Enhanced Impact of Autumn North Tropical Atlantic Sea Surface Temperature Anomalies on Subsequent Winter Snowfall in Northeast China after 2001

Shiqi Xu aChina Meteorological Administration Key Laboratory for Climate Prediction Studies, School of Atmospheric Sciences, Nanjing University, Nanjing, China
bClimate Center of Jilin Province, Jilin Province Meteorological Administration, Changchun, China
dKey Opening Laboratory for Northeast China Cold Vortex Research, China Meteorological Administration, Shenyang, China

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Yihe Fang cRegional Climate Center of Shenyang, Liaoning Province Meteorological Administration, Shenyang, China
dKey Opening Laboratory for Northeast China Cold Vortex Research, China Meteorological Administration, Shenyang, China

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Yitong Lin aChina Meteorological Administration Key Laboratory for Climate Prediction Studies, School of Atmospheric Sciences, Nanjing University, Nanjing, China
cRegional Climate Center of Shenyang, Liaoning Province Meteorological Administration, Shenyang, China
dKey Opening Laboratory for Northeast China Cold Vortex Research, China Meteorological Administration, Shenyang, China

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Xuguang Sun aChina Meteorological Administration Key Laboratory for Climate Prediction Studies, School of Atmospheric Sciences, Nanjing University, Nanjing, China

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Xueyan Yang bClimate Center of Jilin Province, Jilin Province Meteorological Administration, Changchun, China

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Zhiqiang Gong eLaboratory for Climate Studies, National Climate Research Center, China Meteorological Administration, Beijing, China

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Abstract

This study reveals that the relationship between autumn north tropical Atlantic (NTA) sea surface temperature (SST) anomalies and Northeast China’s winter snowfall (NECWS) undergoes a remarkable interdecadal enhancement after 2001. Previous research confirmed that the relationship between the NTA SST anomaly and atmospheric circulation experienced interdecadal changes after the 2000s and suggested various reasons for this phenomenon. During 1961–2000, the NTA SST anomaly has a significantly positive correlation with other oceans, especially the tropical Indian Ocean (TIO), and the latter modulates the former’s impact on atmospheric circulations over the Eurasian continent with a cancelling effect, which results in a weaker relationship of the NTA SST anomaly and NECWS. In contrast, the warm NTA SST anomaly is relatively independent from other oceans during 2001–20, and it proves to be the forcing factor for NECWS since its solo influence on the winter atmospheric circulations initiated from the North Atlantic to East Asia is more robust, featuring the negative phase of the North Atlantic Oscillation and a downstream quasi-barotropic Rossby wave train over the mid- to high latitudes of Eurasian continent. Accordingly, together with the deepened East Asian trough and the strongly northward transported humid and warm air from the western Pacific, the local significantly enhanced ascending motions with cooling temperature favor much more NECWS. The linear baroclinic model simulates the effects of NTA and TIO SST anomalies on winter atmospheric circulations, corroborating the aforementioned results. Such results can be used for the prediction of NECWS with respect to the precursor of the autumn NTA SST anomaly.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Shiqi Xu, Yihe Fang, and Yitong Lin contributed equally and should be regarded as co-first authors.

Corresponding author: Xuguang Sun, xgsun@nju.edu.cn

Abstract

This study reveals that the relationship between autumn north tropical Atlantic (NTA) sea surface temperature (SST) anomalies and Northeast China’s winter snowfall (NECWS) undergoes a remarkable interdecadal enhancement after 2001. Previous research confirmed that the relationship between the NTA SST anomaly and atmospheric circulation experienced interdecadal changes after the 2000s and suggested various reasons for this phenomenon. During 1961–2000, the NTA SST anomaly has a significantly positive correlation with other oceans, especially the tropical Indian Ocean (TIO), and the latter modulates the former’s impact on atmospheric circulations over the Eurasian continent with a cancelling effect, which results in a weaker relationship of the NTA SST anomaly and NECWS. In contrast, the warm NTA SST anomaly is relatively independent from other oceans during 2001–20, and it proves to be the forcing factor for NECWS since its solo influence on the winter atmospheric circulations initiated from the North Atlantic to East Asia is more robust, featuring the negative phase of the North Atlantic Oscillation and a downstream quasi-barotropic Rossby wave train over the mid- to high latitudes of Eurasian continent. Accordingly, together with the deepened East Asian trough and the strongly northward transported humid and warm air from the western Pacific, the local significantly enhanced ascending motions with cooling temperature favor much more NECWS. The linear baroclinic model simulates the effects of NTA and TIO SST anomalies on winter atmospheric circulations, corroborating the aforementioned results. Such results can be used for the prediction of NECWS with respect to the precursor of the autumn NTA SST anomaly.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Shiqi Xu, Yihe Fang, and Yitong Lin contributed equally and should be regarded as co-first authors.

