 2003; Scaife et al. 2005, 2016; Marshall and Scaife 2009). Although it is widely accepted that the QBO has an impact on the NAO and surface climate during boreal winter, whether the former can modulate the spatial structure of the latter and thus its relationship with the surface climate remains unclear. Moreover, Chen and Li (2007) revealed that the influences of the stationary planetary wave activity on the East Asian winter climate are different during the easterly and westerly phases of the QBO. Their results may imply a modulation effect of the QBO on the NAO due to the close relationship between the NAO and stationary planetary wave activity during boreal winter (Chen et al. 2003, 2005). In this study, we re-examine the surface influence of the QBO and find that the QBO can significantly modulate the spatial structure of the NAO and hence its relationship with surface temperature anomalies in Northeast China in late winter (i.e., February), when the impact of the NAO on the surface temperature anomalies is visible there (Watanabe 2004).

The remainder of this manuscript is organized as follows. Section 2 describes the datasets and methods used in this study. Section 3 presents the relationship between the NAO and surface air temperature (SAT) anomalies in China according to the phases of the QBO and explores the possible mechanism responsible for the QBO’s modulation of the NAO–SAT relationship in Northeast China in late winter. Section 4 examines the representation of the QBO’s modulation of the spatial structure of the NAO and its connection with the Northern Hemisphere stratospheric polar vortex in climate models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Section 5 gives a summary and some further discussion.

2. Data and methods

The monthly ERA5 dataset (Hersbach et al. 2020) from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to examine the QBO’s modulation of the atmospheric circulation and NAO–SAT relationship in observations. The data have a horizontal resolution of 2.5° latitude × 2.5° longitude and are available from 1979 to the present. In addition, we utilize observations of monthly SAT provided by the National Climate Center of China Meteorological Administration since 1961. These data, constructed from in situ temperature observations at more than 2400 stations in China by using a thin plate spline interpolation method (Xu et al. 2020), have a horizontal resolution of 0.5° latitude × 0.5° longitude. Both the observations and reanalysis are referred to as observation in this study.

Historical simulations of the CMIP6 models are used to evaluate model performance in simulating the QBO–NAO–SAT connection. The historical simulations branch from piControl and are forced by observed climate forcing, including time-evolving atmospheric compositions, solar variability, volcanic aerosols, and land cover/land use during the period of 1850–2014 (Eyring et al. 2016). Only one realization is used for each model in the present study. More details of the CMIP6 models and experiments can be found on the CMIP website (https://pcmdi.llnl.gov/CMIP6/).

Following previous studies (Kim et al. 2020; Richter et al. 2020), a model is considered to simulate the QBO if zonal-mean zonal wind averaged over 5S°–5°N between 10 and 100 hPa exhibits alternating westerlies and easterlies with a period of approximately 28 months that is similar to the observed one. Note that the criteria used in this study are slightly different from those used in Kim et al. (2020) and Richter et al. (2020); in particular, a criterion regarding the period rather than the standard deviation of the zonal-mean zonal wind is used here. According to the criteria used in this study, there are 6 out of the 46 CMIP6 models generating the QBO internally (see Figs. S1 and S2 in the online supplemental material). These six models (ACCESS-CM2, CESM2-WACCM-FV2, HadGEM3-GC31-LL, HadGEM3-GC31-MM, INM-CM5-0, and KACE-1-0-G) are further analyzed in the present study. All of these models have at least 70 vertical levels and have a model top higher than ∼85 km, except that INM-CM5-0 has a relatively lower model top at the 0.2-hPa pressure level (Table 1). All the model outputs were regridded to a 2.5° × 2.5° regular grid prior to our analysis.

Table 1

Institute and configurations of the CMIP6 models used in the present study.

Table 1

The QBO index is calculated as the zonal-mean zonal wind at 50 hPa averaged over 5S°–5°N for both the observations and simulations (Yoo and Son 2016; Son et al. 2017; Elsbury et al. 2021a). We define the westerly QBO phase when the values of the monthly QBO index in February and the previous January and December are positive and larger than 0.5 standard deviations (σ ≈ 10 m s−1 in the observation) of the winter-mean index, and the easterly QBO phase when the values of the monthly QBO index in February and the previous January and December are negative and less than −0.5 standard deviation of the winter-mean index. The standard deviation of the winter-mean QBO index ranges from 8.6 to 10.8 m s−1 in the simulations. According to these criteria, there are 12 (17) easterly (westerly) QBO years in the observations, and at least 9 (10) easterly (westerly) QBO years for each model (Table S1 in the online supplemental material). To examine sensitivity of the simulated results to QBO indexing, the QBO index at 30 as well as 10 hPa is analyzed and the results are qualitatively the same for each model (Figs. S3 and S4).