Corresponding author: Xuguang Sun, xgsun@nju.edu.cn

1. Introduction

Northeast China (NEC) is located on the eastern coast of Eurasia, spanning mid-to-high latitudes, with long winters and cold climate. Snowfall is the main form of winter precipitation in NEC. Certain amounts of snowfall can promote the growth of plants and provide water to support habitats and cycles of life (Jonas et al. 2008; Wipf et al. 2009; Kunkel et al. 2016; Resano-Mayor et al. 2019). However, heavy snowfall can also cause severe disaster risks (Changnon and Changnon 2006; Zhou et al. 2011; Nicolet et al. 2016; Tei et al. 2020). For example, the once-in-a-century extreme snowstorm in 1983 in Heilongjiang Province in NEC caused a direct economic loss of 14.6 billion Chinese yuan (more than 2 billion U.S. dollars), and 46 people lost their lives in this event (Sun et al. 2017). In 2007, a catastrophic snowfall occurred again over NEC and resulted in similar damages to this region (Beijing Climate Center 2007).

Previous studies have found that fronts, cyclones, and inverted troughs are the main weather systems for heavy snowfall (Marwitz and Toth 1993; Market and Cissell 2002; Heo and Ha 2008; Shen et al. 2021). During a heavy snowfall event, the occurrence and development of frontogenesis or a cyclone are accompanied by different physical processes, such as unstable atmospheric conditions, heating, convergence, and evaporation of water vapor (Rosenblum and Sanders 1974; Esteban et al. 2005); the acute connection of cold and warm currents and favorable elevation are also essential (Mote et al. 1997; Jung and Kim 2009). In addition, large-scale atmospheric circulations also have important influences on the snowfall. Associated with more snowfall events in the middle and high latitudes of North America, Europe, and East Asia, the negative phases of North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) can favor the formation of blocking in the mid- to high latitudes and enhance the occurrence of southward surge of cold air (Seager et al. 2010; Liu et al. 2012; Wang and Zhou 2018). Recent studies have also shown that Northeast China’s winter snowfall (NECWS) has increased since the 1980s, which may be related to the weak winter monsoon (Wang and He 2013) and the strong Hadley cell circulation (Zhou et al. 2017).

The atmospheric circulation anomalies associated with snowfall events are the integrated effects of external forcing and internal atmosphere dynamical forcing (Ren and Zhang 2007), among which sea surface temperature (SST) is an important factor of driving the atmospheric circulations (Yang and Huang 1993). Some studies revealed that SST anomalies in the tropical Indian Ocean (TIO), the South China Sea, and the Kuroshio area had significant influences on the winter monsoon intensity (Chen 1991; Tao and Zhang 1998; Li and Sun 2004). In addition, since the North Atlantic Ocean is located upstream of the Eurasian region, it is bound to have an impact on the climate in the downstream regions. Studies have shown that SST anomalies in the Atlantic Ocean could excite anomalous wave trains along the westerly jets and influence the Eurasian atmospheric circulations (Wu et al. 2012; Han et al. 2017; Z. Chen et al. 2019), leading to an increase in the frequency of extreme precipitation over there (Tian and Fan 2013; Zhang et al. 2020). Chen et al. (2015) found that the north tropical Atlantic (NTA) SST anomaly is closely coupled with NAO. On the one hand, a North Atlantic SST tripole is formed by the NAO-related atmospheric anomalies via changing surface heat flux. On the other hand, it can affect NAO through the atmospheric transient feedback processes in turn. Furthermore, many studies pointed out that SST anomalies were was one of the main influencing factors on winter snowfall (Clark et al. 2001; Shaman and Tziperman 2005; Jin et al. 2006; Myoung et al. 2018). Results showed there was a very close simultaneous relationship between the warming of North Atlantic SST anomaly and the increased NECWS after the 1980s (Li et al. 2012), which may be linked by the enhanced meridional activities of atmospheric circulation due to the weakened westerlies and the negative phase of NAO (H. S. Chen et al. 2019). This study focuses on the linkage of NTA SST anomaly in autumn with subsequent NECWS, aiming to provide a theoretical basis and some precursors for the prediction of NECWS. We found that impact of autumn NTA SST anomaly on the subsequent NECWS has experienced a significant interdecadal change after 2001, and the underlying mechanism is further illustrated. The remainder of this paper is organized as follows. Section 2 introduces the data, methods, and numerical model used in this analysis. Section 3 examines the connection of autumn NTA SST anomaly with the subsequent NECWS, especially its interdecadal change, as well as the associated physical process. Conclusions and discussion are presented in section 4.

2. Data, methods, and the linear baroclinic model

a. Data and methods

Daily snowfall records from December 1961 to February 2021 identified by the weather phenomena from 215 stations in NEC (38°–53°N, 116°–133°E) are used in this study. Quality control of this dataset is performed by the China Meteorological Administration. In addition, the monthly reanalysis data of geopotential height, wind field, and sea level pressure (SLP), etc., with a resolution of 2.5° × 2.5° provided by NCEP–NCAR (Kalnay et al. 1996) and SST datasets (ERSSTv5) with a resolution of 2.0° × 2.0° provided by NOAA (Kaplan et al. 1998) are applied for the mechanism investigation.

The present study is focused on wintertime from December to February. As the winter spans two consecutive years, in this study the winter 2020 denotes December 2020–February 2021, and so on. The snowfall amount is the total daily snowfall in winter. The spatial distributions of 215 stations and multiyear average NECWS are shown in Fig. 1, which shows that NECWS basically follows a decreasing pattern from south to north and east to west. The average NECWS is 16.4 mm, with a minimum of 7.1 mm (1995) and a maximum of 29.8 mm (2019), and there is a significant interdecadal trend (Fig. 2). To emphasize the interannual variability, all of the data are removed linear trends before being analyzed.

Fig. 1.
Fig. 1.

Spatial distributions of 215 stations (red dots) and multiyear average NECWS (shaded; mm).

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

Fig. 2.
Fig. 2.

Time series of the NECWS (bars; mm) and linear trend (dashed line) during 1961–2020.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

To investigate the relationship between SST anomaly and NECWS, two SST anomaly indices are defined in this study. One is TIO SST anomaly index (TIO-I), which is the value of the area-averaged SST anomaly in region of the tropical Indian Ocean (20°S–20°N, 40°–110°E), and the other is the NTA SST anomaly index (NTA-I), which is the value of the area-averaged SST anomaly in region of the north tropical Atlantic (6°–24°N, 14°–58°W).

The main analysis method is regression. We use the linear regression model in this study to discuss the effects of SST anomalies on the NECWS and atmospheric circulations. In addition, the regression equation of SST anomaly index in the key region with NECWS is established. The variance ratio of regression result with NECWS is calculated, and serves as the contribution rate of effect of autumn SSTA on NECWS (Shi 2002).

The T-N wave-activity flux [named for Takaya and Nakamura (2001)] can well describe the Rossby longwave disturbance of the westerlies with a large amplitude in the nonuniform zonal circulation (Shi et al. 2017). In this study, the energy propagation of atmospheric disturbance is diagnosed using the computational formula of the wave-activity flux vector presented by Takaya and Nakamura (2001). Correlation analysis is also used in this study, and the two-tailed Student’s t test is applied for the significance test through the whole paper.

b. The linear baroclinic model

The linear baroclinic model (LBM) was developed by Watanabe and Kimoto (2000), and the model setup is basically the same as in Sun et al. (2010). It is a spectral model with T42 of horizontal resolution (corresponding roughly to 2.8° × 2.8° in latitude and longitude) and 20 unevenly spaced sigma (orography following) levels in the vertical. Refer to Sun et al. (2010) for more details of the model configurations. Since convection-induced diabatic heating is mainly in the midtroposphere (Ling and Zhang 2013), the LBM is forced by some idealized diabatic heating anomalies centered at the 0.45 sigma level and then run for 30 days. Actually, the model solution reaches its steady state after about 15 days of integration. The LBM responses at day 25 are shown in this study, and they are used to show the linear influences of SST forcing in the NTA and TIO on the winter Eurasian atmospheric circulation (Fig. 10).

3. Results

a. Relationship between preceding SST anomalies and NECWS

To investigate the relationship between SST anomalies and NECWS, correlations of NECWS with SST anomalies in previous autumn (September–November) and simultaneous winter (December–February) during 1961–2020 are calculated. As shown in Fig. 3, associated with increased NECWS, remarkable SST anomalies appear in the North Atlantic and parts of the North Pacific. The SST anomaly correlation pattern in previous autumn is different from that in simultaneous winter, especially in the TIO and North Pacific, but the significant positive correlation in NTA is persistent. In other words, there is a significant positive correlation between NTA SST anomaly and NECW, which can last from autumn to winter. In terms of forecasting and persistence of SST anomalies, the analysis below will specifically investigate the impact of autumn NTA SST anomaly on subsequent NECWS.

Fig. 3.
Fig. 3.