The observed monthly NAO index is obtained from the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) and constructed using a rotated principal component analysis (Barnston and Livezey 1987) with monthly mean standardized 500-hPa height anomalies over the extratropical Northern Hemisphere (20°–90°N). The simulated NAO index is calculated as the first principal component of area-weighted monthly mean sea level pressure anomalies over the North Atlantic sector (80°W–40°E, 20°–90°N) for the individual models (Hurrell et al. 2003).

The analysis period is 1979–2020 for the observations and 1973–2014 for the simulations, both of which cover 42 years. Linear trends in the SAT time series are removed prior to the analysis. Statistical significance of the correlation/regression coefficient and composite anomalies is determined by a two-tailed Student’s t test, while the difference between two correlation coefficients is assessed using the Fisher z transformation (Fisher 1921).

3. Modulation by the QBO of the NAO–SAT relationship in Northeast China

Figure 1a displays the correlations between the NAO index and SAT anomalies over China in February for the entire period of 1979–2020. It is shown that the NAO index has a significant and out-of-phase relationship with the SAT anomalies in south central China, whereas a rather weak in-phase relationship is observed in Northeast China (Fig. 1a). This is consistent with the results of previous studies (e.g., Zuo et al. 2016).

Fig. 1.
Fig. 1.

(a) Correlation coefficients between the NAO index and surface air temperature anomalies derived from observations in February 1979–2020. Dots indicate significance at the 95% confidence level. (b)–(d) As in (a), but for the easterly and westerly QBO years in (b) and (c) and their differences (former minus latter) in (d). (e),(f) Scatterplots between the NAO index and normalized surface air temperature anomalies regionally averaged over Northeast China [42°–53°N, 116°–134°E; box in (b)] for the easterly and westerly QBO years, respectively. Solid lines denote linear fitting of the data, R the correlation coefficients, and N the sample size. The statistical significance is determined by a two-tailed Student’s t test in (a)–(c) and the Fisher z transformation in (d).

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

To investigate the modulation effect of the QBO, we further calculate the correlations between the NAO index and SAT anomalies for the easterly and westerly QBO years, respectively (see Figs. 1b,c). It is shown that the in-phase relationship between the NAO and SAT anomalies in Northeast China becomes stronger and more significant for the easterly QBO years (Fig. 1b), but it becomes very weak and almost negligible for the westerly QBO years (Fig. 1c).

The differences in the NAO–SAT correlations between the easterly and westerly QBO years in February are also examined. It is found that the difference is statistically significant at the 95% confidence level in Northeast China (Fig. 1d). Moreover, the NAO index has a correlation coefficient of 0.74 (p < 0.01) with the regionally averaged SAT anomalies over Northeast China (box in Fig. 1b; 42°–53°N, 116°–134°E) for the easterly QBO years (Fig. 1e), but only −0.04 for the westerly QBO years (Fig. 1f). The difference between these two correlation coefficients is statistically significant at the 95% confidence level.

Additionally, a field significance test using the minimum local p value as the global test statistic, which is also known as the Walker test (Wilks 2006), is conducted on the difference in the NAO–SAT correlations across all of China. Instead of accounting for the number of individual points yielding significant results, the Walker test considers the spatial distribution of the field as a whole. The results suggest a field significance at the 95% global confidence level for the difference in the NAO–SAT correlations between the easterly and westerly QBO years. Note here that the effective number of degrees of freedom of the anomalous SAT field that is used as a parameter in determining the critical p value for the Walker test is estimated following Bretherton et al. (1999). This result confirms that the relationship between the NAO and Northeast China SAT anomalies for the easterly QBO years is distinctly different from that for the westerly QBO years in February.

To further confirm the modulation effect of the QBO, a bootstrapping analysis with 1000 resamples and a two-sided p value is conducted. A random set of 12 (17) years resampling with replacement is used for the easterly (westerly) QBO years. According to the bootstrapping analysis, the correlations between the NAO index and SAT anomalies are significant at the 95% confidence level in northern China for the easterly QBO years (Fig. S5a), particularly in the region where the differences between the easterly and westerly QBO years are larger. Moreover, the correlation coefficient between the NAO index and regionally averaged SAT anomalies over Northeast China for the easterly QBO years is significant at the 95% confidence level according to the bootstrapping analysis. Therefore, the results from the bootstrapping analysis support the observed modulation effect of the QBO on the NAO–SAT relationship in Northeast China in February.