Correlation coefficients of NECWS with SST anomaly field in (a) the previous autumn and (b) the simultaneous winter during 1961–2020. The dotted area indicates significance at the 95% confidence level.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

As shown in Fig. 4b, both NECWS and the autumn NTA SST anomaly have strong interannual variabilities, and they are significantly correlated with each other (0.25, above the 90% confidence level). To test the stability of relationship between autumn NTA-I and NECWS, running correlations with a 17-yr window are employed during 1961–2020 (Fig. 4d). The result shows a dramatic increase of running correlation coefficients since 2009 (around 0.60). Combined with Fig. 4c, it can be seen that their relationship is unstable and it changes from weaker to noticeably robust positive after 2001. In the century from 2000 to 2020, the stronger the autumn NTA-I is, the more NECWS there is (Fig. 5b). To further confirm the robustness of the change in the correlation, we also display and examine the running correlation in 11- and 21-yr windows (figures not shown). There is no essential difference in the results.

Fig. 4.
Fig. 4.

(a) Standardized series of autumn NTA-I (red solid line) and winter NTA-I (blue solid line). (b) Standardized series of NTA-I (red solid line) and NECWS (blue solid line). (c) Standardized series of NTA-I (red solid line) and TIO-I (blue solid line). (d) 17-yr running correlation coefficients between NTA-I and NECWS (blue solid line), and between NTA-I and TIO-I (red solid line) during 1961–2020. The black dashed horizontal line indicates the 95% confidence level.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

Fig. 5.
Fig. 5.

Regression patterns of the NECWS anomalies (shading; mm) regressed onto the NTA-I in (a) period I (1961–2000) and (b) period II (2001–20). Red dots indicate stations with significance at the 95% confidence level.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

To better understand the interdecadal change of the relationship between autumn NTA SST anomaly and NECWS, the whole study period 1961–2020 is divided into two parts, 1961–2000 (period I) and 2001–20 (period II), and accordingly the correlation coefficients with and the contribution rates of autumn NTA-I to the NECWS are recalculated before and after 2001, separately. In period I, the correlation is not significant, with a value of only 0.03, and neither is the contribution rate of NTA-I, with a very small value of 0.89%. However, in period II the correlation rises sharply and it reaches up to 0.53 (above the 95% confidence level), and the contribution rate of NTA-I is much higher (29.32%) too.

To summarize the changing impact of NTA-I on NECWS, the NECWS anomalies are regressed onto the autumn NTA-I for the two periods (Figs. 5a,b). It is clearly shown that the NTA-related NECWS exhibits two different anomaly patterns during the two periods. In period II, when autumn NTA-I is stronger, NECWS is heavier with the largest center of positive anomalies in the eastern NEC (above 20 mm) (Fig. 5b). In contrast, NECWS anomalies in period I demonstrate a tripole-like pattern, with weakly positive anomalies in the central NEC and weakly negative anomalies in the northwestern and eastern NEC (Fig. 5a), corresponding to a much weaker relationship between autumn NTA-I and NECWS (Fig. 4d).

b. Interdecadal changes in the NTA-related atmospheric circulation anomalies

According to the above analyses, it is interesting to note that the NECWS amounts are different or even opposite (Figs. 5a,b) despite the similar autumn NTA SST anomaly during the two periods. We first investigate the persistence of the SST anomaly. The correlation coefficient between autumn NTA-I and the subsequent winter NTA-I is 0.78 during 1961–2020 (Fig. 4a); due to the “memory effect” of the ocean, the SST anomaly has a seasonal persistence (Figs. 3 and 9), and its climate effect can be postponed (Chen et al. 2013). Considerable efforts have been made to delineate the relationship between the tropical/midlatitude ocean and the global climate, as well as the atmospheric circulations at low and even mid- to high latitudes with observed data and both realistic and idealized numerical experiments (Nitta and Yamada 1989; Trenberth and Hurrell 1994; Deser and Phillips 2006; Liu and Alexander 2007; Chu et al. 2018; Zhao et al. 2019). Here the winter atmospheric circulation anomalies are regressed onto the autumn NTA-I for the two periods (Figs. 68).

Fig. 6.
Fig. 6.

Regression patterns of winter atmospheric circulation anomalies regressed onto the NTA-I for (a),(b) 200-and (c),(d) 500-hPa height geopotential (shading; gpm) and the associated wave-activity fluxes (vector; m2 s−2) and (e),(f) SLP (shading; hPa) during (left) period I and (right) period II. Dotted areas indicate significance at the 95% confidence level.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

Fig. 7.
Fig. 7.

Regression patterns of winter atmospheric circulation anomalies regressed onto the NTA-I for (a),(b) 850-hPa horizontal wind (vector; m s−1) and (c),(d) vertically integrated moisture flux (vector; kg m s−1) and divergence of the moisture flux (shaded; 10−5 kg m2 s−1) in (left) period I and (right) period II. Red vectors indicate significance at the 95% confidence level.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

Fig. 8.
Fig. 8.

Vertical cross-section regression patterns of winter atmospheric circulation anomalies regressed onto the NTA-I for average air temperature (shaded; °C) and vertical velocity (contour; 10−2 Pa s−1) along 116°–133°E in (a) period I and (b) period II. Dotted areas indicate significance at the 95% confidence level. The red contour indicates the annual mean air temperature of 0°C.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

During period II, in terms of the warm NTA SST anomaly in autumn, winter geopotential height at 200 hPa shows positive anomalies in both the NTA and the subpolar North Atlantic and negative anomaly in the midlatitude North Atlantic (Fig. 6b). A wave pattern starts from the Atlantic and propagates eastward to Europe. This wave pattern bifurcates into two branches with one turning southeastward and equatorward to North Africa and the other extending eastward over the Eurasian continent. The latter can diffuse into Northeast Asia through an arching path. Correspondingly, obvious positive and negative anomaly centers extend zonally from the North Atlantic to the Okhotsk Sea through the Eurasian continent, forming a distribution pattern like the Eurasian teleconnection (EU) (Wallace and Gutzler 1981), which indicates that the warm NTA SST anomaly can have great impacts on the downstream Eurasian regions, especially central Asia and East Asia, where the positive and significantly negative anomaly centers reside in, respectively. The atmospheric circulation at 500 hPa (Fig. 6d) is same as that at 200 hPa. The significantly negative 500-hPa geopotential height anomaly is evident over East Asia, which means the East Asian trough is remarkably strengthened and deepened. In addition, the SLP anomaly (Fig. 6f) is clearly positive throughout the high latitudes and negative in the middle and low latitudes, which is similar to the negative phase of the NAO and AO.

Similarly, the large-scale cyclonic wind vector anomaly at 850 hPa dominates East Asia, and NEC is located on the eastern side of the anomalous cyclonic circulation and controlled by the anomalous southeasterly wind from the western Pacific along the coast of East Asia (Fig. 7b), which favors the transportation of warm and humid water vapor from the west Pacific to NEC with convergence in NEC (Fig. 7d), resulting in heavy snowfall. At the same time, the anomalous northwesterly wind on the western side of the anomalous cyclonic circulation may intensify the East Asian winter monsoon in the inland areas of East Asia, likely causing strong cooling and less precipitation over there. Combining the characteristics of anomalous low-level and mid/high-level circulations, we can find that circulation system affecting the NECWS is deep, with a quasi-barotropic structure of local large-scale low pressure anomaly.

During period I, features of the linear regression of winter geopotential height at 200 hPa and the associated wave-activity flux anomalies against the autumn NTA-I also show a wavelike pattern from the North Atlantic to the North Pacific along the mid- to high latitudes of the Eurasian continent, which bears some resemblance to that during period II but with much weaker amplitude and lower level of statistical significance in East Asia (Fig. 6a). The wave pattern starts from the North Atlantic can only propagate eastward to west Europe. On the other hand, associated with the autumn NTA SST anomaly, geopotential height at 200 hPa is increased in the low latitudes throughout the Indo-Pacific basin besides NTA, with the largest positive correlation center over South Asia. The atmospheric circulation at 500 hPa is same as that at 200 hPa (Fig. 6c). At the same time, SLP anomalies exhibit a meridional dipole pattern with two active centers over the North Atlantic (Fig. 6c), which resembles the NAO patterns like period II. However, the most prominent distinction is that the extent of the two active centers expands eastward, especially in the northern active center. Correspondingly, the western part of East Asia is controlled by northeasterly wind anomalies. Dry and cold air is transported to NEC (Fig. 7a), and convergence of water vapor in NEC is insignificant (Fig. 7c), which is not conducive to snowfall over there, especially heavy snowfall.

To further show the vertical structures of atmospheric circulations for the NECWS due to the NTA SST anomaly, vertical cross-section regressions of mean air temperature and vertical velocity in winter with autumn NTA-I are calculated along the 116°–133°E (Fig. 8). During period II, vertical velocity over NEC (40°–53°N) shows a significant negative anomaly from 1000 to 200 hPa (Fig. 8b), indicating that the warm NTA SST anomaly tends to generate strong ascending motion over NEC, which favors much more snowfall. Usually, precipitation occurs as snowfall when low-level temperature is below 0°C. The red contour in Fig. 8 shows the position where annual mean air temperature is 0°C, and we can see that the air temperatures from high to low levels are all below 0°C in NEC. We also notice that negative air temperature anomalies are confined to below 700 hPa (Fig. 8b). It is possible that the low air temperature is a result of more snowfall. Less solar radiation can reach the surface (there is more upward solar radiation flux anomaly at the surface) due to increased cloudiness accompanying snowfall, and more snow cover reflects more shortwave radiation reaching the surface (Fig. 9b), which leads to low land surface temperature. In turn, the low land surface temperature may be accompanied by low surface air temperature through reduced upward sensible heat flux (Fig. 9d).