Therefore, the observational evidence suggests that the QBO can significantly modulate the relationship between the NAO and Northeast China SAT anomalies in February; that is, the easterly QBO phase facilitates a closer in-phase relationship between the NAO and Northeast China SAT anomalies when compared to the westerly QBO phase. Although a significant correlation is observed between the NAO and SAT anomalies in south central China for the entire period of 1979–2020, the correlation coefficient is relatively weak for both the easterly and westerly QBO years in February. This suggests a limited effect of the QBO in modulating the NAO–SAT relationship in south central China. We next mainly focus on the mechanism responsible for the modulation by the QBO of the relationship between the NAO and Northeast China SAT anomalies in February.

Figure 2 displays the regressions of the 500-hPa geopotential height and 850-hPa wind anomalies onto the NAO index for the easterly and westerly QBO years in February. For the easterly QBO years, the positive phase of the NAO is concurrent with positive geopotential height anomalies over Northeast Asia and opposite anomalies over northwestern Siberia at 500 hPa (Fig. 2a), leading to a weakened East Asian coastal trough in the middle troposphere and weakened northerlies in the lower troposphere (Fig. 2c). Consequently, warm SAT anomalies corresponding to the positive NAO phase are observed from central Siberia to Northeast Asia (Fig. 2c). The opposite situation is observed for the negative NAO phase under the easterly QBO conditions. For the westerly QBO years, however, NAO-associated changes in the 500-hPa geopotential height and 850-hPa horizontal wind are relatively weak over East Asia (Fig. 2b), coinciding with comparatively weak SAT anomalies over this region (Fig. 2d). This result indicates that the NAO-associated atmospheric circulation anomalies feature obviously different spatial patterns over East Asia between the easterly and westerly QBO years, which therefore leads to different impacts of the NAO on the Northeast Asian SAT anomalies between these two QBO conditions in February.

Fig. 2.
Fig. 2.

Regressions of the 500-hPa geopotential height anomalies (shading; gpm) onto the NAO index for the (a) easterly and (b) westerly QBO years in February 1979–2020. (c),(d) As in (a) and (b), but for the 850-hPa wind anomalies (vectors; m s−1) and surface air temperature anomalies (shading; °C). The geopotential height, horizontal wind, and air temperature are derived from ERA5. Dots indicate statistical significance at the 95% confidence level, and contours denote the climatological mean of the 500-hPa geopotential height (gpm). Only the vectors with statistical significance at the 95% confidence level are shown.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

The spatial structure of the NAO in the near-surface layer and the middle troposphere over the extratropical Northern Hemisphere for the easterly and westerly QBO years in February is further examined (Fig. 3). For the easterly QBO years, the northern activity center of the NAO in the sea level pressure anomaly field extends from the North Atlantic sector to western Siberia (Fig. 3a), coinciding with alternating positive and negative 500-hPa geopotential height anomalies over the Eurasian mid- to high latitudes (Fig. 3d) that feature a spatial structure similar to the Eurasian teleconnection pattern (Liu et al. 2014). Consequently, positive (negative) geopotential height anomalies corresponding to the positive (negative) phase of the NAO are observed over Northeast Asia, leading to warm (cold) SAT anomalies over this region (Fig. 2c). For the westerly QBO years, however, the northern activity center of the NAO in the sea level pressure anomaly field is mainly confined to the North Atlantic sector (Fig. 3b). In this case, there is no significant wave train extending downward from western Europe into East Asia in the 500-hPa geopotential height anomaly field (Fig. 3e), leading to relatively weak changes in the atmospheric circulation and thus SAT over East Asia (Fig. 2d).

Fig. 3.
Fig. 3.

Regressions of the sea level pressure anomalies (hPa) onto the NAO index for the (a) easterly and (b) westerly QBO years, and (c) their difference (former minus latter) derived from ERA5 in February 1979–2020. (d)–(f) As in (a)–(c), but for the 500-hPa geopotential height anomalies (gpm). Dots indicate statistical significance at the 95% confidence level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

A comparison of Figs. 3a and 3b and of Figs. 3d and 3e indicates that the NAO pattern for the easterly QBO years appears to exhibit a more hemisphere-wide structure in the near-surface layer and middle troposphere when compared to that for the westerly QBO years in February. Moreover, differences in the NAO-associated atmospheric circulation anomalies between the easterly and westerly QBO years are statistically significant over the Eurasian mid- to high latitudes (Figs. 3c,f), confirming a downward extension of the NAO signal from the North Atlantic toward East Asia for the easterly QBO years. In contrast, the NAO signal is mainly confined to the Euro-Atlantic sector for the westerly QBO years. Moreover, the Walker test is conducted on Fig. 3f and the result indicates a field significance at the 95% global confidence level, which therefore supports the significant difference in the NAO-associated atmospheric circulation anomalies between the easterly and westerly QBO years. It should be noted that the NAO tends to coincide with an action center over the North Pacific in the near-surface layer and the middle troposphere for the westerly QBO years (Figs. 3b,e), but differences in the NAO-associated atmospheric circulation anomalies between the easterly and westerly QBO years are nonsignificant over the North Pacific (Figs. 3c,f).

Previous studies have demonstrated that variation in the stratospheric polar vortex acts as a bridge for the impact of the QBO on the northern surface climate during boreal winter (Anstey and Shepherd 2014; Gray et al. 2018). Therefore, the connection of the NAO with the stratospheric polar vortex and the associated stratosphere–troposphere coupling for the easterly and westerly QBO years in February are investigated (see Fig. 4). For the easterly QBO years, the positive phase of the NAO is concurrent with significant and positive zonal wind anomalies over the entire subpolar region at 50 hPa (Fig. 4a), suggesting a strong in-phase relationship between the NAO and stratospheric polar vortex variability. Consistently, positive (negative) zonal wind anomalies occur over the subpolar (subtropical) region at 200 hPa (Fig. 4c), leading to a near annular structure of the NAO. In fact, it is shown in Fig. 4e that the NAO-associated zonal-mean zonal wind anomalies can clearly be observed in the mid- to high latitudes throughout the troposphere and lower stratosphere for the easterly QBO years. For the westerly QBO years, however, the NAO-associated zonal wind anomalies are rather weak and mainly confined to the Euro-Atlantic sector at both 50 and 200 hPa (Figs. 4b,d). Consequently, the NAO-associated zonal-mean zonal wind anomalies are relatively weak in the high latitudes of the troposphere and lower stratosphere for the westerly QBO years (Fig. 4f).

Fig. 4.
Fig. 4.

Regressions of the zonal wind anomalies (m s−1) at (a),(b) 50 and (c),(d) 200 hPa onto the NAO index for the easterly QBO years in (a) and (c) and the westerly QBO years in (b) and (d) derived from ERA5 in February 1979–2020. (e),(f) As in (a) and (b), but for the zonal-mean zonal wind anomalies. Dots indicate statistical significance at the 95% confidence level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

Since the NAO signal in the zonal wind field is mainly confined to the Euro-Atlantic sector for the westerly QBO years (Figs. 4b,d), NAO-associated zonal-mean zonal wind anomalies for the North Atlantic sector (90°W–0°), the Europe–western Asia sector (0°–90°E), the East Asia–western Pacific sector (90°E–180°), and the eastern Pacific–North America sector (180°–90°W) are further calculated for the easterly and westerly QBO years (Fig. 5). For the easterly QBO years, positive zonal-mean zonal wind anomalies corresponding to the positive NAO phase are observed in the subpolar region throughout the troposphere and lower stratosphere for all subsectors except the eastern Pacific–North America sector (Figs. 5a–d). The different behavior of the zonal-mean zonal wind anomalies over the eastern Pacific–North America sector may be related to the competing role of the QBO and stratospheric polar vortex in altering the North Pacific tropospheric jet (Elsbury et al. 2021a). For the westerly QBO years, however, considerable zonal-mean zonal wind anomalies are only observed in the North Atlantic sector in the mid- to high latitudes (Figs. 5e–h). Moreover, a comparison of Figs. 5a and 5e indicates that the positive zonal-mean zonal wind anomalies corresponding to the positive NAO phase extend poleward in the lower stratosphere for the easterly QBO years. In contrast, they are weaker and mainly confined to 40°–60°N for the westerly QBO years. This result supports the finding that the connection of the NAO with the stratospheric polar vortex is stronger for the easterly QBO years than that for the westerly QBO years in February.

Fig. 5.
Fig. 5.

Regressions of the zonal-mean zonal wind anomalies (m s−1) averaged over (a),(e) 90°W–0°, (b),(f) 0°–90°E, (c),(g) 90°E–180°, and (d),(h) 180°–270°E onto the NAO index for the (top) easterly and (bottom) westerly QBO years derived from ERA5 in February 1979–2020. Dots indicate statistical significance at the 95% confidence level. The y axis is pressure (hPa).