Fig. 9.
Fig. 9.

Regression patterns of (a),(b) upward solar radiation flux anomaly at surface (shaded; W m−2) and surface air temperature anomaly (contour; °C) and (c),(d) sensible heat net flux anomaly (shaded; W m−2) and surface air temperature anomaly (contour; °C) regressed onto the NTA-I during (left) period I and (right) period II. Dotted areas indicate significance at the 95% confidence level for the shaded sector.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

However, during period I the vertical velocity anomaly over NEC is much weaker than during period II, in accordance with the regression of geopotential height at 500 hPa as well (Figs. 6a,b). Therefore, the vertical velocity in the mid- to lower troposphere over NEC is negatively insignificantly correlated with the autumn NTA SST anomaly, as is the air temperature (Figs. 8a and 9a,c). It indicates that even though the autumn NTA may have similarly warmer SST anomalies during periods I and period II, it is unfavorable for NECWS.

c. Possible reasons for the interdecadal changes of NTA-related atmospheric circulation anomalies

Previous studies have demonstrated that the NTA SST anomalies have a strong connection with the SST anomalies in the subtropics and midlatitudes of the North Atlantic Ocean after the late 1990s (Chen et al. 2015; Z. Chen et al. 2019). As for the source of the relationship between the autumn NTA SST anomaly and subsequent NECWS, the global SST anomaly regression patterns against autumn NTA-I are shown in Fig. 10 for the two periods. Figures 10c and 10d illustrate that the NTA SST warm anomaly during period II is accompanied by cold and warm SST anomalies in the midlatitude and subpolar North Atlantic, respectively, which together form a clear tripole SST anomaly pattern. Such a tripole SST anomaly pattern can persist from autumn to the following winter, and it can further induce the negative phase of NAO (Fig. 6f) via wave–current interaction and Rossby wave response (Chen et al. 2015; Peng et al. 2003; Wu et al. 2011; Z. Chen et al. 2019). Numerous studies have confirmed that the relationship between interannual variations of NTA SST anomaly and atmospheric circulation experienced obvious interdecadal changes around the 2000s (Wu et al. 2011; Chen et al. 2015; Han et al. 2018; Z. Chen et al. 2019). The atmospheric response to SST anomalies may depend not only on the amplitude of the SST anomalies, but also on the mean SST. The winter mean NTA SST change may be a plausible reason for several changes in the NAO–NTA SST connection (Chen et al. 2015). Under a higher mean NTA SST after the 2000s (Prigent et al. 2020), NTA SST anomalies induce larger wind anomalies over the North Atlantic that produce a tripole SST anomaly pattern and amplify NTA SST anomalies, and then exert a significant influence on the downstream atmospheric circulation through air–sea interaction (Chen et al. 2015).

Fig. 10.
Fig. 10.

Regression patterns of (a),(c) autumn and (b),(d) winter SST anomalies (shading; °C) regressed onto the NTA-I in (top) period I and (bottom) period II. Dotted areas indicate significance at the 95% confidence level.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

In addition to the above factors, what other factors may contribute to the interdecadal changes? It can be seen that significant warm SST anomalies mainly occur in North Atlantic from autumn to winter during period II (Figs. 10c,d), which may be due to the fact that NTA SST variation is not synchronized with other oceans and is more independent after 2001. By contrast, during period I the autumn NTA SST anomaly has significant simultaneous relationships with those in tropical ocean regions such as the TIO and tropical western Pacific (TWP) (Fig. 10a), and this anomaly pattern is also present and more pronounced in the subsequent winter (Fig. 10b), which indicates that the weak relationship between NTA-I and NECWS during period I may also be related to the modulation effect of TIO and TWP (Annamalai et al. 2007; Hu and Fedorov 2020).

For period I, based on observational facts and numerical experiments, Chu et al. (2018) confirmed that TIO and TWP warming contributes significantly to the positive phase of NAO in the North Atlantic and to the atmospheric circulation anomalies in Eurasia, with TIO warming having the most pronounced effect on the atmospheric circulation. Therefore, we focus on the role of the TIO SST anomaly. Figures 4c and 4d depict that TIO-I and NTA-I have significant interdecadal changes. It can be seen with the increase of the relationship between TIO-I and NTA-I, the influence of NTA-I on NECWS is weakened. Specifically, the relationship between TIO-I and NTA-I is significantly strong before 2001, being especially prominent in the 1980s and 1990s, and this period is the weakest period between NAT-I and NECWS. After 2001, the relationship between NTA-I and TIO-I is significantly weakened, and the impact of NTA-I on NECWS is significantly enhanced. The correlation coefficient between the running correlation coefficients between NTA-I and NECWS and the running correlation coefficients between NTA-I and TIO-I is less than −0.77 during 1961–2020, which is above 99% confidence level.

We use the LBM experiment to explain the specific processes of impacts of SST anomalies in the NTA and TIO on the winter atmospheric circulations. Figure 11a shows that when the forcing is prescribed in the NTA, a teleconnection wave train with a “+ − + − +” pattern emanates northeastward from the NTA to the Okhotsk Sea. Accordingly, as direct Rossby waves response to the diabatic heating, an 850-hPa cyclone appears over the Northeast Asia, and it generates southeasterly wind blowing from the northwest Pacific to the NEC (Fig. 11a). The distribution of height and wind anomalies resembles the observations (Figs. 6d and 7b), although there are some differences in the magnitude and location of height and wind anomalies. Since it is the linear response to the diabatic heating over the NTA, we can easily deduce that the reversed response pattern in Fig. 11a must be similar to that in Fig. 6d. Therefore, as for the winter atmospheric circulation anomalies over East Asia in periods I and II, the anomalous diabatic heating over the NTA play critical roles.

Fig. 11.
Fig. 11.

Winter atmospheric circulation anomalies for 500-hPa height geopotential (shading; gpm) and 850-hPa horizontal wind (vector; m s−1) in the LBM experiments in response to imposed anomalous heating over the (a) NTA and (b) TIO.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

Similarly, when the diabatic heating is prescribed over the TIO in the LBM (Fig. 11b), the effect is very different from that in Fig. 11a. The TIO-only warming causes a dipole pattern with negative height anomalies north of 60°N and positive height anomalies south of it over the North Atlantic sector, resembling a positive phase NAO although it is slightly westward shifted, as well as substantial negative height anomalies over the Eurasian continent main sector. Most importantly, the TIO warming tends to cause positive height anomalies over Northeast Asia and North Pacific sector, as the northeasterly wind anomalies invade NEC. The effect of the warm TIO SST anomaly on atmospheric circulations is generally opposite to that induced by the warm NTA SST anomaly. Although the LBM experiment is idealized and only shows the linear influence of SST anomalies in the NTA and TIO on the winter Eurasian atmospheric circulation, it is still a promising tool to demonstrate those teleconnection links. Due to the superposition of the NTA and TIO warming, the observed atmospheric circulations are different in period I and period II. Overall, the northern TIO cyclone and Northeast Asian anticyclone in the model response provide substantial evidence of the impacts of TIO SST anomalies on the winter Asian atmospheric circulations in period I, modulating the NTA SST anomaly-triggered atmospheric circulations with a cancelling effect.

4. Conclusions and discussion

This study reveals that the connection of autumn NTA SST anomaly with the following NECWS has undergone a pronounced interdecadal change since 2001. Previous research demonstrated the relationship between interannual variations of NTA SST anomaly and atmospheric circulation experienced obvious interdecadal changes due to the amplitude of SST anomalies and the mean SST. Our results also suggest that the TIO SST anomaly plays an important modulation role. Due to the cancelling effect of the TIO that closely accompanies the NTA, the correlation of the autumn NTA SST anomaly with the following NECWS is much weaker and insignificant during 1961–2000.

During the period of 2001–20, the NTA SST anomaly in autumn is relatively independent of other oceans, and it can persist from autumn to winter, acting as the primary forcing factor for the NECWS. Accordingly, in terms of the significant warm NTA SST anomaly, the response of negative phase of NAO is first generated, which is accompanied by a downstream Rossby wave train along the mid- to high latitudes from the North Atlantic to the North Pacific. Furthermore, the wave energy mainly converges over East Asia in winter, which produces and maintains a robust quasi-barotropic low over there, greatly deepening the East Asian trough. At the same time, a low-level large cyclonic anomaly dominates the East Asia; on its eastern side, the anomalous strong southeast wind brings warm and humid water vapor to the NEC from the western Pacific along the coast of East Asia. In the mid- to lower troposphere over NEC, ascending motions and decreased temperature are greatly enhanced, contributing to much more NECWS (Fig. 12).

Fig. 12.
Fig. 12.