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

In short, the NAO-associated stratosphere–troposphere coupling is strong and significant for the easterly QBO years in February, which is concurrent with a near hemisphere-wide structure of the NAO that quite closely resembles the AO pattern and thus a wide impact of the NAO on the surface climate. However, the NAO-associated stratosphere–troposphere coupling is limited in the westerly QBO years. In this case, the NAO features a regional mode that is mainly confined to the Euro-Atlantic sector in the troposphere. This result is consistent with that of Kodera et al. (1999), who revealed that a stronger NAO–stratosphere connection coincides with a more annular-like structure and thus a wider surface impact of the NAO during boreal winter. Also, our finding is in line with that of Chen and Li (2007), who reported that SAT anomalies in Northeast China are closely correlated with the intensity of the tropospheric stationary planetary wave activity during easterly QBO winters rather than during westerly QBO winters.

4. Representation of the QBO modulation effect in CMIP6 models

To examine the ability of state-of-the-art climate models in simulating the QBO’s modulation of the NAO–SAT relationship over East Asia, the SAT and atmospheric circulation anomalies associated with the NAO under different QBO conditions for the individual CMIP6 historical simulations in February are investigated (Fig. 6; see also Fig. S6). The common feature that emerges from Fig. 6 is that the spatial pattern of the NAO-associated SAT anomalies is quite similar between the easterly and westerly QBO conditions for all models; that is, cold SAT anomalies are observed in Northeast Asia for all cases, and warm anomalies occur in Southwest Asia for most cases. This indicates that the models tend to simulate an out-of-phase relationship between the NAO and SAT anomalies in Northeast Asia, which is in contrast to the observed in-phase relationship there (Fig. 2). Consistently, the spatial pattern of the NAO-associated 500-hPa geopotential height anomalies over East Asia is similar between the easterly and westerly QBO conditions in the simulations (Fig. S6); that is, in the positive NAO phase under both QBO conditions, the East Asian coastal trough in the middle troposphere tends to be weakened and coincides with negative geopotential height anomalies to the north, leading to stronger westerly winds and thus cold SAT anomalies over Northeast Asia. Note that for HadGEM3-GC31-LL under the westerly QBO conditions, the cold SAT anomalies in Northeast Asia (Fig. 6f) appear to result from the positive geopotential height anomalies over the northern Siberian plain (Fig. S6f). Nevertheless, these results suggest a limited effect of the QBO in modulating the NAO–SAT relationship over Northeast Asia in the CMIP6 historical simulations in February, which is obviously different from the observational result as shown in Fig. 2.

Fig. 6.
Fig. 6.

Regressions of surface air temperature anomalies (°C) onto the NAO index for the easterly and westerly QBO years derived from individual model simulations in February. Dots indicate statistical significance at the 95% confidence level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

To possibly explain the difference between the simulations and observations, the spatial structure of the simulated NAO and its connection with the simulated stratospheric polar vortex are further examined. Figure 7 displays the regressed 200-hPa zonal wind anomalies onto the NAO index for the easterly and westerly QBO years derived from individual model simulations in February. It is found that the NAO-associated zonal wind anomalies at 200 hPa feature a near annular structure during both the easterly and westerly QBO phases for the individual model simulations (especially for INM-CM5-0 and KACE-1-0-G) in February. Due to the equivalent barotropic structure of the NAO (Thompson et al. 2003), the simulated 500-hPa geopotential height anomalies associated with the NAO also exhibit a near annular structure for both the easterly and westerly QBO years in February (figures not shown). This indicates that all the models tend to simulate a similar spatial pattern of the NAO between the easterly and westerly QBO phases, leading to a similar influence of the NAO on the SAT anomalies over Northeast Asia between these two QBO phases in the simulations.

Fig. 7.
Fig. 7.

Regressions of the 200-hPa zonal wind anomalies (m s−1) onto the NAO index for the easterly and westerly QBO years derived from individual model simulations in February. Dots indicate statistical significance at the 95% confidence level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

Similar to those at 200 hPa, the simulated zonal wind anomalies associated with the NAO also feature an annular-like structure at 50 hPa for both the easterly and westerly QBO years in all the models in February (Fig. 8). In particular, the positive phase of the NAO tends to coincide with an intensified westerly wind at 50 hPa over the subpolar region in all the models. This suggests a strong in-phase relationship between the simulated NAO and stratospheric polar vortex during both the easterly and westerly QBO phases, which is different from the observational result that an NAO–stratosphere connection is only visible during the easterly QBO phases and not in the westerly QBO phases in February. Therefore, the strong connection between the NAO and stratospheric polar vortex is concurrent with a hemisphere-wide structure and thus wide impact of the NAO during both the easterly and westerly QBO phases in the models.

Fig. 8.
Fig. 8.

As in Fig. 7, but for the 50-hPa zonal wind anomalies.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

Due to the important role of the Holton–Tan effect in linking the QBO to the stratospheric polar vortex and thus the NAO, composites of the zonal-mean zonal wind anomalies for the easterly and westerly QBO phases and their differences (former minus latter) in the observations and individual model simulations in February are examined (Fig. 9). The results indicate that the observed subpolar westerly wind in the lower stratosphere during the easterly QBO phases tends to be weaker than during the westerly QBO phases (Figs. 9a–c), consistent with the Holton–Tan effect revealed in earlier studies (Holton and Tan 1980; J. Zhang et al. 2019). Note that the difference in the zonal-mean zonal wind between the easterly QBO and westerly QBO phases is not statistically significant in the high latitudes of the lower stratosphere in February (Fig. 9c), which can be attributed to the QBO-induced shift in the position of the stratospheric polar vortex (J. Zhang et al. 2019; Elsbury et al. 2021a). The canonical Holton–Tan effect is generally considered to be more robust in early winter from a zonal mean perspective (e.g., Dunkerton and Baldwin 1991; Lu et al. 2020), but J. Zhang et al. (2019) argued that the effect exists throughout the winter months from a horizontal field perspective. During easterly (westerly) QBO phases, the stratospheric polar vortex shifts toward Eurasia (North America) (Figs. 10a–c), leading to a zonally asymmetric structure of the subpolar zonal wind anomalies and thus weaker signal in the zonal-mean anomalies in the high latitudes of the lower stratosphere in late winter (Figs. 9a–c; J. Zhang et al. 2019).

Fig. 9.
Fig. 9.

Composites of the zonal-mean zonal wind anomalies (m s−1) for the easterly and westerly QBO years and their differences derived from (a)–(c) observations and (d)–(u) individual model simulations in February. Contours denote the climatological mean of the simulated zonal-mean zonal wind with an interval of 10 m s−1. The y axis is pressure (hPa). Dots indicate statistical significance at the 95% confidence level, and letters E and W denote the easterly and westerly QBO years, respectively.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

Fig. 10.
Fig. 10.

Composites of the geopotential height anomalies (shading; gpm) averaged over 50–10 hPa for the easterly and westerly QBO years and their differences derived from (a)–(c) observations and (d)–(u) individual model simulations in February. Dots indicate statistical significance at the 95% confidence level.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

It is shown in Fig. 9 that all the models tend to simulate a weakened (enhanced) stratospheric polar vortex during easterly (westerly) QBO phases from the zonal mean perspective in February. In more than half of the models (i.e., ACCESS-CM2, CESM2-WACCM-FV2, HadGEM3-GC31-MM, and KACE-1-0-G), the QBO-related zonal-mean zonal wind anomalies are almost nonsignificant at the 95% confidence level over the subpolar and polar regions, consistent with their observed counterparts. However, an apparent difference is found in the position of the QBO-related stratospheric polar vortex anomalies between the simulations and observations from the horizontal perspective (Fig. 10). The simulated stratospheric polar vortex is primarily centered in the polar region during both the easterly and westerly QBO phases in HadGEM3-GC31-LL (Figs. 10j–k), CESM2-WACCM-FV2 (Figs. 10g–i), and INM-CM5-0 (Figs. 10p–q), which is different from the observed one that shifts toward the Eastern (Western) Hemisphere during easterly (westerly) QBO phases (Figs. 10a,b). In the other three models, meanwhile, the QBO-related polar vortex anomalies show a shift different from the observed one. Overall, the Holton–Tan effect in late winter appears to be not well captured in all the models analyzed in this study.

These results suggest that the six CMIP6 models analyzed in this study tend to simulate a strong connection between the NAO and stratospheric polar vortex as well as a hemisphere-wide structure of the NAO during both the easterly and westerly QBO phases in late winter. However, the Holton–Tan effect, which is critical for linking the QBO and NAO, is poorly simulated in these models in late winter. In other words, the models fail to reproduce the observed modulation by the QBO of the stratospheric polar vortex and thus the spatial structure of the NAO and its climate impact in late winter. Note that Rao et al. (2020b) assessed the Holton–Tan effect in early winter in detail by using historical simulations from seven CMIP5 models and nine CMIP6 models, none of which were the same as those employed in this study. They found that the Holton–Tan effect in early winter was underestimated in the majority of their CMIP5/6 models, and a similar result is obtained for the six CMIP6 models used in this study (figures not shown). Also, Elsbury et al. (2021b) pointed out that CMIP6 models underestimate the Holton–Tan effect in midwinter.