Schematic diagram for the pathway of autumn warm NTA SST anomaly influencing NECWS during period II. The letter H (L) indicates the center of the anomalous geopotential high (low) at 500 hPa, and the letter C indicates a cyclonic anomaly.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

For the period of 1961–2000, the autumn SST anomaly in the NTA has a significant positive correlation with those in other oceans, and its influence on winter atmospheric circulations is modulated by those in other oceans, especially the TIO. Warm SST anomalies in the TIO can lead to a positive phase of NAO and weak Rossby wave trains over the mid- to high-latitude Eurasian continent, which is generally opposite to those induced by the warm SST anomaly in NTA (Fig. 13), modulating the NTA SST anomaly-triggered atmospheric circulations with a canceling effect. On the other hand, due to the warm SST anomaly in TIO, geopotential height is greatly enhanced throughout the Indo-Pacific basin in the low latitudes, and it helps to shift the East Asian trough eastward to the North Pacific together with the NTA SST anomaly caused by a high geopotential height anomaly over central Asia. Meanwhile, in the low levels of the anomalous quasi-barotropic atmospheric circulations, the northwest wind anomaly covers almost the whole of East Asia with dry and cold air because of the combined impacts of both the NTA and TIO. Accordingly, weak upward motions and decreased temperature of the mid- to lower troposphere occur over the NEC, which is unfavorable for the NECWS.

Fig. 13.
Fig. 13.

Schematic diagram for the pathway of warm TIO SST anomaly influencing NECWS during period I. The letter H (L) indicates the center of the anomalous geopotential high (low) at 500 hPa.

Citation: Journal of Climate 36, 2; 10.1175/JCLI-D-22-0333.1

It is also worth noticing that along with global warming, there is significant warming in both the NTA and TIO after the 2000s (Hu and Fedorov 2020). If both were to warm at the same time after 2001, this would lead to a phenomenon similar to that in Fig. 5a (i.e., more snow in the north and less snow in the south of NEC). However, why did the independence of autumn and winter SST anomalies in the NTA change around 2000? In addition, we find that the contribution rate of autumn NTA-I to NECWS is 29.32% after 2001 (section 3). There are other forcing factors, such as earlier soil moisture and Arctic sea ice (Fan and Tian 2013; H. S. Chen et al. 2019), that also have impacts on snowfall in the NEC. How do these factors interact to influence NECWS? These questions will be discussed in future work.

In this study, the NCEP–NCAR reanalysis dataset is used for analysis. To further confirm the atmospheric processes connecting the SST and NECWS, analyses are also conducted using reanalysis data from the NOAA-CIRES-DOE twentieth-century dataset (https://psl.noaa.gov/data/gridded/data.20thC_ReanV3.html). The results of the two reanalysis datasets are consistent (figures not shown); thus, the findings of this study are robust. In summary, the autumn NTA SST anomaly has a significant impact on the variability of NECWS, but the TIO SST anomaly also has modulation. We should pay attention to the NTA SST anomaly as well as the variation of TIO SST anomaly in the operational forecasting of NECWS.

Acknowledgments.

This research is jointly supported by the National Natural Science Foundation of China (41775074, 42005037, and 41875100); the Special project for innovation and development of China Meteorological Administration (CXFZ2021J022 and CXFZ2021Z034); the Liaoning Provincial Natural Science Foundation Project (PhD Start-up Research Fund 2019-BS-214); and the Research Project of the Institute of Atmospheric Environment, CMA (2020SYIAE08).

Data availability statement.

Daily snowfall records from observation stations in NEC can be obtained from the lead author. The NCEP–NCAR reanalysis datasets can be downloaded from https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html. The SST datasets provided by NOAA are from https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html.

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Save
  • Annamalai, H., H. Okajima, and M. Watanabe, 2007: Possible impact of the Indian Ocean SST on the Northern Hemisphere circulation during El Niño. J. Climate, 20, 31643189, https://doi.org/10.1175/JCLI4156.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beijing Climate Center, 2007: Monthly climate impact assessment report in China. https://cmdp.ncc-cma.net/influ/moni_china.php.

  • Changnon, S. A., and D. Changnon, 2006: A spatial and temporal analysis of damaging snowstorms in the United States. Nat. Hazards, 37, 373389, https://doi.org/10.1007/s11069-005-6581-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, H. S., and Coauthors, 2019: Interdecadal variation of heavy snowfall in northern China and its linkages with atmospheric circulation and Arctic sea ice (in Chinese with English abstract). Trans. Atmos. Sci., 42, 6677, https://doi.org/10.13878/j.cnki.dqkxxb.20181212001.

    • Search Google Scholar
    • Export Citation
  • Chen, L. J., Y. Yuan, M. Yang, J. Zuo, and W. Li, 2013: A review of physical mechanisms of the global SSTA impact on EASM (in Chinese). J. Appl. Meteor. Sci., 24, 521532, https://qikan.camscma.cn/article/id/20130502?viewType=HTML.

    • Search Google Scholar
    • Export Citation
  • Chen, L. T., 1991: Effect of zonal difference of sea surface temperature anomalies in the Arabian Sea and the South China Sea on summer rainfall over the Yangtze River (in Chinese). Chin. J. Atmos. Sci., 15, 3342.

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