The strong NAO–stratosphere connection seems to be a common bias that may be related to tropospheric and stratospheric climatology in the simulations (Peings et al. 2012; R. Zhang et al. 2019). When compared to the observation in boreal winter (Fig. 11), the models tend to simulate a stronger climatological-mean westerly wind near the tropopause in the middle and/or high latitudes, resulting in a positive refractive index squared (Andrews et al. 1987) in the tropopause and lower stratosphere of the mid- to high latitudes and hence providing favorable conditions for more upward wave fluxes entering the stratosphere (Matsuno 1970). This implies that the stronger westerly bias near the tropopause tends to facilitate a stronger troposphere–stratosphere coupling in the model simulations. Biases in other aspects, such as in the climatological stationary waves, may also have an impact on the NAO–stratosphere connection in the simulations, which requires further investigation but lies beyond the scope of this study.

Fig. 11.
Fig. 11.

Differences in the climatological zonal-mean zonal wind (shading; m s−1) between the simulations and observations (former minus latter) for the individual models in winter. Dots indicate statistical significance at the 95% confidence level. Contours denote refractive index squared, which is defined after Andrews et al. (1987). Contour intervals are 15, and negative values are dashed.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

5. Summary and discussion

The present study finds that the QBO has a significant modulating effect on the spatial structure of the NAO and thus its relationship with SAT anomalies over Northeast Asia in late winter (i.e., February). During the easterly QBO phases in late winter, the NAO variability is closely related to that of the Northern Hemisphere stratospheric polar vortex, implying a strong stratosphere–troposphere coupling in association with the NAO. In this case, the NAO features a hemisphere-wide structure that is quite similar to the AO pattern, leading to a wide impact of the NAO on the SAT anomalies that extend from the Euro-Atlantic sector toward Northeast Asia. Consequently, the NAO significantly correlates with SAT anomalies over Northeast Asia, including Northeast China. During the westerly QBO phases in late winter, however, the NAO has a limited connection with the Northern Hemisphere stratospheric polar vortex. In this case, the NAO tends to feature a classically regional mode that is mainly confined to the Euro-Atlantic sector, resulting in a relatively weak impact on the SAT anomalies over Northeast China. This conclusion is supported by model experiments reported by Elsbury et al. (2021a), in which it was revealed that a shift of the stratospheric polar vortex toward Eurasia under the easterly QBO background state provides favorable conditions for the enhancement of North Atlantic upward wave activity fluxes and thus troposphere–stratosphere coupling in winter.

Furthermore, the ability of state-of-the-art climate models in simulating the modulation effect of the QBO on the spatial structure and thus climate impact of the NAO has been assessed on the basis of the historical simulations of six CMIP6 models that generate the QBO reasonably during boreal winter. It is found that almost all of these models simulate a similar pattern of the NAO-associated atmospheric circulation and thus SAT anomalies over East Asia between the easterly and westerly QBO phases in late winter. Consistently, the models tend to simulate a hemisphere-wide structure of the NAO and a strong connection of the NAO with the stratospheric polar vortex during both the easterly and westerly QBO phases, which is only true during the easterly QBO phases and not in the westerly QBO phases in the observations. In other words, the observed modulation effect of the QBO on the spatial structure of the NAO and thus its relationship with Northeast China SAT anomalies is barely detectable in the simulations in late winter.

In addition, all the models poorly capture the observed Holton–Tan effect, which is critical for linking the QBO and NAO during boreal winter. Four out of the six models (ACCESS-CM2, CESM2-WACCM-FV2, HadGEM3-GC31-MM, and KACE-1-0-G) simulate a relatively weak Holton–Tan effect in late winter, which may be related to the weaker amplitude of the QBO in the simulations than in the observation (Kim et al. 2020). Although HadGEM3-GC31-LL (INM-CM5-0) simulates a weakened (enhanced) stratospheric polar vortex during the easterly (westerly) QBO phase, a relatively weak stratospheric polar vortex response is observed during the opposite QBO phase in the model. The strong connection between the simulated NAO and stratospheric polar vortex may be related to the models’ biases in simulating the stratospheric and tropospheric climatology (Peings et al. 2012; R. Zhang et al. 2019). In particular, it is found that the stronger westerly bias near the tropopause tends to facilitate a stronger troposphere–stratosphere coupling in the simulations. However, the possible cause of the model bias in simulating the winter QBO–NAO connection still requires further examination in future studies.

The modulation by the QBO of the spatial structure and climate impact of the NAO possibly results from QBO-induced changes in the extratropical stratospheric circulation (Chen and Li 2007), which further induce tropospheric circulation anomalies via the downward control principle (Haynes et al. 1991) and tropospheric eddy momentum feedback (Kidston et al. 2015). When compared to that during the westerly QBO phases, the Northern Hemisphere stratospheric polar vortex becomes weaker and thus more disturbed during the easterly QBO phases (Holton and Tan 1980; J. Zhang et al. 2019), which appears to facilitate a stronger stratosphere–troposphere coupling and thus a hemisphere-wide structure of the NAO extending into the stratosphere (Kodera et al. 1999; Kodera 2002). In particular, QBO-induced changes in the mean state may affect the NAO–stratosphere connection via the zonal flow–stationary wave interactions (Kodera et al. 1996; DeWeaver and Nigam 2000). However, how the QBO modulates the zonal flow–stationary wave interactions and thus the vertical extension of the NAO remains unclear and needs to be explored in future studies. In addition, the QBO can also exert an impact on the troposphere and near-surface climate via the subtropical route involving changes in the tropospheric subtropical jet stream (e.g., White et al. 2015; Wang et al. 2018; Elsbury et al. 2021a). The subtropical jet stream, acting as a waveguide, can significantly modulate the downstream extension of the NAO toward East Asia and the North Pacific in winter (Watanabe 2004; Zuo et al. 2015, 2016). Observational evidence indicates that the subtropical jet stream over Asia and the North Pacific shifts poleward during the easterly QBO phases when compared to that during the westerly QBO phases in late winter (Fig. 12), which therefore implies a possible role played by the subtropical jet in linking the QBO to the NAO and thus temperature anomalies over East Asia. Furthermore, it should be noted that the modulation effect of the QBO on the spatial structure of the NAO and thus the NAO–temperature relationship over Northeast Asia is only detectable in late winter, and not in early–middle winter, in the observations, which may be attributable to the stronger Holton–Tan effect in late winter than in early winter (J. Zhang et al. 2019) and the delayed response of the troposphere to the stratosphere (Kodera and Koide 1997; Baldwin and Dunkerton 1999).

Fig. 12.
Fig. 12.

Composites of the 200-hPa zonal wind anomalies (shading; m s−1) for the (a) easterly and (b) westerly QBO years, and (c) their difference (former minus latter) derived from ERA5 in February 1979–2020. Dots indicate statistical significance at the 95% confidence level. Contours denote the climatological mean of 200-hPa zonal wind with a value of 40 m s−1.

Citation: Journal of Climate 35, 24; 10.1175/JCLI-D-22-0353.1

Note that the models tend to simulate an out-of-phase relationship between the NAO and Northeast Asia temperature anomalies during both the easterly and westerly QBO phases in late winter, opposite to the observations during the easterly QBO phases. Such a difference in the simulations and observations appears to be related to model bias in simulating the NAO pattern (Figs. S7–S9). When compared to that of the observed, the northern lobe of the simulated NAO extends more eastward into the Eastern Hemisphere or even splits into two action centers (Fig. S7). Therefore, low anomalies occur over the Laptev and East Siberian Seas in the positive phase of the NAO in the simulations, and northerly anomalies along the western flank of the low favor cold temperature anomalies in Northeast Asia; and vice versa (Figs. S8 and S9). Moreover, previous studies have revealed that SAT anomalies in south central China are also significantly correlated with the NAO in mid- to late winter (Fig. 1a; Zuo et al. 2015, 2016). However, the modulation effect of the QBO on the NAO–temperature relationship is limited in south central China in late winter (Fig. 1d), which is possibly related to the different mechanisms underpinning the NAO–temperature connection in south central China and Northeast China (Zuo et al. 2015).

Acknowledgments.

This work was jointly supported by the Science Foundations of China (42122037, 41975102, 41975047), the National Key Research Program and Development of China (2018YFC1506003, 2019YFC1510104) and the Innovative Development Special Project of China Meteorological Administration (CXFZ2021Z011). The authors declared that they have no conflicts of interest to this work. The authors are grateful to the editor and the three anonymous reviewers for their insightful comments, which helped us improve the quality of this paper.

Data availability statement.

The fifth generation of atmospheric reanalysis in European Centre for Medium-Range Weather Forecasts (ERA5 reanalysis) are from https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5. The CMIP6 data are available at https://pcmdi.llnl.gov/CMIP6/. The observed surface air temperature data are provided by the National Climate Center of China Meteorological Administration and available from the corresponding author upon reasonable request.

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